Module Smaws_Client_ComputeOptimizer.Types

type nonrec volume_type = string
type nonrec volume_size = int
type nonrec volume_arn = string
type nonrec account_id = string
type nonrec volume_baseline_iop_s = int
type nonrec volume_burst_iop_s = int
type nonrec volume_baseline_throughput = int
type nonrec volume_burst_throughput = int
type nonrec root_volume = bool
type nonrec volume_configuration = {
  1. root_volume : root_volume option;
    (*

    Contains the image used to boot the instance during launch.

    *)
  2. volume_burst_throughput : volume_burst_throughput option;
    (*

    The burst throughput of the volume.

    *)
  3. volume_baseline_throughput : volume_baseline_throughput option;
    (*

    The baseline throughput of the volume.

    *)
  4. volume_burst_iop_s : volume_burst_iop_s option;
    (*

    The burst IOPS of the volume.

    *)
  5. volume_baseline_iop_s : volume_baseline_iop_s option;
    (*

    The baseline IOPS of the volume.

    *)
  6. volume_size : volume_size option;
    (*

    The size of the volume, in GiB.

    *)
  7. volume_type : volume_type option;
    (*

    The volume type.

    The volume types can be the following:

    • General Purpose SSD gp2 and gp3
    • Provisioned IOPS SSD io1, io2, and io2 Block Express
    • Throughput Optimized HDD st1
    • Cold HDD sc1
    • Magnetic volumes standard
    *)
}

Describes the configuration of an Amazon Elastic Block Store (Amazon EBS) volume.

type nonrec ebs_finding =
  1. | NOT_OPTIMIZED
  2. | OPTIMIZED
type nonrec ebs_metric_name =
  1. | VOLUME_THROUGHPUT_EXCEEDED
  2. | VOLUME_IOPS_EXCEEDED
  3. | VOLUME_WRITE_BYTES_PER_SECOND
  4. | VOLUME_READ_BYTES_PER_SECOND
  5. | VOLUME_WRITE_OPS_PER_SECOND
  6. | VOLUME_READ_OPS_PER_SECOND
type nonrec metric_statistic =
  1. | AVERAGE
  2. | MAXIMUM
type nonrec metric_value = float
type nonrec ebs_utilization_metric = {
  1. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  2. statistic : metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  3. name : ebs_metric_name option;
    (*

    The name of the utilization metric.

    The following utilization metrics are available:

    • VolumeReadOpsPerSecond - The completed read operations per second from the volume in a specified period of time.

      Unit: Count

    • VolumeWriteOpsPerSecond - The completed write operations per second to the volume in a specified period of time.

      Unit: Count

    • VolumeReadBytesPerSecond - The bytes read per second from the volume in a specified period of time.

      Unit: Bytes

    • VolumeWriteBytesPerSecond - The bytes written to the volume in a specified period of time.

      Unit: Bytes

    • VolumeIOPSExceeded - Indicates whether the volume's provisioned IOPS performance was exceeded in a specified period of time. A value of 1 means the provisioned IOPS were exceeded; a value of 0 means they were not.

      Unit: None

    • VolumeThroughputExceeded - Indicates whether the volume's provisioned throughput performance was exceeded in a specified period of time. A value of 1 means the provisioned throughput was exceeded; a value of 0 means it was not.

      Unit: None

    *)
}

Describes a utilization metric of an Amazon Elastic Block Store (Amazon EBS) volume.

Compare the utilization metric data of your resource against its projected utilization metric data to determine the performance difference between your current resource and the recommended option.

type nonrec ebs_utilization_metrics = ebs_utilization_metric list
type nonrec look_back_period_in_days = float
type nonrec performance_risk = float
type nonrec rank = int
type nonrec savings_opportunity_percentage = float
type nonrec currency =
  1. | CNY
  2. | USD
type nonrec value = float
type nonrec estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings amount possible, based on On-Demand instance pricing, by adopting Compute Optimizer recommendations for a given resource.

For more information, see Estimated monthly savings and savings opportunities in the Compute Optimizer User Guide.

type nonrec savings_opportunity = {
  1. estimated_monthly_savings : estimated_monthly_savings option;
    (*

    An object that describes the estimated monthly savings amount possible by adopting Compute Optimizer recommendations for a given resource. This is based on the On-Demand instance pricing..

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer recommendations for a given resource.

    *)
}

Describes the savings opportunity for recommendations of a given resource type or for the recommendation option of an individual resource.

Savings opportunity represents the estimated monthly savings you can achieve by implementing a given Compute Optimizer recommendation.

Savings opportunity data requires that you opt in to Cost Explorer, as well as activate Receive Amazon EC2 resource recommendations in the Cost Explorer preferences page. That creates a connection between Cost Explorer and Compute Optimizer. With this connection, Cost Explorer generates savings estimates considering the price of existing resources, the price of recommended resources, and historical usage data. Estimated monthly savings reflects the projected dollar savings associated with each of the recommendations generated. For more information, see Enabling Cost Explorer and Optimizing your cost with Rightsizing Recommendations in the Cost Management User Guide.

type nonrec ebs_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

An object that describes the estimated monthly savings possible by adopting Compute Optimizer’s Amazon EBS volume recommendations. This includes any applicable discounts.

type nonrec ebs_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : ebs_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer’s Amazon EBS volume recommendations. This saving includes any applicable discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost after applying the specific discounts. This saving can be achieved by adopting Compute Optimizer’s Amazon EBS volume recommendations.

    *)
}

Describes the savings opportunity for Amazon EBS volume recommendations after applying specific discounts.

type nonrec volume_recommendation_option = {
  1. savings_opportunity_after_discounts : ebs_savings_opportunity_after_discounts option;
    (*

    An object that describes the savings opportunity for the Amazon EBS volume recommendation option with specific discounts. Savings opportunity includes the estimated monthly savings and percentage.

    *)
  2. savings_opportunity : savings_opportunity option;
    (*

    An object that describes the savings opportunity for the EBS volume recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage.

    *)
  3. rank : rank option;
    (*

    The rank of the volume recommendation option.

    The top recommendation option is ranked as 1.

    *)
  4. performance_risk : performance_risk option;
    (*

    The performance risk of the volume recommendation option.

    Performance risk is the likelihood of the recommended volume type meeting the performance requirement of your workload.

    The value ranges from 0 - 4, with 0 meaning that the recommended resource is predicted to always provide enough hardware capability. The higher the performance risk is, the more likely you should validate whether the recommendation will meet the performance requirements of your workload before migrating your resource.

    *)
  5. configuration : volume_configuration option;
    (*

    An array of objects that describe a volume configuration.

    *)
}

Describes a recommendation option for an Amazon Elastic Block Store (Amazon EBS) instance.

type nonrec volume_recommendation_options = volume_recommendation_option list
type nonrec last_refresh_timestamp = Smaws_Lib.CoreTypes.Timestamp.t
type nonrec current_performance_risk =
  1. | HIGH
  2. | MEDIUM
  3. | LOW
  4. | VERY_LOW
type nonrec ebs_savings_estimation_mode_source =
  1. | COST_OPTIMIZATION_HUB
  2. | COST_EXPLORER_RIGHTSIZING
  3. | PUBLIC_PRICING
type nonrec ebs_savings_estimation_mode = {
  1. source : ebs_savings_estimation_mode_source option;
    (*

    Describes the source for calculating the savings opportunity for Amazon EBS volumes.

    *)
}

Describes the savings estimation mode used for calculating savings opportunity for Amazon EBS volumes.

type nonrec look_back_period_preference =
  1. | DAYS_93
  2. | DAYS_32
  3. | DAYS_14
type nonrec ebs_effective_recommendation_preferences = {
  1. look_back_period : look_back_period_preference option;
    (*

    The number of days for which utilization metrics were analyzed for the volume.

    *)
  2. savings_estimation_mode : ebs_savings_estimation_mode option;
    (*

    Describes the savings estimation mode preference applied for calculating savings opportunity for Amazon EBS volumes.

    *)
}

Describes the effective recommendation preferences for Amazon EBS volumes.

type nonrec tag_key = string
type nonrec tag_value = string
type nonrec tag = {
  1. value : tag_value option;
    (*

    One part of a key-value pair that make up a tag. A value acts as a descriptor within a tag category (key). The value can be empty or null.

    *)
  2. key : tag_key option;
    (*

    One part of a key-value pair that makes up a tag. A key is a general label that acts like a category for more specific tag values.

    *)
}

A list of tag key and value pairs that you define.

type nonrec tags = tag list
type nonrec volume_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to your Amazon EBS volume recommendations.

    *)
  2. effective_recommendation_preferences : ebs_effective_recommendation_preferences option;
    (*

    Describes the effective recommendation preferences for Amazon EBS volume.

    *)
  3. current_performance_risk : current_performance_risk option;
    (*

    The risk of the current EBS volume not meeting the performance needs of its workloads. The higher the risk, the more likely the current EBS volume doesn't have sufficient capacity.

    *)
  4. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the volume recommendation was last generated.

    *)
  5. volume_recommendation_options : volume_recommendation_options option;
    (*

    An array of objects that describe the recommendation options for the volume.

    *)
  6. look_back_period_in_days : look_back_period_in_days option;
    (*

    The number of days for which utilization metrics were analyzed for the volume.

    *)
  7. utilization_metrics : ebs_utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the volume.

    *)
  8. finding : ebs_finding option;
    (*

    The finding classification of the volume.

    Findings for volumes include:

    • NotOptimized—A volume is considered not optimized when Compute Optimizer identifies a recommendation that can provide better performance for your workload.
    • Optimized—An volume is considered optimized when Compute Optimizer determines that the volume is correctly provisioned to run your workload based on the chosen volume type. For optimized resources, Compute Optimizer might recommend a new generation volume type.
    *)
  9. current_configuration : volume_configuration option;
    (*

    An array of objects that describe the current configuration of the volume.

    *)
  10. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the volume.

    *)
  11. volume_arn : volume_arn option;
    (*

    The Amazon Resource Name (ARN) of the current volume.

    *)
}

Describes an Amazon Elastic Block Store (Amazon EBS) volume recommendation.

type nonrec volume_recommendations = volume_recommendation list
type nonrec volume_arns = volume_arn list
type nonrec very_low = Smaws_Lib.CoreTypes.Int64.t
type nonrec customizable_metric_name =
  1. | MEMORY_UTILIZATION
  2. | CPU_UTILIZATION
type nonrec customizable_metric_threshold =
  1. | P99_5
  2. | P95
  3. | P90
type nonrec customizable_metric_headroom =
  1. | PERCENT_0
  2. | PERCENT_10
  3. | PERCENT_20
  4. | PERCENT_30
type nonrec customizable_metric_parameters = {
  1. headroom : customizable_metric_headroom option;
    (*

    The headroom value in percentage used for the specified metric parameter.

    The following lists the valid values for CPU and memory utilization.

    • CPU utilization: PERCENT_30 | PERCENT_20 | PERCENT_0
    • Memory utilization: PERCENT_30 | PERCENT_20 | PERCENT_10
    *)
  2. threshold : customizable_metric_threshold option;
    (*

    The threshold value used for the specified metric parameter.

    You can only specify the threshold value for CPU utilization.

    *)
}

Defines the various metric parameters that can be customized, such as threshold and headroom.

type nonrec utilization_preference = {
  1. metric_parameters : customizable_metric_parameters option;
    (*

    The parameters to set when customizing the resource utilization thresholds.

    *)
  2. metric_name : customizable_metric_name option;
    (*

    The name of the resource utilization metric name to customize.

    *)
}

The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom.

This preference is only available for the Amazon EC2 instance resource type.

type nonrec utilization_preferences = utilization_preference list
type nonrec metric_name =
  1. | GPU_MEMORY_PERCENTAGE
  2. | GPU_PERCENTAGE
  3. | NETWORK_PACKETS_OUT_PER_SECOND
  4. | NETWORK_PACKETS_IN_PER_SECOND
  5. | NETWORK_OUT_BYTES_PER_SECOND
  6. | NETWORK_IN_BYTES_PER_SECOND
  7. | DISK_WRITE_BYTES_PER_SECOND
  8. | DISK_READ_BYTES_PER_SECOND
  9. | DISK_WRITE_OPS_PER_SECOND
  10. | DISK_READ_OPS_PER_SECOND
  11. | EBS_WRITE_BYTES_PER_SECOND
  12. | EBS_READ_BYTES_PER_SECOND
  13. | EBS_WRITE_OPS_PER_SECOND
  14. | EBS_READ_OPS_PER_SECOND
  15. | MEMORY
  16. | CPU
type nonrec utilization_metric = {
  1. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  2. statistic : metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  3. name : metric_name option;
    (*

    The name of the utilization metric.

    The following utilization metrics are available:

    • Cpu - The percentage of allocated EC2 compute units that are currently in use on the instance. This metric identifies the processing power required to run an application on the instance.

      Depending on the instance type, tools in your operating system can show a lower percentage than CloudWatch when the instance is not allocated a full processor core.

      Units: Percent

    • Memory - The percentage of memory that is currently in use on the instance. This metric identifies the amount of memory required to run an application on the instance.

      Units: Percent

      The Memory metric is returned only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent.

    • GPU - The percentage of allocated GPUs that currently run on the instance.

    • GPU_MEMORY - The percentage of total GPU memory that currently runs on the instance.

      The GPU and GPU_MEMORY metrics are only returned for resources with the unified CloudWatch Agent installed on them. For more information, see Enabling NVIDIA GPU utilization with the CloudWatch Agent.

    • EBS_READ_OPS_PER_SECOND - The completed read operations from all EBS volumes attached to the instance in a specified period of time.

      Unit: Count

    • EBS_WRITE_OPS_PER_SECOND - The completed write operations to all EBS volumes attached to the instance in a specified period of time.

      Unit: Count

    • EBS_READ_BYTES_PER_SECOND - The bytes read from all EBS volumes attached to the instance in a specified period of time.

      Unit: Bytes

    • EBS_WRITE_BYTES_PER_SECOND - The bytes written to all EBS volumes attached to the instance in a specified period of time.

      Unit: Bytes

    • DISK_READ_OPS_PER_SECOND - The completed read operations from all instance store volumes available to the instance in a specified period of time.

      If there are no instance store volumes, either the value is 0 or the metric is not reported.

    • DISK_WRITE_OPS_PER_SECOND - The completed write operations from all instance store volumes available to the instance in a specified period of time.

      If there are no instance store volumes, either the value is 0 or the metric is not reported.

    • DISK_READ_BYTES_PER_SECOND - The bytes read from all instance store volumes available to the instance. This metric is used to determine the volume of the data the application reads from the disk of the instance. This can be used to determine the speed of the application.

      If there are no instance store volumes, either the value is 0 or the metric is not reported.

    • DISK_WRITE_BYTES_PER_SECOND - The bytes written to all instance store volumes available to the instance. This metric is used to determine the volume of the data the application writes onto the disk of the instance. This can be used to determine the speed of the application.

      If there are no instance store volumes, either the value is 0 or the metric is not reported.

    • NETWORK_IN_BYTES_PER_SECOND - The number of bytes received by the instance on all network interfaces. This metric identifies the volume of incoming network traffic to a single instance.
    • NETWORK_OUT_BYTES_PER_SECOND - The number of bytes sent out by the instance on all network interfaces. This metric identifies the volume of outgoing network traffic from a single instance.
    • NETWORK_PACKETS_IN_PER_SECOND - The number of packets received by the instance on all network interfaces. This metric identifies the volume of incoming traffic in terms of the number of packets on a single instance.
    • NETWORK_PACKETS_OUT_PER_SECOND - The number of packets sent out by the instance on all network interfaces. This metric identifies the volume of outgoing traffic in terms of the number of packets on a single instance.
    *)
}

Describes a utilization metric of a resource, such as an Amazon EC2 instance.

Compare the utilization metric data of your resource against its projected utilization metric data to determine the performance difference between your current resource and the recommended option.

type nonrec utilization_metrics = utilization_metric list
type nonrec upper_bound_value = float
type nonrec status =
  1. | FAILED
  2. | PENDING
  3. | INACTIVE
  4. | ACTIVE
type nonrec status_reason = string
type nonrec update_enrollment_status_response = {
  1. status_reason : status_reason option;
    (*

    The reason for the enrollment status of the account. For example, an account might show a status of Pending because member accounts of an organization require more time to be enrolled in the service.

    *)
  2. status : status option;
    (*

    The enrollment status of the account.

    *)
}
type nonrec include_member_accounts = bool
type nonrec update_enrollment_status_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to enroll member accounts of the organization if the account is the management account of an organization.

    *)
  2. status : status;
    (*

    The new enrollment status of the account.

    The following status options are available:

    • Active - Opts in your account to the Compute Optimizer service. Compute Optimizer begins analyzing the configuration and utilization metrics of your Amazon Web Services resources after you opt in. For more information, see Metrics analyzed by Compute Optimizer in the Compute Optimizer User Guide.
    • Inactive - Opts out your account from the Compute Optimizer service. Your account's recommendations and related metrics data will be deleted from Compute Optimizer after you opt out.

    The Pending and Failed options cannot be used to update the enrollment status of an account. They are returned in the response of a request to update the enrollment status of an account.

    *)
}
type nonrec error_message = string
type nonrec throttling_exception = {
  1. message : error_message;
}

The request was denied due to request throttling.

type nonrec service_unavailable_exception = {
  1. message : error_message option;
}

The request has failed due to a temporary failure of the server.

type nonrec missing_authentication_token = {
  1. message : error_message option;
}

The request must contain either a valid (registered) Amazon Web Services access key ID or X.509 certificate.

type nonrec invalid_parameter_value_exception = {
  1. message : error_message option;
}

The value supplied for the input parameter is out of range or not valid.

type nonrec internal_server_exception = {
  1. message : error_message option;
}

An internal error has occurred. Try your call again.

type nonrec access_denied_exception = {
  1. message : error_message option;
}

You do not have sufficient access to perform this action.

type nonrec timestamp = Smaws_Lib.CoreTypes.Timestamp.t
type nonrec timestamps = timestamp list
type nonrec task_definition_arn = string
type nonrec summary_value = float
type nonrec finding =
  1. | NOT_OPTIMIZED
  2. | OPTIMIZED
  3. | OVER_PROVISIONED
  4. | UNDER_PROVISIONED
type nonrec finding_reason_code =
  1. | MEMORY_UNDER_PROVISIONED
  2. | MEMORY_OVER_PROVISIONED
type nonrec reason_code_summary = {
  1. value : summary_value option;
    (*

    The value of the finding reason code summary.

    *)
  2. name : finding_reason_code option;
    (*

    The name of the finding reason code.

    *)
}

A summary of a finding reason code.

type nonrec reason_code_summaries = reason_code_summary list
type nonrec summary = {
  1. reason_code_summaries : reason_code_summaries option;
    (*

    An array of objects that summarize a finding reason code.

    *)
  2. value : summary_value option;
    (*

    The value of the recommendation summary.

    *)
  3. name : finding option;
    (*

    The finding classification of the recommendation.

    *)
}

The summary of a recommendation.

type nonrec summaries = summary list
type nonrec storage_type = string
type nonrec nullable_memory = int
type nonrec nullable_cpu = int
type nonrec container_name = string
type nonrec nullable_memory_reservation = int
type nonrec memory_size_configuration = {
  1. memory_reservation : nullable_memory_reservation option;
    (*

    The limit of memory reserve for the container.

    *)
  2. memory : nullable_memory option;
    (*

    The amount of memory in the container.

    *)
}

The memory size configurations of a container.

type nonrec container_configuration = {
  1. cpu : nullable_cpu option;
    (*

    The number of CPU units reserved for the container.

    *)
  2. memory_size_configuration : memory_size_configuration option;
    (*

    The memory size configurations for the container.

    *)
  3. container_name : container_name option;
    (*

    The name of the container.

    *)
}

Describes the container configurations within the tasks of your Amazon ECS service.

type nonrec container_configurations = container_configuration list
type nonrec auto_scaling_configuration =
  1. | TARGET_TRACKING_SCALING_MEMORY
  2. | TARGET_TRACKING_SCALING_CPU
type nonrec service_configuration = {
  1. task_definition_arn : task_definition_arn option;
    (*

    The task definition ARN used by the tasks in the Amazon ECS service.

    *)
  2. auto_scaling_configuration : auto_scaling_configuration option;
    (*

    Describes the Auto Scaling configuration methods for an Amazon ECS service. This affects the generated recommendations. For example, if Auto Scaling is configured on a service’s CPU, then Compute Optimizer doesn’t generate CPU size recommendations.

    The Auto Scaling configuration methods include:

    • TARGET_TRACKING_SCALING_CPU — If the Amazon ECS service is configured to use target scaling on CPU, Compute Optimizer doesn't generate CPU recommendations.
    • TARGET_TRACKING_SCALING_MEMORY — If the Amazon ECS service is configured to use target scaling on memory, Compute Optimizer doesn't generate memory recommendations.

    For more information about step scaling and target scaling, see Step scaling policies for Application Auto Scaling and Target tracking scaling policies for Application Auto Scaling in the Application Auto Scaling User Guide.

    *)
  3. container_configurations : container_configurations option;
    (*

    The container configurations within a task of an Amazon ECS service.

    *)
  4. cpu : nullable_cpu option;
    (*

    The number of CPU units used by the tasks in the Amazon ECS service.

    *)
  5. memory : nullable_memory option;
    (*

    The amount of memory used by the tasks in the Amazon ECS service.

    *)
}

The Amazon ECS service configurations used for recommendations.

type nonrec service_arn = string
type nonrec service_arns = service_arn list
type nonrec scope_value = string
type nonrec scope_name =
  1. | RESOURCE_ARN
  2. | ACCOUNT_ID
  3. | ORGANIZATION
type nonrec scope = {
  1. value : scope_value option;
    (*

    The value of the scope.

    If you specified the name of the scope as:

    • Organization - The value must be ALL_ACCOUNTS.
    • AccountId - The value must be a 12-digit Amazon Web Services account ID.
    • ResourceArn - The value must be the Amazon Resource Name (ARN) of an EC2 instance or an Auto Scaling group.

    Only EC2 instance and Auto Scaling group ARNs are currently supported.

    *)
  2. name : scope_name option;
    (*

    The name of the scope.

    The following scopes are possible:

    • Organization - Specifies that the recommendation preference applies at the organization level, for all member accounts of an organization.
    • AccountId - Specifies that the recommendation preference applies at the account level, for all resources of a given resource type in an account.
    • ResourceArn - Specifies that the recommendation preference applies at the individual resource level.
    *)
}

Describes the scope of a recommendation preference.

Recommendation preferences can be created at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see Activating enhanced infrastructure metrics in the Compute Optimizer User Guide.

You cannot create recommendation preferences for Auto Scaling groups at the organization and account levels. You can create recommendation preferences for Auto Scaling groups only at the resource level by specifying a scope name of ResourceArn and a scope value of the Auto Scaling group Amazon Resource Name (ARN). This will configure the preference for all instances that are part of the specified Auto Scaling group. You also cannot create recommendation preferences at the resource level for instances that are part of an Auto Scaling group. You can create recommendation preferences at the resource level only for standalone instances.

type nonrec savings_estimation_mode =
  1. | BEFORE_DISCOUNTS
  2. | AFTER_DISCOUNTS
type nonrec destination_bucket = string
type nonrec destination_key_prefix = string
type nonrec s3_destination_config = {
  1. key_prefix : destination_key_prefix option;
    (*

    The Amazon S3 bucket prefix for an export job.

    *)
  2. bucket : destination_bucket option;
    (*

    The name of the Amazon S3 bucket to use as the destination for an export job.

    *)
}

Describes the destination Amazon Simple Storage Service (Amazon S3) bucket name and key prefix for a recommendations export job.

You must create the destination Amazon S3 bucket for your recommendations export before you create the export job. Compute Optimizer does not create the S3 bucket for you. After you create the S3 bucket, ensure that it has the required permission policy to allow Compute Optimizer to write the export file to it. If you plan to specify an object prefix when you create the export job, you must include the object prefix in the policy that you add to the S3 bucket. For more information, see Amazon S3 Bucket Policy for Compute Optimizer in the Compute Optimizer User Guide.

type nonrec destination_key = string
type nonrec metadata_key = string
type nonrec s3_destination = {
  1. metadata_key : metadata_key option;
    (*

    The Amazon S3 bucket key of a metadata file.

    The key uniquely identifies the object, or metadata file, in the S3 bucket.

    *)
  2. key : destination_key option;
    (*

    The Amazon S3 bucket key of an export file.

    The key uniquely identifies the object, or export file, in the S3 bucket.

    *)
  3. bucket : destination_bucket option;
    (*

    The name of the Amazon S3 bucket used as the destination of an export file.

    *)
}

Describes the destination Amazon Simple Storage Service (Amazon S3) bucket name and object keys of a recommendations export file, and its associated metadata file.

type nonrec resource_type =
  1. | IDLE
  2. | AURORA_DB_CLUSTER_STORAGE
  3. | RDS_DB_INSTANCE
  4. | LICENSE
  5. | ECS_SERVICE
  6. | NOT_APPLICABLE
  7. | LAMBDA_FUNCTION
  8. | EBS_VOLUME
  9. | AUTO_SCALING_GROUP
  10. | EC2_INSTANCE
type nonrec resource_not_found_exception = {
  1. message : error_message option;
}

A resource that is required for the action doesn't exist.

type nonrec resource_id = string
type nonrec resource_arn = string
type nonrec resource_arns = resource_arn list
type nonrec metric_values = metric_value list
type nonrec projected_metric = {
  1. values : metric_values option;
    (*

    The values of the projected utilization metrics.

    *)
  2. timestamps : timestamps option;
    (*

    The timestamps of the projected utilization metric.

    *)
  3. name : metric_name option;
    (*

    The name of the projected utilization metric.

    The following projected utilization metrics are returned:

    • Cpu - The projected percentage of allocated EC2 compute units that would be in use on the recommendation option had you used that resource during the analyzed period. This metric identifies the processing power required to run an application on the recommendation option.

      Depending on the instance type, tools in your operating system can show a lower percentage than CloudWatch when the instance is not allocated a full processor core.

    • Memory - The percentage of memory that would be in use on the recommendation option had you used that resource during the analyzed period. This metric identifies the amount of memory required to run an application on the recommendation option.

      Units: Percent

      The Memory metric is only returned for resources with the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent.

    • GPU - The projected percentage of allocated GPUs if you adjust your configurations to Compute Optimizer's recommendation option.

    • GPU_MEMORY - The projected percentage of total GPU memory if you adjust your configurations to Compute Optimizer's recommendation option.

      The GPU and GPU_MEMORY metrics are only returned for resources with the unified CloudWatch Agent installed on them. For more information, see Enabling NVIDIA GPU utilization with the CloudWatch Agent.

    *)
}

Describes a projected utilization metric of a recommendation option, such as an Amazon EC2 instance. This represents the projected utilization of a recommendation option had you used that resource during the analyzed period.

Compare the utilization metric data of your resource against its projected utilization metric data to determine the performance difference between your current resource and the recommended option.

The Cpu, Memory, GPU, and GPU_MEMORY metrics are the only projected utilization metrics returned when you run the GetEC2RecommendationProjectedMetrics action. Additionally, these metrics are only returned for resources with the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent and Enabling NVIDIA GPU utilization with the CloudWatch Agent.

type nonrec projected_metrics = projected_metric list

Describes a projected utilization metric of a recommendation option.

The Cpu and Memory metrics are the only projected utilization metrics returned when you run the GetEC2RecommendationProjectedMetrics action. Additionally, the Memory metric is returned only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent.

type nonrec idle_finding =
  1. | UNUSED
  2. | UNATTACHED
  3. | IDLE
type nonrec idle_summary = {
  1. value : summary_value option;
    (*

    The count of idle resources in the finding group.

    *)
  2. name : idle_finding option;
    (*

    The name of the finding group for the idle resources.

    *)
}

Describes the findings summary of the idle resources.

type nonrec idle_summaries = idle_summary list
type nonrec recommendation_source_type =
  1. | SAGE_MAKER_ENDPOINT
  2. | WORKSPACES
  3. | DOCUMENT_DB_CLUSTER
  4. | MEMORY_DB_CLUSTER
  5. | ELASTI_CACHE_CLUSTER
  6. | DYNAMO_DB_TABLE
  7. | NAT_GATEWAY
  8. | AURORA_DB_CLUSTER_STORAGE
  9. | RDS_DB_INSTANCE_STORAGE
  10. | RDS_DB_INSTANCE
  11. | LICENSE
  12. | ECS_SERVICE
  13. | LAMBDA_FUNCTION
  14. | EBS_VOLUME
  15. | AUTO_SCALING_GROUP
  16. | EC2_INSTANCE
type nonrec high = Smaws_Lib.CoreTypes.Int64.t
type nonrec medium = Smaws_Lib.CoreTypes.Int64.t
type nonrec low = Smaws_Lib.CoreTypes.Int64.t
type nonrec current_performance_risk_ratings = {
  1. very_low : very_low option;
    (*

    A count of the applicable resource types with a very low performance risk rating.

    *)
  2. low : low option;
    (*

    A count of the applicable resource types with a low performance risk rating.

    *)
  3. medium : medium option;
    (*

    A count of the applicable resource types with a medium performance risk rating.

    *)
  4. high : high option;
    (*

    A count of the applicable resource types with a high performance risk rating.

    *)
}

Describes the performance risk ratings for a given resource type.

Resources with a high or medium rating are at risk of not meeting the performance needs of their workloads, while resources with a low rating are performing well in their workloads.

type nonrec inferred_workload_type =
  1. | SQLSERVER
  2. | KAFKA
  3. | REDIS
  4. | POSTGRE_SQL
  5. | NGINX
  6. | MEMCACHED
  7. | APACHE_HADOOP
  8. | APACHE_CASSANDRA
  9. | AMAZON_EMR
type nonrec inferred_workload_types = inferred_workload_type list
type nonrec inferred_workload_saving = {
  1. estimated_monthly_savings : estimated_monthly_savings option;
    (*

    An object that describes the estimated monthly savings amount possible by adopting Compute Optimizer recommendations for a given resource. This is based on the On-Demand instance pricing.

    *)
  2. inferred_workload_types : inferred_workload_types option;
    (*

    The applications that might be running on the instance as inferred by Compute Optimizer.

    Compute Optimizer can infer if one of the following applications might be running on the instance:

    • AmazonEmr - Infers that Amazon EMR might be running on the instance.
    • ApacheCassandra - Infers that Apache Cassandra might be running on the instance.
    • ApacheHadoop - Infers that Apache Hadoop might be running on the instance.
    • Memcached - Infers that Memcached might be running on the instance.
    • NGINX - Infers that NGINX might be running on the instance.
    • PostgreSql - Infers that PostgreSQL might be running on the instance.
    • Redis - Infers that Redis might be running on the instance.
    • Kafka - Infers that Kafka might be running on the instance.
    • SQLServer - Infers that SQLServer might be running on the instance.
    *)
}

The estimated monthly savings after you adjust the configurations of your instances running on the inferred workload types to the recommended configurations. If the inferredWorkloadTypes list contains multiple entries, then the savings are the sum of the monthly savings from instances that run the exact combination of the inferred workload types.

type nonrec inferred_workload_savings = inferred_workload_saving list
type nonrec recommendation_summary = {
  1. inferred_workload_savings : inferred_workload_savings option;
    (*

    An array of objects that describes the estimated monthly saving amounts for the instances running on the specified inferredWorkloadTypes. The array contains the top five savings opportunites for the instances that run inferred workload types.

    *)
  2. current_performance_risk_ratings : current_performance_risk_ratings option;
    (*

    An object that describes the performance risk ratings for a given resource type.

    *)
  3. aggregated_savings_opportunity : savings_opportunity option;
  4. idle_savings_opportunity : savings_opportunity option;
  5. savings_opportunity : savings_opportunity option;
    (*

    An object that describes the savings opportunity for a given resource type. Savings opportunity includes the estimated monthly savings amount and percentage.

    *)
  6. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the recommendation summary.

    *)
  7. recommendation_resource_type : recommendation_source_type option;
    (*

    The resource type that the recommendation summary applies to.

    *)
  8. idle_summaries : idle_summaries option;
    (*

    Describes the findings summary of the idle resources.

    *)
  9. summaries : summaries option;
    (*

    An array of objects that describe a recommendation summary.

    *)
}

A summary of a recommendation.

type nonrec recommendation_summaries = recommendation_summary list
type nonrec recommendation_source_arn = string
type nonrec recommendation_source = {
  1. recommendation_source_type : recommendation_source_type option;
    (*

    The resource type of the recommendation source.

    *)
  2. recommendation_source_arn : recommendation_source_arn option;
    (*

    The Amazon Resource Name (ARN) of the recommendation source.

    *)
}

Describes the source of a recommendation, such as an Amazon EC2 instance or Auto Scaling group.

type nonrec recommendation_sources = recommendation_source list
type nonrec enhanced_infrastructure_metrics =
  1. | INACTIVE
  2. | ACTIVE
type nonrec inferred_workload_types_preference =
  1. | INACTIVE
  2. | ACTIVE
type nonrec external_metrics_source =
  1. | INSTANA
  2. | NEWRELIC
  3. | DYNATRACE
  4. | DATADOG
type nonrec external_metrics_preference = {
  1. source : external_metrics_source option;
    (*

    Contains the source options for external metrics preferences.

    *)
}

Describes the external metrics preferences for EC2 rightsizing recommendations.

type nonrec preferred_resource_name =
  1. | EC2_INSTANCE_TYPES
type nonrec preferred_resource_value = string
type nonrec preferred_resource_values = preferred_resource_value list
type nonrec effective_preferred_resource = {
  1. exclude_list : preferred_resource_values option;
    (*

    The list of preferred resources values that you want excluded from rightsizing recommendation candidates.

    *)
  2. effective_include_list : preferred_resource_values option;
    (*

    The expanded version of your preferred resource's include list.

    *)
  3. include_list : preferred_resource_values option;
    (*

    The list of preferred resource values that you want considered as rightsizing recommendation candidates.

    *)
  4. name : preferred_resource_name option;
    (*

    The name of the preferred resource list.

    *)
}

Describes the effective preferred resources that Compute Optimizer considers as rightsizing recommendation candidates.

Compute Optimizer only supports Amazon EC2 instance types.

type nonrec effective_preferred_resources = effective_preferred_resource list
type nonrec recommendation_preferences_detail = {
  1. savings_estimation_mode : savings_estimation_mode option;
    (*

    Describes the savings estimation mode used for calculating savings opportunity.

    Only the account manager or delegated administrator of your organization can activate this preference.

    *)
  2. preferred_resources : effective_preferred_resources option;
    (*

    The preference to control which resource type values are considered when generating rightsizing recommendations. This object resolves any wildcard expressions and returns the effective list of candidate resource type values. If the preference isn’t set, this object is null.

    *)
  3. utilization_preferences : utilization_preferences option;
    (*

    The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom. If the preference isn’t set, this object is null.

    This preference is only available for the Amazon EC2 instance resource type.

    *)
  4. look_back_period : look_back_period_preference option;
    (*

    The preference to control the number of days the utilization metrics of the Amazon Web Services resource are analyzed. If the preference isn’t set, this object is null.

    *)
  5. external_metrics_preference : external_metrics_preference option;
    (*

    An object that describes the external metrics recommendation preference.

    If the preference is applied in the latest recommendation refresh, an object with a valid source value appears in the response. If the preference isn't applied to the recommendations already, then this object doesn't appear in the response.

    *)
  6. inferred_workload_types : inferred_workload_types_preference option;
    (*

    The status of the inferred workload types recommendation preference.

    When the recommendations page is refreshed, a status of Active confirms that the preference is applied to the recommendations, and a status of Inactive confirms that the preference isn't yet applied to recommendations.

    *)
  7. enhanced_infrastructure_metrics : enhanced_infrastructure_metrics option;
    (*

    The status of the enhanced infrastructure metrics recommendation preference.

    When the recommendations page is refreshed, a status of Active confirms that the preference is applied to the recommendations, and a status of Inactive confirms that the preference isn't yet applied to recommendations.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  8. resource_type : resource_type option;
    (*

    The target resource type of the recommendation preference to create.

    The Ec2Instance option encompasses standalone instances and instances that are part of Auto Scaling groups. The AutoScalingGroup option encompasses only instances that are part of an Auto Scaling group.

    *)
  9. scope : scope option;
    (*

    An object that describes the scope of the recommendation preference.

    Recommendation preferences can be created at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see Activating enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
}

Describes a recommendation preference.

type nonrec recommendation_preferences_details = recommendation_preferences_detail list
type nonrec cpu_vendor_architecture =
  1. | CURRENT
  2. | AWS_ARM64
type nonrec cpu_vendor_architectures = cpu_vendor_architecture list
type nonrec recommendation_preferences = {
  1. cpu_vendor_architectures : cpu_vendor_architectures option;
    (*

    Specifies the CPU vendor and architecture for Amazon EC2 instance and Auto Scaling group recommendations.

    For example, when you specify AWS_ARM64 with:

    • A GetEC2InstanceRecommendations or GetAutoScalingGroupRecommendations request, Compute Optimizer returns recommendations that consist of Graviton instance types only.
    • A GetEC2RecommendationProjectedMetrics request, Compute Optimizer returns projected utilization metrics for Graviton instance type recommendations only.
    • A ExportEC2InstanceRecommendations or ExportAutoScalingGroupRecommendations request, Compute Optimizer exports recommendations that consist of Graviton instance types only.
    *)
}

Describes the recommendation preferences to return in the response of a GetAutoScalingGroupRecommendations, GetEC2InstanceRecommendations, GetEC2RecommendationProjectedMetrics, GetRDSDatabaseRecommendations, and GetRDSDatabaseRecommendationProjectedMetrics request.

type nonrec recommendation_preference_name =
  1. | UTILIZATION_PREFERENCES
  2. | PREFERRED_RESOURCES
  3. | LOOKBACK_PERIOD_PREFERENCE
  4. | EXTERNAL_METRICS_PREFERENCE
  5. | INFERRED_WORKLOAD_TYPES
  6. | ENHANCED_INFRASTRUCTURE_METRICS
type nonrec recommendation_preference_names = recommendation_preference_name list
type nonrec instance_type = string
type nonrec gpu_count = int
type nonrec gpu_memory_size_in_mi_b = int
type nonrec gpu = {
  1. gpu_memory_size_in_mi_b : gpu_memory_size_in_mi_b option;
    (*

    The total size of the memory for the GPU accelerators for the instance type, in MiB.

    *)
  2. gpu_count : gpu_count option;
    (*

    The number of GPUs for the instance type.

    *)
}

Describes the GPU accelerators for the instance type.

type nonrec gpus = gpu list
type nonrec gpu_info = {
  1. gpus : gpus option;
    (*

    Describes the GPU accelerators for the instance type.

    *)
}

Describes the GPU accelerator settings for the instance type.

type nonrec projected_utilization_metrics = utilization_metric list
type nonrec platform_difference =
  1. | ARCHITECTURE
  2. | VIRTUALIZATION_TYPE
  3. | INSTANCE_STORE_AVAILABILITY
  4. | STORAGE_INTERFACE
  5. | NETWORK_INTERFACE
  6. | HYPERVISOR
type nonrec platform_differences = platform_difference list
type nonrec instance_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

An object that describes the estimated monthly savings possible by adopting Compute Optimizer’s Amazon EC2 instance recommendations. This is based on the Savings Plans and Reserved Instances pricing discounts.

type nonrec instance_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : instance_estimated_monthly_savings option;
    (*

    An object that describes the estimated monthly savings possible by adopting Compute Optimizer’s Amazon EC2 instance recommendations. This is based on pricing after applying the Savings Plans and Reserved Instances discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost after applying the Savings Plans and Reserved Instances discounts. This saving can be achieved by adopting Compute Optimizer’s EC2 instance recommendations.

    *)
}

Describes the savings opportunity for instance recommendations after applying the Savings Plans and Reserved Instances discounts.

Savings opportunity after discounts represents the estimated monthly savings you can achieve by implementing Compute Optimizer recommendations.

type nonrec migration_effort =
  1. | HIGH
  2. | MEDIUM
  3. | LOW
  4. | VERY_LOW
type nonrec instance_recommendation_option = {
  1. migration_effort : migration_effort option;
    (*

    The level of effort required to migrate from the current instance type to the recommended instance type.

    For example, the migration effort is Low if Amazon EMR is the inferred workload type and an Amazon Web Services Graviton instance type is recommended. The migration effort is Medium if a workload type couldn't be inferred but an Amazon Web Services Graviton instance type is recommended. The migration effort is VeryLow if both the current and recommended instance types are of the same CPU architecture.

    *)
  2. savings_opportunity_after_discounts : instance_savings_opportunity_after_discounts option;
    (*

    An object that describes the savings opportunity for the instance recommendation option that includes Savings Plans and Reserved Instances discounts. Savings opportunity includes the estimated monthly savings and percentage.

    *)
  3. savings_opportunity : savings_opportunity option;
    (*

    An object that describes the savings opportunity for the instance recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage.

    *)
  4. rank : rank option;
    (*

    The rank of the instance recommendation option.

    The top recommendation option is ranked as 1.

    *)
  5. performance_risk : performance_risk option;
    (*

    The performance risk of the instance recommendation option.

    Performance risk indicates the likelihood of the recommended instance type not meeting the resource needs of your workload. Compute Optimizer calculates an individual performance risk score for each specification of the recommended instance, including CPU, memory, EBS throughput, EBS IOPS, disk throughput, disk IOPS, network throughput, and network PPS. The performance risk of the recommended instance is calculated as the maximum performance risk score across the analyzed resource specifications.

    The value ranges from 0 - 4, with 0 meaning that the recommended resource is predicted to always provide enough hardware capability. The higher the performance risk is, the more likely you should validate whether the recommendation will meet the performance requirements of your workload before migrating your resource.

    *)
  6. platform_differences : platform_differences option;
    (*

    Describes the configuration differences between the current instance and the recommended instance type. You should consider the configuration differences before migrating your workloads from the current instance to the recommended instance type. The Change the instance type guide for Linux and Change the instance type guide for Windows provide general guidance for getting started with an instance migration.

    Platform differences include:

    • Hypervisor — The hypervisor of the recommended instance type is different than that of the current instance. For example, the recommended instance type uses a Nitro hypervisor and the current instance uses a Xen hypervisor. The differences that you should consider between these hypervisors are covered in the Nitro Hypervisor section of the Amazon EC2 frequently asked questions. For more information, see Instances built on the Nitro System in the Amazon EC2 User Guide for Linux, or Instances built on the Nitro System in the Amazon EC2 User Guide for Windows.
    • NetworkInterface — The network interface of the recommended instance type is different than that of the current instance. For example, the recommended instance type supports enhanced networking and the current instance might not. To enable enhanced networking for the recommended instance type, you must install the Elastic Network Adapter (ENA) driver or the Intel 82599 Virtual Function driver. For more information, see Networking and storage features and Enhanced networking on Linux in the Amazon EC2 User Guide for Linux, or Networking and storage features and Enhanced networking on Windows in the Amazon EC2 User Guide for Windows.
    • StorageInterface — The storage interface of the recommended instance type is different than that of the current instance. For example, the recommended instance type uses an NVMe storage interface and the current instance does not. To access NVMe volumes for the recommended instance type, you will need to install or upgrade the NVMe driver. For more information, see Networking and storage features and Amazon EBS and NVMe on Linux instances in the Amazon EC2 User Guide for Linux, or Networking and storage features and Amazon EBS and NVMe on Windows instances in the Amazon EC2 User Guide for Windows.
    • InstanceStoreAvailability — The recommended instance type does not support instance store volumes and the current instance does. Before migrating, you might need to back up the data on your instance store volumes if you want to preserve them. For more information, see How do I back up an instance store volume on my Amazon EC2 instance to Amazon EBS? in the Amazon Web Services Premium Support Knowledge Base. For more information, see Networking and storage features and Amazon EC2 instance store in the Amazon EC2 User Guide for Linux, or see Networking and storage features and Amazon EC2 instance store in the Amazon EC2 User Guide for Windows.
    • VirtualizationType — The recommended instance type uses the hardware virtual machine (HVM) virtualization type and the current instance uses the paravirtual (PV) virtualization type. For more information about the differences between these virtualization types, see Linux AMI virtualization types in the Amazon EC2 User Guide for Linux, or Windows AMI virtualization types in the Amazon EC2 User Guide for Windows.
    • Architecture — The CPU architecture between the recommended instance type and the current instance is different. For example, the recommended instance type might use an Arm CPU architecture and the current instance type might use a different one, such as x86. Before migrating, you should consider recompiling the software on your instance for the new architecture. Alternatively, you might switch to an Amazon Machine Image (AMI) that supports the new architecture. For more information about the CPU architecture for each instance type, see Amazon EC2 Instance Types.
    *)
  7. projected_utilization_metrics : projected_utilization_metrics option;
    (*

    An array of objects that describe the projected utilization metrics of the instance recommendation option.

    The Cpu and Memory metrics are the only projected utilization metrics returned. Additionally, the Memory metric is returned only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent.

    *)
  8. instance_gpu_info : gpu_info option;
    (*

    Describes the GPU accelerator settings for the recommended instance type.

    *)
  9. instance_type : instance_type option;
    (*

    The instance type of the instance recommendation.

    *)
}

Describes a recommendation option for an Amazon EC2 instance.

type nonrec recommendation_options = instance_recommendation_option list
type nonrec job_id = string
type nonrec export_destination = {
  1. s3 : s3_destination option;
    (*

    An object that describes the destination Amazon Simple Storage Service (Amazon S3) bucket name and object keys of a recommendations export file, and its associated metadata file.

    *)
}

Describes the destination of the recommendations export and metadata files.

type nonrec job_status =
  1. | FAILED
  2. | COMPLETE
  3. | IN_PROGRESS
  4. | QUEUED
type nonrec creation_timestamp = Smaws_Lib.CoreTypes.Timestamp.t
type nonrec last_updated_timestamp = Smaws_Lib.CoreTypes.Timestamp.t
type nonrec failure_reason = string
type nonrec recommendation_export_job = {
  1. failure_reason : failure_reason option;
    (*

    The reason for an export job failure.

    *)
  2. last_updated_timestamp : last_updated_timestamp option;
    (*

    The timestamp of when the export job was last updated.

    *)
  3. creation_timestamp : creation_timestamp option;
    (*

    The timestamp of when the export job was created.

    *)
  4. status : job_status option;
    (*

    The status of the export job.

    *)
  5. resource_type : resource_type option;
    (*

    The resource type of the exported recommendations.

    *)
  6. destination : export_destination option;
    (*

    An object that describes the destination of the export file.

    *)
  7. job_id : job_id option;
    (*

    The identification number of the export job.

    *)
}

Describes a recommendation export job.

Use the DescribeRecommendationExportJobs action to view your recommendation export jobs.

Use the ExportAutoScalingGroupRecommendations or ExportEC2InstanceRecommendations actions to request an export of your recommendations.

type nonrec recommendation_export_jobs = recommendation_export_job list
type nonrec rds_storage_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings for DB instance storage.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings possible for DB instance storage by adopting Compute Optimizer recommendations. This is based on DB instance pricing after applying Savings Plans discounts.

type nonrec rds_storage_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : rds_storage_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer’s DB instance storage recommendations. This includes any applicable Savings Plans discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer’s DB instance storage recommendations. This includes any applicable Savings Plans discounts.

    *)
}

Describes the savings opportunity for Amazon RDS storage recommendations after applying Savings Plans discounts.

Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

type nonrec rds_storage_finding_reason_code =
  1. | DB_CLUSTER_STORAGE_SAVINGS_AVAILABLE
  2. | DB_CLUSTER_STORAGE_OPTION_AVAILABLE
  3. | NEW_GENERATION_STORAGE_TYPE_AVAILABLE
  4. | EBS_VOLUME_THROUGHPUT_OVER_PROVISIONED
  5. | EBS_VOLUME_IOPS_OVER_PROVISIONED
  6. | EBS_VOLUME_THROUGHPUT_UNDER_PROVISIONED
  7. | EBS_VOLUME_ALLOCATED_STORAGE_UNDER_PROVISIONED
type nonrec rds_storage_finding_reason_codes = rds_storage_finding_reason_code list
type nonrec rds_storage_finding =
  1. | NOT_OPTIMIZED
  2. | OVER_PROVISIONED
  3. | UNDER_PROVISIONED
  4. | OPTIMIZED
type nonrec rds_savings_estimation_mode_source =
  1. | COST_OPTIMIZATION_HUB
  2. | COST_EXPLORER_RIGHTSIZING
  3. | PUBLIC_PRICING
type nonrec rds_savings_estimation_mode = {
  1. source : rds_savings_estimation_mode_source option;
    (*

    Describes the source for calculating the savings opportunity for DB instances.

    *)
}

Describes the savings estimation mode used for calculating savings opportunity for DB instances.

type nonrec rds_instance_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings for DB instances.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings possible for DB instances by adopting Compute Optimizer recommendations. This is based on DB instance pricing after applying Savings Plans discounts.

type nonrec rds_instance_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : rds_instance_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer’s DB instance recommendations. This includes any applicable Savings Plans discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer’s DB instance recommendations. This includes any applicable Savings Plans discounts.

    *)
}

Describes the savings opportunity for DB instance recommendations after applying Savings Plans discounts.

Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

type nonrec rds_instance_finding_reason_code =
  1. | INSTANCE_STORAGE_WRITE_IOPS_UNDER_PROVISIONED
  2. | INSTANCE_STORAGE_READ_IOPS_UNDER_PROVISIONED
  3. | MEMORY_UNDER_PROVISIONED
  4. | DB_CLUSTER_WRITER_UNDER_PROVISIONED
  5. | NEW_ENGINE_VERSION_AVAILABLE
  6. | NEW_GENERATION_DB_INSTANCE_CLASS_AVAILABLE
  7. | EBS_THROUGHPUT_UNDER_PROVISIONED
  8. | NETWORK_BANDWIDTH_UNDER_PROVISIONED
  9. | CPU_UNDER_PROVISIONED
  10. | EBS_THROUGHPUT_OVER_PROVISIONED
  11. | EBS_IOPS_UNDER_PROVISIONED
  12. | EBS_IOPS_OVER_PROVISIONED
  13. | NETWORK_BANDWIDTH_OVER_PROVISIONED
  14. | CPU_OVER_PROVISIONED
type nonrec rds_instance_finding_reason_codes = rds_instance_finding_reason_code list
type nonrec rds_instance_finding =
  1. | OVER_PROVISIONED
  2. | UNDER_PROVISIONED
  3. | OPTIMIZED
type nonrec rds_estimated_monthly_volume_io_ps_cost_variation =
  1. | HIGH
  2. | MEDIUM
  3. | LOW
  4. | NONE
type nonrec rds_effective_recommendation_preferences = {
  1. savings_estimation_mode : rds_savings_estimation_mode option;
    (*

    Describes the savings estimation mode preference applied for calculating savings opportunity for DB instances.

    *)
  2. look_back_period : look_back_period_preference option;
    (*

    The number of days the utilization metrics of the DB instance are analyzed.

    *)
  3. enhanced_infrastructure_metrics : enhanced_infrastructure_metrics option;
    (*

    Describes the activation status of the enhanced infrastructure metrics preference.

    A status of Active confirms that the preference is applied in the latest recommendation refresh, and a status of Inactive confirms that it's not yet applied to recommendations.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  4. cpu_vendor_architectures : cpu_vendor_architectures option;
    (*

    Describes the CPU vendor and architecture for DB instance recommendations.

    *)
}

Describes the effective recommendation preferences for Amazon Aurora and RDS databases.

type nonrec rdsdb_metric_name =
  1. | VOLUME_WRITE_IOPS
  2. | VOLUME_BYTES_USED
  3. | VOLUME_READ_IOPS
  4. | WRITE_IOPS_EPHEMERAL_STORAGE
  5. | READ_IOPS_EPHEMERAL_STORAGE
  6. | AURORA_MEMORY_NUM_KILL_QUERY_TOTAL
  7. | AURORA_MEMORY_NUM_KILL_CONN_TOTAL
  8. | AURORA_MEMORY_NUM_DECLINED_SQL
  9. | AURORA_MEMORY_HEALTH_STATE
  10. | STORAGE_NETWORK_TRANSMIT_THROUGHPUT
  11. | STORAGE_NETWORK_RECEIVE_THROUGHPUT
  12. | DATABASE_CONNECTIONS
  13. | EBS_VOLUME_WRITE_THROUGHPUT
  14. | EBS_VOLUME_READ_THROUGHPUT
  15. | EBS_VOLUME_WRITE_IOPS
  16. | EBS_VOLUME_READ_IOPS
  17. | NETWORK_TRANSMIT_THROUGHPUT
  18. | NETWORK_RECEIVE_THROUGHPUT
  19. | EBS_VOLUME_STORAGE_SPACE_UTILIZATION
  20. | MEMORY
  21. | CPU
type nonrec rds_database_projected_metric = {
  1. values : metric_values option;
    (*

    The values for the projected metric.

    *)
  2. timestamps : timestamps option;
    (*

    The timestamps of the projected metric.

    *)
  3. name : rdsdb_metric_name option;
    (*

    The name of the projected metric.

    *)
}

Describes the projected metrics of an Amazon Aurora and RDS database recommendation option.

To determine the performance difference between your current Amazon Aurora and RDS database and the recommended option, compare the metric data of your service against its projected metric data.

type nonrec rds_database_projected_metrics = rds_database_projected_metric list

Describes the projected metrics of an Amazon Aurora and RDS database recommendation option.

To determine the performance difference between your current Amazon Aurora and RDS database and the recommended option, compare the metric data of your service against its projected metric data.

type nonrec rdsdb_metric_statistic =
  1. | AVERAGE
  2. | MINIMUM
  3. | MAXIMUM
type nonrec rdsdb_utilization_metric = {
  1. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  2. statistic : rdsdb_metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  3. name : rdsdb_metric_name option;
    (*

    The name of the utilization metric.

    *)
}

Describes the utilization metric of an Amazon Aurora and RDS database.

To determine the performance difference between your current DB instance and the recommended option, compare the utilization metric data of your service against its projected utilization metric data.

type nonrec rdsdb_utilization_metrics = rdsdb_utilization_metric list
type nonrec allocated_storage = int
type nonrec nullable_iop_s = int
type nonrec nullable_max_allocated_storage = int
type nonrec nullable_storage_throughput = int
type nonrec db_storage_configuration = {
  1. storage_throughput : nullable_storage_throughput option;
    (*

    The storage throughput of the DB storage.

    *)
  2. max_allocated_storage : nullable_max_allocated_storage option;
    (*

    The maximum limit in gibibytes (GiB) to which Amazon RDS can automatically scale the storage of the DB instance.

    *)
  3. iops : nullable_iop_s option;
    (*

    The provisioned IOPs of the DB storage.

    *)
  4. allocated_storage : allocated_storage option;
    (*

    The size of the DB storage in gigabytes (GB).

    *)
  5. storage_type : storage_type option;
    (*

    The type of DB storage.

    *)
}

The configuration of the recommended RDS storage.

type nonrec rdsdb_storage_recommendation_option = {
  1. estimated_monthly_volume_io_ps_cost_variation : rds_estimated_monthly_volume_io_ps_cost_variation option;
    (*

    The projected level of variation in monthly I/O costs for the DB storage recommendation option.

    *)
  2. savings_opportunity_after_discounts : rds_storage_savings_opportunity_after_discounts option;
    (*

    Describes the savings opportunity for DB storage recommendations or for the recommendation option.

    Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

    *)
  3. savings_opportunity : savings_opportunity option;
  4. rank : rank option;
    (*

    The rank identifier of the DB storage recommendation option.

    *)
  5. storage_configuration : db_storage_configuration option;
    (*

    The recommended storage configuration.

    *)
}

Describes the recommendation options for DB storage.

type nonrec rdsdb_storage_recommendation_options = rdsdb_storage_recommendation_option list
type nonrec engine = string
type nonrec engine_version = string
type nonrec promotion_tier = int
type nonrec current_db_instance_class = string
type nonrec db_cluster_identifier = string
type nonrec idle =
  1. | FALSE
  2. | TRUE
type nonrec rds_current_instance_performance_risk =
  1. | HIGH
  2. | MEDIUM
  3. | LOW
  4. | VERY_LOW
type nonrec db_instance_class = string
type nonrec rdsdb_projected_utilization_metrics = rdsdb_utilization_metric list
type nonrec rdsdb_instance_recommendation_option = {
  1. savings_opportunity_after_discounts : rds_instance_savings_opportunity_after_discounts option;
    (*

    Describes the savings opportunity for Amazon Aurora and RDS database recommendations or for the recommendation option.

    Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

    *)
  2. savings_opportunity : savings_opportunity option;
  3. rank : rank option;
    (*

    The rank identifier of the DB instance recommendation option.

    *)
  4. performance_risk : performance_risk option;
    (*

    The performance risk of the DB instance recommendation option.

    *)
  5. projected_utilization_metrics : rdsdb_projected_utilization_metrics option;
    (*

    An array of objects that describe the projected utilization metrics of the DB instance recommendation option.

    *)
  6. db_instance_class : db_instance_class option;
    (*

    Describes the DB instance class recommendation option for your Amazon Aurora or RDS database.

    *)
}

Describes the recommendation options for a DB instance.

type nonrec rdsdb_instance_recommendation_options = rdsdb_instance_recommendation_option list
type nonrec rdsdb_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to your DB instance recommendations.

    *)
  2. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the DB instance recommendation was last generated.

    *)
  3. lookback_period_in_days : look_back_period_in_days option;
    (*

    The number of days the DB instance utilization metrics were analyzed.

    *)
  4. effective_recommendation_preferences : rds_effective_recommendation_preferences option;
    (*

    Describes the effective recommendation preferences for DB instances.

    *)
  5. utilization_metrics : rdsdb_utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the DB instance.

    *)
  6. storage_recommendation_options : rdsdb_storage_recommendation_options option;
    (*

    An array of objects that describe the recommendation options for DB instance storage.

    *)
  7. instance_recommendation_options : rdsdb_instance_recommendation_options option;
    (*

    An array of objects that describe the recommendation options for the RDS DB instance.

    *)
  8. storage_finding_reason_codes : rds_storage_finding_reason_codes option;
    (*

    The reason for the finding classification of RDS DB instance storage.

    *)
  9. current_storage_estimated_monthly_volume_io_ps_cost_variation : rds_estimated_monthly_volume_io_ps_cost_variation option;
    (*

    The level of variation in monthly I/O costs for the current DB storage configuration.

    *)
  10. current_instance_performance_risk : rds_current_instance_performance_risk option;
    (*

    The performance risk for the current DB instance.

    *)
  11. instance_finding_reason_codes : rds_instance_finding_reason_codes option;
    (*

    The reason for the finding classification of a DB instance.

    *)
  12. storage_finding : rds_storage_finding option;
    (*

    The finding classification of Amazon RDS DB instance storage.

    For more information about finding classifications, see Finding classifications for Aurora and RDS databases in the Compute Optimizer User Guide.

    *)
  13. instance_finding : rds_instance_finding option;
    (*

    The finding classification of an Amazon Aurora and RDS DB instance.

    For more information about finding classifications, see Finding classifications for Aurora and RDS databases in the Compute Optimizer User Guide.

    *)
  14. idle : idle option;
    (*

    This indicates if the DB instance is idle or not.

    *)
  15. db_cluster_identifier : db_cluster_identifier option;
    (*

    The identifier for DB cluster.

    *)
  16. current_storage_configuration : db_storage_configuration option;
    (*

    The configuration of the current DB storage.

    *)
  17. current_db_instance_class : current_db_instance_class option;
    (*

    The DB instance class of the current Aurora or RDS DB instance.

    *)
  18. promotion_tier : promotion_tier option;
    (*

    The promotion tier for the Aurora instance.

    *)
  19. engine_version : engine_version option;
    (*

    The database engine version.

    *)
  20. engine : engine option;
    (*

    The engine of the DB instance.

    *)
  21. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the Amazon Aurora or RDS database.

    *)
  22. resource_arn : resource_arn option;
    (*

    The ARN of the current Amazon Aurora or RDS database.

    The following is the format of the ARN:

    arn:aws:rds:{region}:{accountId}:db:{resourceName}

    *)
}

Describes an Amazon Aurora and RDS database recommendation.

type nonrec rdsdb_recommendations = rdsdb_recommendation list
type nonrec rdsdb_recommendation_filter_name =
  1. | IDLE
  2. | STORAGE_FINDING_REASON_CODE
  3. | STORAGE_FINDING
  4. | INSTANCE_FINDING_REASON_CODE
  5. | INSTANCE_FINDING
type nonrec filter_value = string
type nonrec filter_values = filter_value list
type nonrec rdsdb_recommendation_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    *)
  2. name : rdsdb_recommendation_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification.

    You can filter your DB instance recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your DB instance recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all DB instance recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your DB instance recommendations. Use this filter to find all of your DB instance recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your DB instance recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of DB instance recommendations. Use this filter with the GetECSServiceRecommendations action.

type nonrec rdsdb_recommendation_filters = rdsdb_recommendation_filter list
type nonrec put_recommendation_preferences_response = unit
type nonrec preferred_resource = {
  1. exclude_list : preferred_resource_values option;
    (*

    The preferred resource type values to exclude from the recommendation candidates. If this isn’t specified, all supported resources are included by default. You can specify up to 1000 values in this list.

    *)
  2. include_list : preferred_resource_values option;
    (*

    The preferred resource type values to include in the recommendation candidates. You can specify the exact resource type value, such as m5.large, or use wild card expressions, such as m5. If this isn’t specified, all supported resources are included by default. You can specify up to 1000 values in this list.

    *)
  3. name : preferred_resource_name option;
    (*

    The type of preferred resource to customize.

    Compute Optimizer only supports the customization of Ec2InstanceTypes.

    *)
}

The preference to control which resource type values are considered when generating rightsizing recommendations. You can specify this preference as a combination of include and exclude lists. You must specify either an includeList or excludeList. If the preference is an empty set of resource type values, an error occurs. For more information, see Rightsizing recommendation preferences in the Compute Optimizer User Guide.

  • This preference is only available for the Amazon EC2 instance and Auto Scaling group resource types.
  • Compute Optimizer only supports the customization of Ec2InstanceTypes.
type nonrec preferred_resources = preferred_resource list
type nonrec put_recommendation_preferences_request = {
  1. savings_estimation_mode : savings_estimation_mode option;
    (*

    The status of the savings estimation mode preference to create or update.

    Specify the AfterDiscounts status to activate the preference, or specify BeforeDiscounts to deactivate the preference.

    Only the account manager or delegated administrator of your organization can activate this preference.

    For more information, see Savings estimation mode in the Compute Optimizer User Guide.

    *)
  2. preferred_resources : preferred_resources option;
    (*

    The preference to control which resource type values are considered when generating rightsizing recommendations. You can specify this preference as a combination of include and exclude lists. You must specify either an includeList or excludeList. If the preference is an empty set of resource type values, an error occurs.

    You can only set this preference for the Amazon EC2 instance, Auto Scaling group, Amazon EBS volume, Amazon ECS service, Amazon RDS DB instance, and Aurora DB cluster storage resource types.

    *)
  3. utilization_preferences : utilization_preferences option;
    (*

    The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom. When this preference isn't specified, we use the following default values.

    CPU utilization:

    • P99_5 for threshold
    • PERCENT_20 for headroom

    Memory utilization:

    • PERCENT_20 for headroom
    • You can only set CPU and memory utilization preferences for the Amazon EC2 instance resource type.
    • The threshold setting isn’t available for memory utilization.
    *)
  4. look_back_period : look_back_period_preference option;
    (*

    The preference to control the number of days the utilization metrics of the Amazon Web Services resource are analyzed. When this preference isn't specified, we use the default value DAYS_14.

    You can only set this preference for the Amazon EC2 instance, Auto Scaling group, Amazon EBS volume, Amazon ECS service on Fargate, Amazon RDS DB instance, and Aurora DB cluster storage resource types.

    • Lookback period preferences for Amazon EC2 instances, Amazon EBS volumes, Amazon ECS services, Amazon RDS DB instances, and Aurora DB cluster storage resource types can be set at the organization, account, and resource levels.
    • Auto Scaling group lookback preferences can only be set at the resource level.
    • Amazon EBS volume lookback preferences can be set at the organization, account, and resource levels.
    • Amazon ECS service on Fargate lookback preferences can be set at the organization, account, and resource levels.
    • Amazon RDS DB instance lookback preferences can be set at the organization, account, and resource levels.
    • Aurora DB cluster storage lookback preferences can be set at the organization, account, and resource levels.
    • Changing the lookback period for Amazon EBS volumes to 14 days does not affect the 32-day lookback period used to determine whether an Amazon EBS volume is unattached.
    *)
  5. external_metrics_preference : external_metrics_preference option;
    (*

    The provider of the external metrics recommendation preference to create or update.

    Specify a valid provider in the source field to activate the preference. To delete this preference, see the DeleteRecommendationPreferences action.

    This preference can only be set for the Ec2Instance resource type.

    For more information, see External metrics ingestion in the Compute Optimizer User Guide.

    *)
  6. inferred_workload_types : inferred_workload_types_preference option;
    (*

    The status of the inferred workload types recommendation preference to create or update.

    The inferred workload type feature is active by default. To deactivate it, create a recommendation preference.

    Specify the Inactive status to deactivate the feature, or specify Active to activate it.

    For more information, see Inferred workload types in the Compute Optimizer User Guide.

    *)
  7. enhanced_infrastructure_metrics : enhanced_infrastructure_metrics option;
    (*

    The status of the enhanced infrastructure metrics recommendation preference to create or update.

    Specify the Active status to activate the preference, or specify Inactive to deactivate the preference.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  8. scope : scope option;
    (*

    An object that describes the scope of the recommendation preference to create.

    You can create recommendation preferences at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see Activating enhanced infrastructure metrics in the Compute Optimizer User Guide.

    You cannot create recommendation preferences for Auto Scaling groups at the organization and account levels. You can create recommendation preferences for Auto Scaling groups only at the resource level by specifying a scope name of ResourceArn and a scope value of the Auto Scaling group Amazon Resource Name (ARN). This will configure the preference for all instances that are part of the specified Auto Scaling group. You also cannot create recommendation preferences at the resource level for instances that are part of an Auto Scaling group. You can create recommendation preferences at the resource level only for standalone instances.

    *)
  9. resource_type : resource_type;
    (*

    The target resource type of the recommendation preference to create.

    The Ec2Instance option encompasses standalone instances and instances that are part of Auto Scaling groups. The AutoScalingGroup option encompasses only instances that are part of an Auto Scaling group.

    *)
}
type nonrec opt_in_required_exception = {
  1. message : error_message option;
}

The account is not opted in to Compute Optimizer.

type nonrec period = int
type nonrec dimension =
  1. | SAVINGS_VALUE_AFTER_DISCOUNT
  2. | SAVINGS_VALUE
type nonrec order =
  1. | DESC
  2. | ASC
type nonrec order_by = {
  1. order : order option;
    (*

    The order to sort the recommendations.

    *)
  2. dimension : dimension option;
    (*

    The dimension values to sort the recommendations.

    *)
}

Describes how the recommendations are ordered.

type nonrec operating_system = string
type nonrec number_of_member_accounts_opted_in = int
type nonrec number_of_invocations = Smaws_Lib.CoreTypes.Int64.t
type nonrec number_of_cores = int
type nonrec nullable_instance_type = string
type nonrec nullable_estimated_instance_hour_reduction_percentage = float
type nonrec next_token = string
type nonrec mixed_instance_type = string
type nonrec mixed_instance_types = mixed_instance_type list
type nonrec min_size = int
type nonrec metric_source_provider =
  1. | CloudWatchAppInsights
type nonrec metric_provider_arn = string
type nonrec metric_source = {
  1. provider_arn : metric_provider_arn option;
    (*

    The ARN of the metric source provider.

    *)
  2. provider : metric_source_provider option;
    (*

    The name of the metric source provider.

    *)
}

The list of metric sources required to generate recommendations for commercial software licenses.

type nonrec metrics_source = metric_source list
type nonrec message = string
type nonrec memory_size = int
type nonrec member_accounts_enrolled = bool
type nonrec max_size = int
type nonrec max_results = int
type nonrec lower_bound_value = float
type nonrec limit_exceeded_exception = {
  1. message : error_message option;
}

The request exceeds a limit of the service.

type nonrec license_version = string
type nonrec license_edition =
  1. | NO_LICENSE_EDITION_FOUND
  2. | FREE
  3. | STANDARD
  4. | ENTERPRISE
type nonrec license_name =
  1. | SQLSERVER
type nonrec license_model =
  1. | BRING_YOUR_OWN_LICENSE
  2. | LICENSE_INCLUDED
type nonrec license_configuration = {
  1. metrics_source : metrics_source option;
    (*

    The list of metric sources required to generate recommendations for commercial software licenses.

    *)
  2. license_version : license_version option;
    (*

    The version of the license for the application that runs on the instance.

    *)
  3. license_model : license_model option;
    (*

    The license type associated with the instance.

    *)
  4. license_name : license_name option;
    (*

    The name of the license for the application that runs on the instance.

    *)
  5. license_edition : license_edition option;
    (*

    The edition of the license for the application that runs on the instance.

    *)
  6. operating_system : operating_system option;
    (*

    The operating system of the instance.

    *)
  7. instance_type : instance_type option;
    (*

    The instance type used in the license.

    *)
  8. number_of_cores : number_of_cores option;
    (*

    The current number of cores associated with the instance.

    *)
}

Describes the configuration of a license for an Amazon EC2 instance.

type nonrec license_finding =
  1. | NOT_OPTIMIZED
  2. | OPTIMIZED
  3. | INSUFFICIENT_METRICS
type nonrec license_finding_reason_code =
  1. | OPTIMIZED
  2. | LICENSE_OVER_PROVISIONED
  3. | CW_APP_INSIGHTS_ERROR
  4. | CW_APP_INSIGHTS_DISABLED
type nonrec license_finding_reason_codes = license_finding_reason_code list
type nonrec license_recommendation_option = {
  1. savings_opportunity : savings_opportunity option;
  2. license_model : license_model option;
    (*

    The recommended license type associated with the instance.

    *)
  3. license_edition : license_edition option;
    (*

    The recommended edition of the license for the application that runs on the instance.

    *)
  4. operating_system : operating_system option;
    (*

    The operating system of a license recommendation option.

    *)
  5. rank : rank option;
    (*

    The rank of the license recommendation option.

    The top recommendation option is ranked as 1.

    *)
}

Describes the recommendation options for licenses.

type nonrec license_recommendation_options = license_recommendation_option list
type nonrec license_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to an EC2 instance.

    *)
  2. license_recommendation_options : license_recommendation_options option;
    (*

    An array of objects that describe the license recommendation options.

    *)
  3. finding_reason_codes : license_finding_reason_codes option;
    (*

    The reason for the finding classification for an instance that runs on a license.

    Finding reason codes include:

    • Optimized — All specifications of your license meet the performance requirements of your workload.
    • LicenseOverprovisioned — A license is considered over-provisioned when your license can be downgraded while still meeting the performance requirements of your workload.
    • InvalidCloudwatchApplicationInsights — CloudWatch Application Insights isn't configured properly.
    • CloudwatchApplicationInsightsError — There is a CloudWatch Application Insights error.
    *)
  4. finding : license_finding option;
    (*

    The finding classification for an instance that runs on a license.

    Findings include:

    • InsufficentMetrics — When Compute Optimizer detects that your CloudWatch Application Insights isn't enabled or is enabled with insufficient permissions.
    • NotOptimized — When Compute Optimizer detects that your EC2 infrastructure isn't using any of the SQL server license features you're paying for, a license is considered not optimized.
    • Optimized — When Compute Optimizer detects that all specifications of your license meet the performance requirements of your workload.
    *)
  5. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the license recommendation was last generated.

    *)
  6. lookback_period_in_days : look_back_period_in_days option;
    (*

    The number of days for which utilization metrics were analyzed for an instance that runs on a license.

    *)
  7. current_license_configuration : license_configuration option;
    (*

    An object that describes the current configuration of an instance that runs on a license.

    *)
  8. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the license.

    *)
  9. resource_arn : resource_arn option;
    (*

    The ARN that identifies the Amazon EC2 instance.

    *)
}

Describes a license recommendation for an EC2 instance.

type nonrec license_recommendations = license_recommendation list
type nonrec license_recommendation_filter_name =
  1. | LICENSE_NAME
  2. | LICENSE_FINDING_REASON_CODE
  3. | LICENSE_FINDING
type nonrec license_recommendation_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values for this parameter are as follows, depending on what you specify for the name parameter:

    • If you specify the name parameter as Finding, then specify Optimized, NotOptimized, or InsufficentMetrics.
    • If you specify the name parameter as FindingReasonCode, then specify Optimized, LicenseOverprovisioned, InvalidCloudwatchApplicationInsights, or CloudwatchApplicationInsightsError.
    *)
  2. name : license_recommendation_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification.

    Specify FindingReasonCode to return recommendations with a specific finding reason code.

    You can filter your license recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your license recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all license recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your license recommendations. Use this filter to find all of your license recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your license recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of license recommendations. Use this filter with the GetLicenseRecommendation action.

type nonrec license_recommendation_filters = license_recommendation_filter list
type nonrec lambda_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings possible for Lambda functions by adopting Compute Optimizer recommendations. This is based on Lambda functions pricing after applying Savings Plans discounts.

type nonrec lambda_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : lambda_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer’s Lambda function recommendations. This includes any applicable Savings Plans discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer’s Lambda function recommendations. This includes any applicable Savings Plans discounts.

    *)
}

Describes the savings opportunity for Lambda functions recommendations after applying Savings Plans discounts.

Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

type nonrec lambda_savings_estimation_mode_source =
  1. | COST_OPTIMIZATION_HUB
  2. | COST_EXPLORER_RIGHTSIZING
  3. | PUBLIC_PRICING
type nonrec lambda_savings_estimation_mode = {
  1. source : lambda_savings_estimation_mode_source option;
    (*

    Describes the source for calculation of savings opportunity for Lambda functions.

    *)
}

Describes the savings estimation used for calculating savings opportunity for Lambda functions.

type nonrec lambda_function_metric_name =
  1. | MEMORY
  2. | DURATION
type nonrec lambda_function_metric_statistic =
  1. | AVERAGE
  2. | MAXIMUM
type nonrec lambda_function_utilization_metric = {
  1. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  2. statistic : lambda_function_metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  3. name : lambda_function_metric_name option;
    (*

    The name of the utilization metric.

    The following utilization metrics are available:

    • Duration - The amount of time that your function code spends processing an event.
    • Memory - The amount of memory used per invocation.
    *)
}

Describes a utilization metric of an Lambda function.

type nonrec lambda_function_utilization_metrics = lambda_function_utilization_metric list
type nonrec function_arn = string
type nonrec function_version = string
type nonrec lambda_function_recommendation_finding =
  1. | UNAVAILABLE
  2. | NOT_OPTIMIZED
  3. | OPTIMIZED
type nonrec lambda_function_recommendation_finding_reason_code =
  1. | INCONCLUSIVE
  2. | INSUFFICIENT_DATA
  3. | MEMORY_UNDER_PROVISIONED
  4. | MEMORY_OVER_PROVISIONED
type nonrec lambda_function_recommendation_finding_reason_codes = lambda_function_recommendation_finding_reason_code list
type nonrec lambda_function_memory_metric_name =
  1. | DURATION
type nonrec lambda_function_memory_metric_statistic =
  1. | EXPECTED
  2. | UPPER_BOUND
  3. | LOWER_BOUND
type nonrec lambda_function_memory_projected_metric = {
  1. value : metric_value option;
    (*

    The values of the projected utilization metrics.

    *)
  2. statistic : lambda_function_memory_metric_statistic option;
    (*

    The statistic of the projected utilization metric.

    *)
  3. name : lambda_function_memory_metric_name option;
    (*

    The name of the projected utilization metric.

    *)
}

Describes a projected utilization metric of an Lambda function recommendation option.

type nonrec lambda_function_memory_projected_metrics = lambda_function_memory_projected_metric list
type nonrec lambda_function_memory_recommendation_option = {
  1. savings_opportunity_after_discounts : lambda_savings_opportunity_after_discounts option;
    (*

    An object that describes the savings opportunity for the Lambda recommendation option which includes Saving Plans discounts. Savings opportunity includes the estimated monthly savings and percentage.

    *)
  2. savings_opportunity : savings_opportunity option;
    (*

    An object that describes the savings opportunity for the Lambda function recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage.

    *)
  3. projected_utilization_metrics : lambda_function_memory_projected_metrics option;
    (*

    An array of objects that describe the projected utilization metrics of the function recommendation option.

    *)
  4. memory_size : memory_size option;
    (*

    The memory size, in MB, of the function recommendation option.

    *)
  5. rank : rank option;
    (*

    The rank of the function recommendation option.

    The top recommendation option is ranked as 1.

    *)
}

Describes a recommendation option for an Lambda function.

type nonrec lambda_function_memory_recommendation_options = lambda_function_memory_recommendation_option list
type nonrec lambda_effective_recommendation_preferences = {
  1. savings_estimation_mode : lambda_savings_estimation_mode option;
    (*

    Describes the savings estimation mode applied for calculating savings opportunity for Lambda functions.

    *)
}

Describes the effective recommendation preferences for Lambda functions.

type nonrec lambda_function_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to your Lambda function recommendations.

    *)
  2. effective_recommendation_preferences : lambda_effective_recommendation_preferences option;
    (*

    Describes the effective recommendation preferences for Lambda functions.

    *)
  3. current_performance_risk : current_performance_risk option;
    (*

    The risk of the current Lambda function not meeting the performance needs of its workloads. The higher the risk, the more likely the current Lambda function requires more memory.

    *)
  4. memory_size_recommendation_options : lambda_function_memory_recommendation_options option;
    (*

    An array of objects that describe the memory configuration recommendation options for the function.

    *)
  5. finding_reason_codes : lambda_function_recommendation_finding_reason_codes option;
    (*

    The reason for the finding classification of the function.

    Functions that have a finding classification of Optimized don't have a finding reason code.

    Finding reason codes for functions include:

    • MemoryOverprovisioned — The function is over-provisioned when its memory configuration can be sized down while still meeting the performance requirements of your workload. An over-provisioned function might lead to unnecessary infrastructure cost. This finding reason code is part of the NotOptimized finding classification.
    • MemoryUnderprovisioned — The function is under-provisioned when its memory configuration doesn't meet the performance requirements of the workload. An under-provisioned function might lead to poor application performance. This finding reason code is part of the NotOptimized finding classification.
    • InsufficientData — The function does not have sufficient metric data for Compute Optimizer to generate a recommendation. For more information, see the Supported resources and requirements in the Compute Optimizer User Guide. This finding reason code is part of the Unavailable finding classification.
    • Inconclusive — The function does not qualify for a recommendation because Compute Optimizer cannot generate a recommendation with a high degree of confidence. This finding reason code is part of the Unavailable finding classification.
    *)
  6. finding : lambda_function_recommendation_finding option;
    (*

    The finding classification of the function.

    Findings for functions include:

    • Optimized — The function is correctly provisioned to run your workload based on its current configuration and its utilization history. This finding classification does not include finding reason codes.
    • NotOptimized — The function is performing at a higher level (over-provisioned) or at a lower level (under-provisioned) than required for your workload because its current configuration is not optimal. Over-provisioned resources might lead to unnecessary infrastructure cost, and under-provisioned resources might lead to poor application performance. This finding classification can include the MemoryUnderprovisioned and MemoryUnderprovisioned finding reason codes.

    • Unavailable — Compute Optimizer was unable to generate a recommendation for the function. This could be because the function has not accumulated sufficient metric data, or the function does not qualify for a recommendation. This finding classification can include the InsufficientData and Inconclusive finding reason codes.

      Functions with a finding of unavailable are not returned unless you specify the filter parameter with a value of Unavailable in your GetLambdaFunctionRecommendations request.

    *)
  7. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the function recommendation was last generated.

    *)
  8. lookback_period_in_days : look_back_period_in_days option;
    (*

    The number of days for which utilization metrics were analyzed for the function.

    *)
  9. utilization_metrics : lambda_function_utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the function.

    *)
  10. number_of_invocations : number_of_invocations option;
    (*

    The number of times your function code was applied during the look-back period.

    *)
  11. current_memory_size : memory_size option;
    (*

    The amount of memory, in MB, that's allocated to the current function.

    *)
  12. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the function.

    *)
  13. function_version : function_version option;
    (*

    The version number of the current function.

    *)
  14. function_arn : function_arn option;
    (*

    The Amazon Resource Name (ARN) of the current function.

    *)
}

Describes an Lambda function recommendation.

type nonrec lambda_function_recommendations = lambda_function_recommendation list
type nonrec lambda_function_recommendation_filter_name =
  1. | FINDING_REASON_CODE
  2. | FINDING
type nonrec lambda_function_recommendation_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values for this parameter are as follows, depending on what you specify for the name parameter:

    • Specify Optimized, NotOptimized, or Unavailable if you specify the name parameter as Finding.
    • Specify MemoryOverprovisioned, MemoryUnderprovisioned, InsufficientData, or Inconclusive if you specify the name parameter as FindingReasonCode.
    *)
  2. name : lambda_function_recommendation_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification (for example, NotOptimized).

    Specify FindingReasonCode to return recommendations with a specific finding reason code (for example, MemoryUnderprovisioned).

    You can filter your Lambda function recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your Lambda function recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all Lambda function recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your Lambda function recommendations. Use this filter to find all of your Lambda function recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your Lambda function recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of Lambda function recommendations. Use this filter with the GetLambdaFunctionRecommendations action.

You can use EBSFilter with the GetEBSVolumeRecommendations action, JobFilter with the DescribeRecommendationExportJobs action, and Filter with the GetAutoScalingGroupRecommendations and GetEC2InstanceRecommendations actions.

type nonrec lambda_function_recommendation_filters = lambda_function_recommendation_filter list
type nonrec job_ids = job_id list
type nonrec job_filter_name =
  1. | JOB_STATUS
  2. | RESOURCE_TYPE
type nonrec job_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values for this parameter are as follows, depending on what you specify for the name parameter:

    • Specify Ec2Instance or AutoScalingGroup if you specify the name parameter as ResourceType. There is no filter for EBS volumes because volume recommendations cannot be exported at this time.
    • Specify Queued, InProgress, Complete, or Failed if you specify the name parameter as JobStatus.
    *)
  2. name : job_filter_name option;
    (*

    The name of the filter.

    Specify ResourceType to return export jobs of a specific resource type (for example, Ec2Instance).

    Specify JobStatus to return export jobs with a specific status (e.g, Complete).

    *)
}

Describes a filter that returns a more specific list of recommendation export jobs. Use this filter with the DescribeRecommendationExportJobs action.

You can use EBSFilter with the GetEBSVolumeRecommendations action, LambdaFunctionRecommendationFilter with the GetLambdaFunctionRecommendations action, and Filter with the GetAutoScalingGroupRecommendations and GetEC2InstanceRecommendations actions.

type nonrec job_filters = job_filter list
type nonrec instance_state =
  1. | STOPPED
  2. | STOPPING
  3. | TERMINATED
  4. | SHUTTING_DOWN
  5. | RUNNING
  6. | PENDING
type nonrec instance_savings_estimation_mode_source =
  1. | COST_OPTIMIZATION_HUB
  2. | COST_EXPLORER_RIGHTSIZING
  3. | PUBLIC_PRICING
type nonrec instance_savings_estimation_mode = {
  1. source : instance_savings_estimation_mode_source option;
    (*

    Describes the source for calculating the savings opportunity for Amazon EC2 instances.

    *)
}

Describes the savings estimation mode used for calculating savings opportunity for Amazon EC2 instances.

type nonrec instance_arn = string
type nonrec instance_name = string
type nonrec current_instance_type = string
type nonrec instance_recommendation_finding_reason_code =
  1. | GPU_MEMORY_OVER_PROVISIONED
  2. | GPU_MEMORY_UNDER_PROVISIONED
  3. | GPU_OVER_PROVISIONED
  4. | GPU_UNDER_PROVISIONED
  5. | DISK_THROUGHPUT_UNDER_PROVISIONED
  6. | DISK_THROUGHPUT_OVER_PROVISIONED
  7. | DISK_IOPS_UNDER_PROVISIONED
  8. | DISK_IOPS_OVER_PROVISIONED
  9. | NETWORK_PPS_UNDER_PROVISIONED
  10. | NETWORK_PPS_OVER_PROVISIONED
  11. | NETWORK_BANDWIDTH_UNDER_PROVISIONED
  12. | NETWORK_BANDWIDTH_OVER_PROVISIONED
  13. | EBS_IOPS_UNDER_PROVISIONED
  14. | EBS_IOPS_OVER_PROVISIONED
  15. | EBS_THROUGHPUT_UNDER_PROVISIONED
  16. | EBS_THROUGHPUT_OVER_PROVISIONED
  17. | MEMORY_UNDER_PROVISIONED
  18. | MEMORY_OVER_PROVISIONED
  19. | CPU_UNDER_PROVISIONED
  20. | CPU_OVER_PROVISIONED
type nonrec instance_recommendation_finding_reason_codes = instance_recommendation_finding_reason_code list
type nonrec effective_recommendation_preferences = {
  1. savings_estimation_mode : instance_savings_estimation_mode option;
    (*

    Describes the savings estimation mode applied for calculating savings opportunity for a resource.

    *)
  2. preferred_resources : effective_preferred_resources option;
    (*

    The resource type values that are considered as candidates when generating rightsizing recommendations.

    *)
  3. utilization_preferences : utilization_preferences option;
    (*

    The resource’s CPU and memory utilization preferences, such as threshold and headroom, that are used to generate rightsizing recommendations.

    This preference is only available for the Amazon EC2 instance resource type.

    *)
  4. look_back_period : look_back_period_preference option;
    (*

    The number of days the utilization metrics of the Amazon Web Services resource are analyzed.

    *)
  5. external_metrics_preference : external_metrics_preference option;
    (*

    An object that describes the external metrics recommendation preference.

    If the preference is applied in the latest recommendation refresh, an object with a valid source value appears in the response. If the preference isn't applied to the recommendations already, then this object doesn't appear in the response.

    *)
  6. inferred_workload_types : inferred_workload_types_preference option;
    (*

    Describes the activation status of the inferred workload types preference.

    A status of Active confirms that the preference is applied in the latest recommendation refresh. A status of Inactive confirms that it's not yet applied to recommendations.

    *)
  7. enhanced_infrastructure_metrics : enhanced_infrastructure_metrics option;
    (*

    Describes the activation status of the enhanced infrastructure metrics preference.

    A status of Active confirms that the preference is applied in the latest recommendation refresh, and a status of Inactive confirms that it's not yet applied to recommendations.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  8. cpu_vendor_architectures : cpu_vendor_architectures option;
    (*

    Describes the CPU vendor and architecture for an instance or Auto Scaling group recommendations.

    For example, when you specify AWS_ARM64 with:

    • A GetEC2InstanceRecommendations or GetAutoScalingGroupRecommendations request, Compute Optimizer returns recommendations that consist of Graviton instance types only.
    • A GetEC2RecommendationProjectedMetrics request, Compute Optimizer returns projected utilization metrics for Graviton instance type recommendations only.
    • A ExportEC2InstanceRecommendations or ExportAutoScalingGroupRecommendations request, Compute Optimizer exports recommendations that consist of Graviton instance types only.
    *)
}

Describes the effective recommendation preferences for a resource.

type nonrec external_metric_status_code =
  1. | INSUFFICIENT_INSTANA_METRICS
  2. | INSUFFICIENT_NEWRELIC_METRICS
  3. | INSUFFICIENT_DYNATRACE_METRICS
  4. | INSUFFICIENT_DATADOG_METRICS
  5. | INSTANA_INTEGRATION_ERROR
  6. | NEWRELIC_INTEGRATION_ERROR
  7. | DYNATRACE_INTEGRATION_ERROR
  8. | DATADOG_INTEGRATION_ERROR
  9. | INTEGRATION_SUCCESS
  10. | NO_EXTERNAL_METRIC_SET
type nonrec external_metric_status_reason = string
type nonrec external_metric_status = {
  1. status_reason : external_metric_status_reason option;
    (*

    The reason for Compute Optimizer's integration status with your external metric provider.

    *)
  2. status_code : external_metric_status_code option;
    (*

    The status code for Compute Optimizer's integration with an external metrics provider.

    *)
}

Describes Compute Optimizer's integration status with your chosen external metric provider. For example, Datadog.

type nonrec instance_idle =
  1. | FALSE
  2. | TRUE
type nonrec instance_recommendation = {
  1. idle : instance_idle option;
    (*

    Describes if an Amazon EC2 instance is idle.

    *)
  2. current_instance_gpu_info : gpu_info option;
    (*

    Describes the GPU accelerator settings for the current instance type.

    *)
  3. external_metric_status : external_metric_status option;
    (*

    An object that describes Compute Optimizer's integration status with your external metrics provider.

    *)
  4. tags : tags option;
    (*

    A list of tags assigned to your Amazon EC2 instance recommendations.

    *)
  5. instance_state : instance_state option;
    (*

    The state of the instance when the recommendation was generated.

    *)
  6. inferred_workload_types : inferred_workload_types option;
    (*

    The applications that might be running on the instance as inferred by Compute Optimizer.

    Compute Optimizer can infer if one of the following applications might be running on the instance:

    • AmazonEmr - Infers that Amazon EMR might be running on the instance.
    • ApacheCassandra - Infers that Apache Cassandra might be running on the instance.
    • ApacheHadoop - Infers that Apache Hadoop might be running on the instance.
    • Memcached - Infers that Memcached might be running on the instance.
    • NGINX - Infers that NGINX might be running on the instance.
    • PostgreSql - Infers that PostgreSQL might be running on the instance.
    • Redis - Infers that Redis might be running on the instance.
    • Kafka - Infers that Kafka might be running on the instance.
    • SQLServer - Infers that SQLServer might be running on the instance.
    *)
  7. effective_recommendation_preferences : effective_recommendation_preferences option;
    (*

    An object that describes the effective recommendation preferences for the instance.

    *)
  8. current_performance_risk : current_performance_risk option;
    (*

    The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current instance cannot meet the performance requirements of its workload.

    *)
  9. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the instance recommendation was last generated.

    *)
  10. recommendation_sources : recommendation_sources option;
    (*

    An array of objects that describe the source resource of the recommendation.

    *)
  11. recommendation_options : recommendation_options option;
    (*

    An array of objects that describe the recommendation options for the instance.

    *)
  12. look_back_period_in_days : look_back_period_in_days option;
    (*

    The number of days for which utilization metrics were analyzed for the instance.

    *)
  13. utilization_metrics : utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the instance.

    *)
  14. finding_reason_codes : instance_recommendation_finding_reason_codes option;
    (*

    The reason for the finding classification of the instance.

    Finding reason codes for instances include:

    • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.
    • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing the CPUUtilization metric of the current instance during the look-back period.
    • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

    • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.

      Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the mem_used_percent metric in the CWAgent namespace, or the legacy MemoryUtilization metric in the System/Linux namespace. On Windows instances, Compute Optimizer analyses the Memory % Committed Bytes In Use metric in the CWAgent namespace.

    • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metrics of EBS volumes attached to the current instance during the look-back period.
    • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing the VolumeReadBytes and VolumeWriteBytes metrics of EBS volumes attached to the current instance during the look-back period.
    • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metric of EBS volumes attached to the current instance during the look-back period.
    • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing the VolumeReadOps and VolumeWriteOps metric of EBS volumes attached to the current instance during the look-back period.
    • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period.
    • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing the NetworkIn and NetworkOut metrics of the current instance during the look-back period. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.
    • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.
    • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing the NetworkPacketsIn and NetworkPacketsIn metrics of the current instance during the look-back period.
    • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.
    • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing the DiskReadOps and DiskWriteOps metrics of the current instance during the look-back period.
    • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.
    • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing the DiskReadBytes and DiskWriteBytes metrics of the current instance during the look-back period.

    For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.

    *)
  15. finding : finding option;
    (*

    The finding classification of the instance.

    Findings for instances include:

    • Underprovisioned—An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance.
    • Overprovisioned—An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost.
    • Optimized—An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.

    The valid values in your API responses appear as OVER_PROVISIONED, UNDER_PROVISIONED, or OPTIMIZED.

    *)
  16. current_instance_type : current_instance_type option;
    (*

    The instance type of the current instance.

    *)
  17. instance_name : instance_name option;
    (*

    The name of the current instance.

    *)
  18. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the instance.

    *)
  19. instance_arn : instance_arn option;
    (*

    The Amazon Resource Name (ARN) of the current instance.

    *)
}

Describes an Amazon EC2 instance recommendation.

type nonrec instance_recommendations = instance_recommendation list
type nonrec instance_arns = instance_arn list
type nonrec idle_metric_name =
  1. | CURR_CONNECTIONS
  2. | ELASTI_CACHE_PROCESSING_UNITS
  3. | SET_TYPE_CMDS
  4. | GET_TYPE_CMDS
  5. | INVOCATIONS
  6. | USER_CONNECTED
  7. | IS_IDLE
  8. | KEYSPACE_MISSES
  9. | KEYSPACE_HITS
  10. | CACHE_MISSES
  11. | CACHE_HITS
  12. | ENGINE_CPU_UTILIZATION
  13. | NEW_CONNECTIONS
  14. | CONSUMED_CHANGE_DATA_CAPTURE_UNITS
  15. | CONSUMED_WRITE_CAPACITY_UNITS
  16. | CONSUMED_READ_CAPACITY_UNITS
  17. | PACKETS_IN_FROM_DESTINATION
  18. | PACKETS_IN_FROM_SOURCE
  19. | ACTIVE_CONNECTION_COUNT
  20. | VOLUME_WRITE_OPS_PER_SECOND
  21. | VOLUME_READ_OPS_PER_SECOND
  22. | EBS_VOLUME_WRITE_IOPS
  23. | EBS_VOLUME_READ_IOPS
  24. | DATABASE_CONNECTIONS
  25. | NETWORK_IN_BYTES_PER_SECOND
  26. | NETWORK_OUT_BYTES_PER_SECOND
  27. | MEMORY
  28. | CPU
type nonrec idle_dimension_key = string
type nonrec idle_dimension_value = string
type nonrec idle_dimension_values = idle_dimension_value list
type nonrec idle_dimension = {
  1. values : idle_dimension_values option;
    (*

    The value of the dimension.

    *)
  2. key : idle_dimension_key option;
    (*

    The name of the dimension key.

    *)
}

Describes the dimension of an idle resource utilization metric.

type nonrec idle_dimensions = idle_dimension list
type nonrec idle_utilization_metric = {
  1. dimensions : idle_dimensions option;
    (*

    The dimensions of the utilization metric.

    *)
  2. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  3. statistic : metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  4. name : idle_metric_name option;
    (*

    The name of the utilization metric.

    *)
}

Describes the utilization metric of an idle resource.

type nonrec idle_utilization_metrics = idle_utilization_metric list
type nonrec idle_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings for Idle resources.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings possible for idle resources by adopting Compute Optimizer recommendations.

type nonrec idle_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : idle_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer's idle resource recommendations. This includes any applicable discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer's idle resource recommendations. This includes any applicable discounts.

    *)
}

Describes the savings opportunity for idle resource recommendations after applying discounts.

Savings opportunity represents the estimated monthly savings after applying discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

type nonrec idle_savings_opportunity = {
  1. estimated_monthly_savings : idle_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer's idle resource recommendations.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer's idle resource recommendations.

    *)
}

Describes the savings opportunity for idle resource recommendations.

type nonrec idle_recommendation_resource_type =
  1. | SAGE_MAKER_ENDPOINT
  2. | WORKSPACES
  3. | DOCUMENT_DB_CLUSTER
  4. | MEMORY_DB_CLUSTER
  5. | ELASTI_CACHE_CLUSTER
  6. | DYNAMO_DB_TABLE
  7. | NAT_GATEWAY
  8. | RDS_DB_INSTANCE
  9. | ECS_SERVICE
  10. | EBS_VOLUME
  11. | AUTO_SCALING_GROUP
  12. | EC2_INSTANCE
type nonrec idle_finding_description = string
type nonrec idle_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to your idle resource recommendations.

    *)
  2. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the idle resource recommendation was last generated.

    *)
  3. look_back_period_in_days : look_back_period_in_days option;
    (*

    The number of days the idle resource utilization metrics were analyzed.

    *)
  4. utilization_metrics : idle_utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the idle resource.

    *)
  5. savings_opportunity_after_discounts : idle_savings_opportunity_after_discounts option;
    (*

    The savings opportunity for the idle resource after any applying discounts.

    *)
  6. savings_opportunity : idle_savings_opportunity option;
    (*

    The savings opportunity for the idle resource.

    *)
  7. finding_description : idle_finding_description option;
    (*

    A summary of the findings for the resource.

    *)
  8. finding : idle_finding option;
    (*

    The finding classification of an idle resource.

    *)
  9. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the idle resource.

    *)
  10. resource_type : idle_recommendation_resource_type option;
    (*

    The type of resource that is idle.

    *)
  11. resource_id : resource_id option;
    (*

    The unique identifier for the resource.

    *)
  12. resource_arn : resource_arn option;
    (*

    The ARN of the current idle resource.

    *)
}

Describes an Idle resource recommendation.

type nonrec idle_recommendations = idle_recommendation list
type nonrec idle_recommendation_filter_name =
  1. | RESOURCE_TYPE
  2. | FINDING
type nonrec idle_recommendation_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    *)
  2. name : idle_recommendation_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification.

    You can filter your idle resource recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your idle resource recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all idle resource service recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your idle resource recommendations. Use this filter to find all of your idle resource recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your idle resource service recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of idle resource recommendations.

type nonrec idle_recommendation_filters = idle_recommendation_filter list
type nonrec identifier = string
type nonrec code = string
type nonrec idle_recommendation_error = {
  1. resource_type : idle_recommendation_resource_type option;
    (*

    The type of resource associated with the error.

    *)
  2. message : message option;
    (*

    The error message.

    *)
  3. code : code option;
    (*

    The error code.

    *)
  4. identifier : identifier option;
    (*

    The ID of the error.

    *)
}

Returns of list of resources that doesn't have idle recommendations.

type nonrec idle_recommendation_errors = idle_recommendation_error list
type nonrec idle_max_results = int
type nonrec get_recommendation_summaries_response = {
  1. recommendation_summaries : recommendation_summaries option;
    (*

    An array of objects that summarize a recommendation.

    *)
  2. next_token : next_token option;
    (*

    The token to use to advance to the next page of recommendation summaries.

    This value is null when there are no more pages of recommendation summaries to return.

    *)
}
type nonrec account_ids = account_id list
type nonrec get_recommendation_summaries_request = {
  1. max_results : max_results option;
    (*

    The maximum number of recommendation summaries to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  2. next_token : next_token option;
    (*

    The token to advance to the next page of recommendation summaries.

    *)
  3. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return recommendation summaries.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return recommendation summaries.

    Only one account ID can be specified per request.

    *)
}
type nonrec get_recommendation_preferences_response = {
  1. recommendation_preferences_details : recommendation_preferences_details option;
    (*

    An array of objects that describe recommendation preferences.

    *)
  2. next_token : next_token option;
    (*

    The token to use to advance to the next page of recommendation preferences.

    This value is null when there are no more pages of recommendation preferences to return.

    *)
}
type nonrec get_recommendation_preferences_request = {
  1. max_results : max_results option;
    (*

    The maximum number of recommendation preferences to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  2. next_token : next_token option;
    (*

    The token to advance to the next page of recommendation preferences.

    *)
  3. scope : scope option;
    (*

    An object that describes the scope of the recommendation preference to return.

    You can return recommendation preferences that are created at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see Activating enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  4. resource_type : resource_type;
    (*

    The target resource type of the recommendation preference for which to return preferences.

    The Ec2Instance option encompasses standalone instances and instances that are part of Auto Scaling groups. The AutoScalingGroup option encompasses only instances that are part of an Auto Scaling group.

    *)
}
type nonrec get_recommendation_error = {
  1. message : message option;
    (*

    The message, or reason, for the error.

    *)
  2. code : code option;
    (*

    The error code.

    *)
  3. identifier : identifier option;
    (*

    The ID of the error.

    *)
}

Describes an error experienced when getting recommendations.

For example, an error is returned if you request recommendations for an unsupported Auto Scaling group, or if you request recommendations for an instance of an unsupported instance family.

type nonrec get_recommendation_errors = get_recommendation_error list
type nonrec get_rds_database_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    *)
  2. rds_db_recommendations : rdsdb_recommendations option;
    (*

    An array of objects that describe the Amazon Aurora and RDS database recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to advance to the next page of Amazon Aurora and RDS database recommendations.

    *)
}
type nonrec get_rds_database_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
  2. account_ids : account_ids option;
    (*

    Return the Amazon Aurora and RDS database recommendations to the specified Amazon Web Services account IDs.

    If your account is the management account or the delegated administrator of an organization, use this parameter to return the Amazon Aurora and RDS database recommendations to specific member accounts.

    You can only specify one account ID per request.

    *)
  3. filters : rdsdb_recommendation_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of Amazon Aurora and RDS database recommendations.

    *)
  4. max_results : max_results option;
    (*

    The maximum number of Amazon Aurora and RDS database recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  5. next_token : next_token option;
    (*

    The token to advance to the next page of Amazon Aurora and RDS database recommendations.

    *)
  6. resource_arns : resource_arns option;
    (*

    The ARN that identifies the Amazon Aurora or RDS database.

    The following is the format of the ARN:

    arn:aws:rds:{region}:{accountId}:db:{resourceName}

    The following is the format of a DB Cluster ARN:

    arn:aws:rds:{region}:{accountId}:cluster:{resourceName}

    *)
}
type nonrec get_rds_database_recommendation_projected_metrics_response = {
  1. recommended_option_projected_metrics : rds_database_recommended_option_projected_metrics option;
    (*

    An array of objects that describes the projected metrics.

    *)
}
type nonrec get_rds_database_recommendation_projected_metrics_request = {
  1. recommendation_preferences : recommendation_preferences option;
  2. end_time : timestamp;
    (*

    The timestamp of the last projected metrics data point to return.

    *)
  3. start_time : timestamp;
    (*

    The timestamp of the first projected metrics data point to return.

    *)
  4. period : period;
    (*

    The granularity, in seconds, of the projected metrics data points.

    *)
  5. stat : metric_statistic;
    (*

    The statistic of the projected metrics.

    *)
  6. resource_arn : resource_arn;
    (*

    The ARN that identifies the Amazon Aurora or RDS database.

    The following is the format of the ARN:

    arn:aws:rds:{region}:{accountId}:db:{resourceName}

    *)
}
type nonrec get_license_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    *)
  2. license_recommendations : license_recommendations option;
    (*

    An array of objects that describe license recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to use to advance to the next page of license recommendations.

    *)
}
type nonrec get_license_recommendations_request = {
  1. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return license recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return license recommendations.

    Only one account ID can be specified per request.

    *)
  2. filters : license_recommendation_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of license recommendations.

    *)
  3. max_results : max_results option;
    (*

    The maximum number of license recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  4. next_token : next_token option;
    (*

    The token to advance to the next page of license recommendations.

    *)
  5. resource_arns : resource_arns option;
    (*

    The ARN that identifies the Amazon EC2 instance.

    The following is the format of the ARN:

    arn:aws:ec2:region:aws_account_id:instance/instance-id

    *)
}
type nonrec get_lambda_function_recommendations_response = {
  1. lambda_function_recommendations : lambda_function_recommendations option;
    (*

    An array of objects that describe function recommendations.

    *)
  2. next_token : next_token option;
    (*

    The token to use to advance to the next page of function recommendations.

    This value is null when there are no more pages of function recommendations to return.

    *)
}
type nonrec function_arns = function_arn list
type nonrec get_lambda_function_recommendations_request = {
  1. max_results : max_results option;
    (*

    The maximum number of function recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  2. next_token : next_token option;
    (*

    The token to advance to the next page of function recommendations.

    *)
  3. filters : lambda_function_recommendation_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of function recommendations.

    *)
  4. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return function recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return function recommendations.

    Only one account ID can be specified per request.

    *)
  5. function_arns : function_arns option;
    (*

    The Amazon Resource Name (ARN) of the functions for which to return recommendations.

    You can specify a qualified or unqualified ARN. If you specify an unqualified ARN without a function version suffix, Compute Optimizer will return recommendations for the latest ($LATEST) version of the function. If you specify a qualified ARN with a version suffix, Compute Optimizer will return recommendations for the specified function version. For more information about using function versions, see Using versions in the Lambda Developer Guide.

    *)
}
type nonrec get_idle_recommendations_response = {
  1. errors : idle_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    *)
  2. idle_recommendations : idle_recommendations option;
    (*

    An array of objects that describe the idle resource recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to advance to the next page of idle resource recommendations.

    *)
}
type nonrec get_idle_recommendations_request = {
  1. order_by : order_by option;
    (*

    The order to sort the idle resource recommendations.

    *)
  2. account_ids : account_ids option;
    (*

    Return the idle resource recommendations to the specified Amazon Web Services account IDs.

    If your account is the management account or the delegated administrator of an organization, use this parameter to return the idle resource recommendations to specific member accounts.

    You can only specify one account ID per request.

    *)
  3. filters : idle_recommendation_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of idle resource recommendations.

    *)
  4. max_results : idle_max_results option;
    (*

    The maximum number of idle resource recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  5. next_token : next_token option;
    (*

    The token to advance to the next page of idle resource recommendations.

    *)
  6. resource_arns : resource_arns option;
    (*

    The ARN that identifies the idle resource.

    *)
}
type nonrec account_enrollment_status = {
  1. last_updated_timestamp : last_updated_timestamp option;
    (*

    The Unix epoch timestamp, in seconds, of when the account enrollment status was last updated.

    *)
  2. status_reason : status_reason option;
    (*

    The reason for the account enrollment status.

    For example, an account might show a status of Pending because member accounts of an organization require more time to be enrolled in the service.

    *)
  3. status : status option;
    (*

    The account enrollment status.

    *)
  4. account_id : account_id option;
    (*

    The Amazon Web Services account ID.

    *)
}

Describes the enrollment status of an organization's member accounts in Compute Optimizer.

type nonrec account_enrollment_statuses = account_enrollment_status list
type nonrec get_enrollment_statuses_for_organization_response = {
  1. next_token : next_token option;
    (*

    The token to use to advance to the next page of account enrollment statuses.

    This value is null when there are no more pages of account enrollment statuses to return.

    *)
  2. account_enrollment_statuses : account_enrollment_statuses option;
    (*

    An array of objects that describe the enrollment statuses of organization member accounts.

    *)
}
type nonrec enrollment_filter_name =
  1. | STATUS
type nonrec enrollment_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values are Active, Inactive, Pending, and Failed.

    *)
  2. name : enrollment_filter_name option;
    (*

    The name of the filter.

    Specify Status to return accounts with a specific enrollment status (for example, Active).

    *)
}

Describes a filter that returns a more specific list of account enrollment statuses. Use this filter with the GetEnrollmentStatusesForOrganization action.

type nonrec enrollment_filters = enrollment_filter list
type nonrec get_enrollment_statuses_for_organization_request = {
  1. max_results : max_results option;
    (*

    The maximum number of account enrollment statuses to return with a single request. You can specify up to 100 statuses to return with each request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  2. next_token : next_token option;
    (*

    The token to advance to the next page of account enrollment statuses.

    *)
  3. filters : enrollment_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of account enrollment statuses.

    *)
}
type nonrec get_enrollment_status_response = {
  1. number_of_member_accounts_opted_in : number_of_member_accounts_opted_in option;
    (*

    The count of organization member accounts that are opted in to the service, if your account is an organization management account.

    *)
  2. last_updated_timestamp : last_updated_timestamp option;
    (*

    The Unix epoch timestamp, in seconds, of when the account enrollment status was last updated.

    *)
  3. member_accounts_enrolled : member_accounts_enrolled option;
    (*

    Confirms the enrollment status of member accounts of the organization, if the account is a management account of an organization.

    *)
  4. status_reason : status_reason option;
    (*

    The reason for the enrollment status of the account.

    For example, an account might show a status of Pending because member accounts of an organization require more time to be enrolled in the service.

    *)
  5. status : status option;
    (*

    The enrollment status of the account.

    *)
}
type nonrec get_enrollment_status_request = unit
type nonrec get_effective_recommendation_preferences_response = {
  1. preferred_resources : effective_preferred_resources option;
    (*

    The resource type values that are considered as candidates when generating rightsizing recommendations. This object resolves any wildcard expressions and returns the effective list of candidate resource type values. It also considers all applicable preferences that you set at the resource, account, and organization level.

    To validate that the preference is applied to your last generated set of recommendations, review the effectiveRecommendationPreferences value in the response of the GetAutoScalingGroupRecommendations or GetEC2InstanceRecommendations actions.

    *)
  2. utilization_preferences : utilization_preferences option;
    (*

    The resource’s CPU and memory utilization preferences, such as threshold and headroom, that were used to generate rightsizing recommendations. It considers all applicable preferences that you set at the resource, account, and organization level.

    To validate that the preference is applied to your last generated set of recommendations, review the effectiveRecommendationPreferences value in the response of the GetAutoScalingGroupRecommendations or GetEC2InstanceRecommendations actions.

    *)
  3. look_back_period : look_back_period_preference option;
    (*

    The number of days the utilization metrics of the Amazon Web Services resource are analyzed.

    To validate that the preference is applied to your last generated set of recommendations, review the effectiveRecommendationPreferences value in the response of the GetAutoScalingGroupRecommendations, GetEC2InstanceRecommendations, GetEBSVolumeRecommendations, GetECSServiceRecommendations, or GetRDSDatabaseRecommendations actions.

    *)
  4. external_metrics_preference : external_metrics_preference option;
    (*

    The provider of the external metrics recommendation preference. Considers all applicable preferences that you might have set at the account and organization level.

    If the preference is applied in the latest recommendation refresh, an object with a valid source value appears in the response. If the preference isn't applied to the recommendations already, then this object doesn't appear in the response.

    To validate whether the preference is applied to your last generated set of recommendations, review the effectiveRecommendationPreferences value in the response of the GetEC2InstanceRecommendations actions.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  5. enhanced_infrastructure_metrics : enhanced_infrastructure_metrics option;
    (*

    The status of the enhanced infrastructure metrics recommendation preference. Considers all applicable preferences that you might have set at the resource, account, and organization level.

    A status of Active confirms that the preference is applied in the latest recommendation refresh, and a status of Inactive confirms that it's not yet applied to recommendations.

    To validate whether the preference is applied to your last generated set of recommendations, review the effectiveRecommendationPreferences value in the response of the GetAutoScalingGroupRecommendations and GetEC2InstanceRecommendations actions.

    For more information, see Enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
}
type nonrec get_effective_recommendation_preferences_request = {
  1. resource_arn : resource_arn;
    (*

    The Amazon Resource Name (ARN) of the resource for which to confirm effective recommendation preferences. Only EC2 instance and Auto Scaling group ARNs are currently supported.

    *)
}
type nonrec ecs_service_metric_name =
  1. | MEMORY
  2. | CPU
type nonrec ecs_service_metric_statistic =
  1. | AVERAGE
  2. | MAXIMUM
type nonrec ecs_service_utilization_metric = {
  1. value : metric_value option;
    (*

    The value of the utilization metric.

    *)
  2. statistic : ecs_service_metric_statistic option;
    (*

    The statistic of the utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  3. name : ecs_service_metric_name option;
    (*

    The name of the utilization metric.

    The following utilization metrics are available:

    • Cpu — The amount of CPU capacity that's used in the service.
    • Memory — The amount of memory that's used in the service.
    *)
}

Describes the utilization metric of an Amazon ECS service.

To determine the performance difference between your current Amazon ECS service and the recommended option, compare the utilization metric data of your service against its projected utilization metric data.

type nonrec ecs_service_utilization_metrics = ecs_service_utilization_metric list
type nonrec ecs_service_launch_type =
  1. | FARGATE
  2. | EC2
type nonrec ecs_service_recommendation_finding =
  1. | OVER_PROVISIONED
  2. | UNDER_PROVISIONED
  3. | OPTIMIZED
type nonrec ecs_service_recommendation_finding_reason_code =
  1. | CPU_UNDER_PROVISIONED
  2. | CPU_OVER_PROVISIONED
  3. | MEMORY_UNDER_PROVISIONED
  4. | MEMORY_OVER_PROVISIONED
type nonrec ecs_service_recommendation_finding_reason_codes = ecs_service_recommendation_finding_reason_code list
type nonrec ecs_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings for Amazon ECS services.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

Describes the estimated monthly savings possible for Amazon ECS services by adopting Compute Optimizer recommendations. This is based on Amazon ECS service pricing after applying Savings Plans discounts.

type nonrec ecs_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : ecs_estimated_monthly_savings option;
    (*

    The estimated monthly savings possible by adopting Compute Optimizer’s Amazon ECS service recommendations. This includes any applicable Savings Plans discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer’s Amazon ECS service recommendations. This includes any applicable Savings Plans discounts.

    *)
}

Describes the savings opportunity for Amazon ECS service recommendations after applying Savings Plans discounts.

Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

type nonrec ecs_service_projected_utilization_metric = {
  1. upper_bound_value : upper_bound_value option;
    (*

    The upper bound values for the projected utilization metrics.

    *)
  2. lower_bound_value : lower_bound_value option;
    (*

    The lower bound values for the projected utilization metrics.

    *)
  3. statistic : ecs_service_metric_statistic option;
    (*

    The statistic of the projected utilization metric.

    The Compute Optimizer API, Command Line Interface (CLI), and SDKs return utilization metrics using only the Maximum statistic, which is the highest value observed during the specified period.

    The Compute Optimizer console displays graphs for some utilization metrics using the Average statistic, which is the value of Sum / SampleCount during the specified period. For more information, see Viewing resource recommendations in the Compute Optimizer User Guide. You can also get averaged utilization metric data for your resources using Amazon CloudWatch. For more information, see the Amazon CloudWatch User Guide.

    *)
  4. name : ecs_service_metric_name option;
    (*

    The name of the projected utilization metric.

    The following utilization metrics are available:

    • Cpu — The percentage of allocated compute units that are currently in use on the service tasks.
    • Memory — The percentage of memory that's currently in use on the service tasks.
    *)
}

Describes the projected utilization metrics of an Amazon ECS service recommendation option.

To determine the performance difference between your current Amazon ECS service and the recommended option, compare the utilization metric data of your service against its projected utilization metric data.

type nonrec ecs_service_projected_utilization_metrics = ecs_service_projected_utilization_metric list
type nonrec container_recommendation = {
  1. cpu : nullable_cpu option;
    (*

    The recommended number of CPU units reserved for the container.

    *)
  2. memory_size_configuration : memory_size_configuration option;
    (*

    The recommended memory size configurations for the container.

    *)
  3. container_name : container_name option;
    (*

    The name of the container.

    *)
}

The CPU and memory recommendations for a container within the tasks of your Amazon ECS service.

type nonrec container_recommendations = container_recommendation list
type nonrec ecs_service_recommendation_option = {
  1. container_recommendations : container_recommendations option;
    (*

    The CPU and memory size recommendations for the containers within the task of your Amazon ECS service.

    *)
  2. projected_utilization_metrics : ecs_service_projected_utilization_metrics option;
    (*

    An array of objects that describe the projected utilization metrics of the Amazon ECS service recommendation option.

    *)
  3. savings_opportunity_after_discounts : ecs_savings_opportunity_after_discounts option;
    (*

    Describes the savings opportunity for Amazon ECS service recommendations or for the recommendation option.

    Savings opportunity represents the estimated monthly savings after applying Savings Plans discounts. You can achieve this by implementing a given Compute Optimizer recommendation.

    *)
  4. savings_opportunity : savings_opportunity option;
  5. cpu : nullable_cpu option;
    (*

    The CPU size of the Amazon ECS service recommendation option.

    *)
  6. memory : nullable_memory option;
    (*

    The memory size of the Amazon ECS service recommendation option.

    *)
}

Describes the recommendation options for an Amazon ECS service.

type nonrec ecs_service_recommendation_options = ecs_service_recommendation_option list
type nonrec ecs_savings_estimation_mode_source =
  1. | COST_OPTIMIZATION_HUB
  2. | COST_EXPLORER_RIGHTSIZING
  3. | PUBLIC_PRICING
type nonrec ecs_savings_estimation_mode = {
  1. source : ecs_savings_estimation_mode_source option;
    (*

    Describes the source for calculating the savings opportunity for Amazon ECS services.

    *)
}

Describes the savings estimation mode used for calculating savings opportunity for Amazon ECS services.

type nonrec ecs_effective_recommendation_preferences = {
  1. look_back_period : look_back_period_preference option;
    (*

    The number of days the Amazon ECS service utilization metrics were analyzed.

    *)
  2. savings_estimation_mode : ecs_savings_estimation_mode option;
    (*

    Describes the savings estimation mode preference applied for calculating savings opportunity for Amazon ECS services.

    *)
}

Describes the effective recommendation preferences for Amazon ECS services.

type nonrec ecs_service_recommendation = {
  1. tags : tags option;
    (*

    A list of tags assigned to your Amazon ECS service recommendations.

    *)
  2. effective_recommendation_preferences : ecs_effective_recommendation_preferences option;
    (*

    Describes the effective recommendation preferences for Amazon ECS services.

    *)
  3. current_performance_risk : current_performance_risk option;
    (*

    The risk of the current Amazon ECS service not meeting the performance needs of its workloads. The higher the risk, the more likely the current service can't meet the performance requirements of its workload.

    *)
  4. service_recommendation_options : ecs_service_recommendation_options option;
    (*

    An array of objects that describe the recommendation options for the Amazon ECS service.

    *)
  5. finding_reason_codes : ecs_service_recommendation_finding_reason_codes option;
    (*

    The reason for the finding classification of an Amazon ECS service.

    Finding reason codes for Amazon ECS services include:

    • CPUUnderprovisioned — The service CPU configuration can be sized up to enhance the performance of your workload. This is identified by analyzing the CPUUtilization metric of the current service during the look-back period.
    • CPUOverprovisioned — The service CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the CPUUtilization metric of the current service during the look-back period.
    • MemoryUnderprovisioned — The service memory configuration can be sized up to enhance the performance of your workload. This is identified by analyzing the MemoryUtilization metric of the current service during the look-back period.
    • MemoryOverprovisioned — The service memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the MemoryUtilization metric of the current service during the look-back period.
    *)
  6. finding : ecs_service_recommendation_finding option;
    (*

    The finding classification of an Amazon ECS service.

    Findings for Amazon ECS services include:

    • Underprovisioned — When Compute Optimizer detects that there’s not enough memory or CPU, an Amazon ECS service is considered under-provisioned. An under-provisioned service might result in poor application performance.
    • Overprovisioned — When Compute Optimizer detects that there’s excessive memory or CPU, an Amazon ECS service is considered over-provisioned. An over-provisioned service might result in additional infrastructure costs.
    • Optimized — When both the CPU and memory of your Amazon ECS service meet the performance requirements of your workload, the service is considered optimized.
    *)
  7. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the Amazon ECS service recommendation was last generated.

    *)
  8. launch_type : ecs_service_launch_type option;
    (*

    The launch type the Amazon ECS service is using.

    Compute Optimizer only supports the Fargate launch type.

    *)
  9. lookback_period_in_days : look_back_period_in_days option;
    (*

    The number of days the Amazon ECS service utilization metrics were analyzed.

    *)
  10. utilization_metrics : ecs_service_utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the Amazon ECS service.

    *)
  11. current_service_configuration : service_configuration option;
    (*

    The configuration of the current Amazon ECS service.

    *)
  12. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the Amazon ECS service.

    *)
  13. service_arn : service_arn option;
    (*

    The Amazon Resource Name (ARN) of the current Amazon ECS service.

    The following is the format of the ARN:

    arn:aws:ecs:region:aws_account_id:service/cluster-name/service-name

    *)
}

Describes an Amazon ECS service recommendation.

type nonrec ecs_service_recommendations = ecs_service_recommendation list
type nonrec get_ecs_service_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    *)
  2. ecs_service_recommendations : ecs_service_recommendations option;
    (*

    An array of objects that describe the Amazon ECS service recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to advance to the next page of Amazon ECS service recommendations.

    *)
}
type nonrec ecs_service_recommendation_filter_name =
  1. | FINDING_REASON_CODE
  2. | FINDING
type nonrec ecs_service_recommendation_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values for this parameter are as follows:

    • If you specify the name parameter as Finding, specify Optimized, Underprovisioned, or Overprovisioned.
    • If you specify the name parameter as FindingReasonCode, specify CPUUnderprovisioned, CPUOverprovisioned, MemoryUnderprovisioned, or MemoryOverprovisioned.
    *)
  2. name : ecs_service_recommendation_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification.

    Specify FindingReasonCode to return recommendations with a specific finding reason code.

    You can filter your Amazon ECS service recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your Amazon ECS service recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all Amazon ECS service recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your Amazon ECS service recommendations. Use this filter to find all of your Amazon ECS service recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your Amazon ECS service recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of Amazon ECS service recommendations. Use this filter with the GetECSServiceRecommendations action.

type nonrec ecs_service_recommendation_filters = ecs_service_recommendation_filter list
type nonrec get_ecs_service_recommendations_request = {
  1. account_ids : account_ids option;
    (*

    Return the Amazon ECS service recommendations to the specified Amazon Web Services account IDs.

    If your account is the management account or the delegated administrator of an organization, use this parameter to return the Amazon ECS service recommendations to specific member accounts.

    You can only specify one account ID per request.

    *)
  2. filters : ecs_service_recommendation_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of Amazon ECS service recommendations.

    *)
  3. max_results : max_results option;
    (*

    The maximum number of Amazon ECS service recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  4. next_token : next_token option;
    (*

    The token to advance to the next page of Amazon ECS service recommendations.

    *)
  5. service_arns : service_arns option;
    (*

    The ARN that identifies the Amazon ECS service.

    The following is the format of the ARN:

    arn:aws:ecs:region:aws_account_id:service/cluster-name/service-name

    *)
}
type nonrec cpu_size = int
type nonrec ecs_service_projected_metric = {
  1. lower_bound_values : metric_values option;
    (*

    The lower bound values for the projected metric.

    *)
  2. upper_bound_values : metric_values option;
    (*

    The upper bound values for the projected metric.

    *)
  3. timestamps : timestamps option;
    (*

    The timestamps of the projected metric.

    *)
  4. name : ecs_service_metric_name option;
    (*

    The name of the projected metric.

    The following metrics are available:

    • Cpu — The percentage of allocated compute units that are currently in use on the service tasks.
    • Memory — The percentage of memory that's currently in use on the service tasks.
    *)
}

Describes the projected metrics of an Amazon ECS service recommendation option.

To determine the performance difference between your current Amazon ECS service and the recommended option, compare the metric data of your service against its projected metric data.

type nonrec ecs_service_projected_metrics = ecs_service_projected_metric list

Describes the projected metrics of an Amazon ECS service recommendation option.

To determine the performance difference between your current Amazon ECS service and the recommended option, compare the metric data of your service against its projected metric data.

type nonrec get_ecs_service_recommendation_projected_metrics_response = {
  1. recommended_option_projected_metrics : ecs_service_recommended_option_projected_metrics option;
    (*

    An array of objects that describes the projected metrics.

    *)
}
type nonrec get_ecs_service_recommendation_projected_metrics_request = {
  1. end_time : timestamp;
    (*

    The timestamp of the last projected metrics data point to return.

    *)
  2. start_time : timestamp;
    (*

    The timestamp of the first projected metrics data point to return.

    *)
  3. period : period;
    (*

    The granularity, in seconds, of the projected metrics data points.

    *)
  4. stat : metric_statistic;
    (*

    The statistic of the projected metrics.

    *)
  5. service_arn : service_arn;
    (*

    The ARN that identifies the Amazon ECS service.

    The following is the format of the ARN:

    arn:aws:ecs:region:aws_account_id:service/cluster-name/service-name

    *)
}
type nonrec get_ec2_recommendation_projected_metrics_response = {
  1. recommended_option_projected_metrics : recommended_option_projected_metrics option;
    (*

    An array of objects that describes projected metrics.

    *)
}
type nonrec get_ec2_recommendation_projected_metrics_request = {
  1. recommendation_preferences : recommendation_preferences option;
    (*

    An object to specify the preferences for the Amazon EC2 recommendation projected metrics to return in the response.

    *)
  2. end_time : timestamp;
    (*

    The timestamp of the last projected metrics data point to return.

    *)
  3. start_time : timestamp;
    (*

    The timestamp of the first projected metrics data point to return.

    *)
  4. period : period;
    (*

    The granularity, in seconds, of the projected metrics data points.

    *)
  5. stat : metric_statistic;
    (*

    The statistic of the projected metrics.

    *)
  6. instance_arn : instance_arn;
    (*

    The Amazon Resource Name (ARN) of the instances for which to return recommendation projected metrics.

    *)
}
type nonrec get_ec2_instance_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    For example, an error is returned if you request recommendations for an instance of an unsupported instance family.

    *)
  2. instance_recommendations : instance_recommendations option;
    (*

    An array of objects that describe instance recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to use to advance to the next page of instance recommendations.

    This value is null when there are no more pages of instance recommendations to return.

    *)
}
type nonrec filter_name =
  1. | INFERRED_WORKLOAD_TYPES
  2. | RECOMMENDATION_SOURCE_TYPE
  3. | FINDING_REASON_CODES
  4. | FINDING
type nonrec filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values for this parameter are as follows, depending on what you specify for the name parameter and the resource type that you wish to filter results for:

    • Specify Optimized or NotOptimized if you specify the name parameter as Finding and you want to filter results for Auto Scaling groups.
    • Specify Underprovisioned, Overprovisioned, or Optimized if you specify the name parameter as Finding and you want to filter results for EC2 instances.
    • Specify Ec2Instance or AutoScalingGroup if you specify the name parameter as RecommendationSourceType.

    • Specify one of the following options if you specify the name parameter as FindingReasonCodes:

      • CPUOverprovisioned — The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload.
      • CPUUnderprovisioned — The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance.
      • MemoryOverprovisioned — The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload.
      • MemoryUnderprovisioned — The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance.
      • EBSThroughputOverprovisioned — The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload.
      • EBSThroughputUnderprovisioned — The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance.
      • EBSIOPSOverprovisioned — The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload.
      • EBSIOPSUnderprovisioned — The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance.
      • NetworkBandwidthOverprovisioned — The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload.
      • NetworkBandwidthUnderprovisioned — The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This finding reason happens when the NetworkIn or NetworkOut performance of an instance is impacted.
      • NetworkPPSOverprovisioned — The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload.
      • NetworkPPSUnderprovisioned — The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance.
      • DiskIOPSOverprovisioned — The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload.
      • DiskIOPSUnderprovisioned — The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance.
      • DiskThroughputOverprovisioned — The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload.
      • DiskThroughputUnderprovisioned — The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance.
    *)
  2. name : filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification. For example, Underprovisioned.

    Specify RecommendationSourceType to return recommendations of a specific resource type. For example, Ec2Instance.

    Specify FindingReasonCodes to return recommendations with a specific finding reason code. For example, CPUUnderprovisioned.

    Specify InferredWorkloadTypes to return recommendations of a specific inferred workload. For example, Redis.

    You can filter your EC2 instance recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your recommendations. Use this filter to find all of your recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of recommendations. Use this filter with the GetAutoScalingGroupRecommendations and GetEC2InstanceRecommendations actions.

You can use EBSFilter with the GetEBSVolumeRecommendations action, LambdaFunctionRecommendationFilter with the GetLambdaFunctionRecommendations action, and JobFilter with the DescribeRecommendationExportJobs action.

type nonrec filters = filter list
type nonrec get_ec2_instance_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
    (*

    An object to specify the preferences for the Amazon EC2 instance recommendations to return in the response.

    *)
  2. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return instance recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return instance recommendations.

    Only one account ID can be specified per request.

    *)
  3. filters : filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of instance recommendations.

    *)
  4. max_results : max_results option;
    (*

    The maximum number of instance recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  5. next_token : next_token option;
    (*

    The token to advance to the next page of instance recommendations.

    *)
  6. instance_arns : instance_arns option;
    (*

    The Amazon Resource Name (ARN) of the instances for which to return recommendations.

    *)
}
type nonrec get_ebs_volume_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    For example, an error is returned if you request recommendations for an unsupported volume.

    *)
  2. volume_recommendations : volume_recommendations option;
    (*

    An array of objects that describe volume recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to use to advance to the next page of volume recommendations.

    This value is null when there are no more pages of volume recommendations to return.

    *)
}
type nonrec ebs_filter_name =
  1. | FINDING
type nonrec ebs_filter = {
  1. values : filter_values option;
    (*

    The value of the filter.

    The valid values are Optimized, or NotOptimized.

    *)
  2. name : ebs_filter_name option;
    (*

    The name of the filter.

    Specify Finding to return recommendations with a specific finding classification (for example, NotOptimized).

    You can filter your Amazon EBS volume recommendations by tag:key and tag-key tags.

    A tag:key is a key and value combination of a tag assigned to your Amazon EBS volume recommendations. Use the tag key in the filter name and the tag value as the filter value. For example, to find all Amazon EBS volume recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    A tag-key is the key of a tag assigned to your Amazon EBS volume recommendations. Use this filter to find all of your Amazon EBS volume recommendations that have a tag with a specific key. This doesn’t consider the tag value. For example, you can find your Amazon EBS volume recommendations with a tag key value of Owner or without any tag keys assigned.

    *)
}

Describes a filter that returns a more specific list of Amazon Elastic Block Store (Amazon EBS) volume recommendations. Use this filter with the GetEBSVolumeRecommendations action.

You can use LambdaFunctionRecommendationFilter with the GetLambdaFunctionRecommendations action, JobFilter with the DescribeRecommendationExportJobs action, and Filter with the GetAutoScalingGroupRecommendations and GetEC2InstanceRecommendations actions.

type nonrec ebs_filters = ebs_filter list
type nonrec get_ebs_volume_recommendations_request = {
  1. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return volume recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return volume recommendations.

    Only one account ID can be specified per request.

    *)
  2. filters : ebs_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of volume recommendations.

    *)
  3. max_results : max_results option;
    (*

    The maximum number of volume recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  4. next_token : next_token option;
    (*

    The token to advance to the next page of volume recommendations.

    *)
  5. volume_arns : volume_arns option;
    (*

    The Amazon Resource Name (ARN) of the volumes for which to return recommendations.

    *)
}
type nonrec auto_scaling_group_arn = string
type nonrec auto_scaling_group_name = string
type nonrec desired_capacity = int
type nonrec allocation_strategy =
  1. | LOWEST_PRICE
  2. | PRIORITIZED
type nonrec asg_type =
  1. | MIXED_INSTANCE_TYPE
  2. | SINGLE_INSTANCE_TYPE
type nonrec auto_scaling_group_configuration = {
  1. mixed_instance_types : mixed_instance_types option;
    (*

    List the instance types within an EC2 Auto Scaling group that has mixed instance types.

    *)
  2. type_ : asg_type option;
    (*

    Describes whether the EC2 Auto Scaling group has a single instance type or a mixed instance type configuration.

    *)
  3. estimated_instance_hour_reduction_percentage : nullable_estimated_instance_hour_reduction_percentage option;
    (*

    Describes the projected percentage reduction in instance hours after adopting the recommended configuration. This field is only available for EC2 Auto Scaling groups with scaling policies.

    *)
  4. allocation_strategy : allocation_strategy option;
    (*

    Describes the allocation strategy that the EC2 Auto Scaling group uses. This field is only available for EC2 Auto Scaling groups with mixed instance types.

    *)
  5. instance_type : nullable_instance_type option;
    (*

    The instance type for the EC2 Auto Scaling group.

    *)
  6. max_size : max_size option;
    (*

    The maximum size, or maximum number of instances, for the EC2 Auto Scaling group.

    *)
  7. min_size : min_size option;
    (*

    The minimum size, or minimum number of instances, for the EC2 Auto Scaling group.

    *)
  8. desired_capacity : desired_capacity option;
    (*

    The desired capacity, or number of instances, for the EC2 Auto Scaling group.

    *)
}

Describes the configuration of an EC2 Auto Scaling group.

type nonrec auto_scaling_group_estimated_monthly_savings = {
  1. value : value option;
    (*

    The value of the estimated monthly savings.

    *)
  2. currency : currency option;
    (*

    The currency of the estimated monthly savings.

    *)
}

An object that describes the estimated monthly savings possible by adopting Compute Optimizer’s Auto Scaling group recommendations. This is based on the Savings Plans and Reserved Instances discounts.

type nonrec auto_scaling_group_savings_opportunity_after_discounts = {
  1. estimated_monthly_savings : auto_scaling_group_estimated_monthly_savings option;
    (*

    An object that describes the estimated monthly savings possible by adopting Compute Optimizer’s Auto Scaling group recommendations. This is based on the Savings Plans and Reserved Instances pricing discounts.

    *)
  2. savings_opportunity_percentage : savings_opportunity_percentage option;
    (*

    The estimated monthly savings possible as a percentage of monthly cost after applying the Savings Plans and Reserved Instances discounts. This saving can be achieved by adopting Compute Optimizer’s Auto Scaling group recommendations.

    *)
}

Describes the savings opportunity for Auto Scaling group recommendations after applying the Savings Plans and Reserved Instances discounts.

Savings opportunity represents the estimated monthly savings you can achieve by implementing Compute Optimizer recommendations.

type nonrec auto_scaling_group_recommendation_option = {
  1. migration_effort : migration_effort option;
    (*

    The level of effort required to migrate from the current instance type to the recommended instance type.

    For example, the migration effort is Low if Amazon EMR is the inferred workload type and an Amazon Web Services Graviton instance type is recommended. The migration effort is Medium if a workload type couldn't be inferred but an Amazon Web Services Graviton instance type is recommended. The migration effort is VeryLow if both the current and recommended instance types are of the same CPU architecture.

    *)
  2. savings_opportunity_after_discounts : auto_scaling_group_savings_opportunity_after_discounts option;
    (*

    An object that describes the savings opportunity for the Auto Scaling group recommendation option that includes Savings Plans and Reserved Instances discounts. Savings opportunity includes the estimated monthly savings and percentage.

    *)
  3. savings_opportunity : savings_opportunity option;
    (*

    An object that describes the savings opportunity for the Auto Scaling group recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage.

    *)
  4. rank : rank option;
    (*

    The rank of the Auto Scaling group recommendation option.

    The top recommendation option is ranked as 1.

    *)
  5. performance_risk : performance_risk option;
    (*

    The performance risk of the Auto Scaling group configuration recommendation.

    Performance risk indicates the likelihood of the recommended instance type not meeting the resource needs of your workload. Compute Optimizer calculates an individual performance risk score for each specification of the recommended instance, including CPU, memory, EBS throughput, EBS IOPS, disk throughput, disk IOPS, network throughput, and network PPS. The performance risk of the recommended instance is calculated as the maximum performance risk score across the analyzed resource specifications.

    The value ranges from 0 - 4, with 0 meaning that the recommended resource is predicted to always provide enough hardware capability. The higher the performance risk is, the more likely you should validate whether the recommendation will meet the performance requirements of your workload before migrating your resource.

    *)
  6. projected_utilization_metrics : projected_utilization_metrics option;
    (*

    An array of objects that describe the projected utilization metrics of the Auto Scaling group recommendation option.

    The Cpu and Memory metrics are the only projected utilization metrics returned. Additionally, the Memory metric is returned only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling Memory Utilization with the CloudWatch Agent.

    *)
  7. instance_gpu_info : gpu_info option;
    (*

    Describes the GPU accelerator settings for the recommended instance type of the Auto Scaling group.

    *)
  8. configuration : auto_scaling_group_configuration option;
    (*

    An array of objects that describe an Auto Scaling group configuration.

    *)
}

Describes a recommendation option for an Auto Scaling group.

type nonrec auto_scaling_group_recommendation_options = auto_scaling_group_recommendation_option list
type nonrec auto_scaling_group_recommendation = {
  1. inferred_workload_types : inferred_workload_types option;
    (*

    The applications that might be running on the instances in the Auto Scaling group as inferred by Compute Optimizer.

    Compute Optimizer can infer if one of the following applications might be running on the instances:

    • AmazonEmr - Infers that Amazon EMR might be running on the instances.
    • ApacheCassandra - Infers that Apache Cassandra might be running on the instances.
    • ApacheHadoop - Infers that Apache Hadoop might be running on the instances.
    • Memcached - Infers that Memcached might be running on the instances.
    • NGINX - Infers that NGINX might be running on the instances.
    • PostgreSql - Infers that PostgreSQL might be running on the instances.
    • Redis - Infers that Redis might be running on the instances.
    • Kafka - Infers that Kafka might be running on the instance.
    • SQLServer - Infers that SQLServer might be running on the instance.
    *)
  2. effective_recommendation_preferences : effective_recommendation_preferences option;
    (*

    An object that describes the effective recommendation preferences for the Auto Scaling group.

    *)
  3. current_performance_risk : current_performance_risk option;
    (*

    The risk of the current Auto Scaling group not meeting the performance needs of its workloads. The higher the risk, the more likely the current Auto Scaling group configuration has insufficient capacity and cannot meet workload requirements.

    *)
  4. last_refresh_timestamp : last_refresh_timestamp option;
    (*

    The timestamp of when the Auto Scaling group recommendation was last generated.

    *)
  5. recommendation_options : auto_scaling_group_recommendation_options option;
    (*

    An array of objects that describe the recommendation options for the Auto Scaling group.

    *)
  6. current_instance_gpu_info : gpu_info option;
    (*

    Describes the GPU accelerator settings for the current instance type of the Auto Scaling group.

    *)
  7. current_configuration : auto_scaling_group_configuration option;
    (*

    An array of objects that describe the current configuration of the Auto Scaling group.

    *)
  8. look_back_period_in_days : look_back_period_in_days option;
    (*

    The number of days for which utilization metrics were analyzed for the Auto Scaling group.

    *)
  9. utilization_metrics : utilization_metrics option;
    (*

    An array of objects that describe the utilization metrics of the Auto Scaling group.

    *)
  10. finding : finding option;
    (*

    The finding classification of the Auto Scaling group.

    Findings for Auto Scaling groups include:

    • NotOptimized—An Auto Scaling group is considered not optimized when Compute Optimizer identifies a recommendation that can provide better performance for your workload.
    • Optimized—An Auto Scaling group is considered optimized when Compute Optimizer determines that the group is correctly provisioned to run your workload based on the chosen instance type. For optimized resources, Compute Optimizer might recommend a new generation instance type.
    *)
  11. auto_scaling_group_name : auto_scaling_group_name option;
    (*

    The name of the Auto Scaling group.

    *)
  12. auto_scaling_group_arn : auto_scaling_group_arn option;
    (*

    The Amazon Resource Name (ARN) of the Auto Scaling group.

    *)
  13. account_id : account_id option;
    (*

    The Amazon Web Services account ID of the Auto Scaling group.

    *)
}

Describes an Auto Scaling group recommendation.

type nonrec auto_scaling_group_recommendations = auto_scaling_group_recommendation list
type nonrec get_auto_scaling_group_recommendations_response = {
  1. errors : get_recommendation_errors option;
    (*

    An array of objects that describe errors of the request.

    For example, an error is returned if you request recommendations for an unsupported Auto Scaling group.

    *)
  2. auto_scaling_group_recommendations : auto_scaling_group_recommendations option;
    (*

    An array of objects that describe Auto Scaling group recommendations.

    *)
  3. next_token : next_token option;
    (*

    The token to use to advance to the next page of Auto Scaling group recommendations.

    This value is null when there are no more pages of Auto Scaling group recommendations to return.

    *)
}
type nonrec auto_scaling_group_arns = auto_scaling_group_arn list
type nonrec get_auto_scaling_group_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
    (*

    An object to specify the preferences for the Auto Scaling group recommendations to return in the response.

    *)
  2. filters : filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of Auto Scaling group recommendations.

    *)
  3. max_results : max_results option;
    (*

    The maximum number of Auto Scaling group recommendations to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  4. next_token : next_token option;
    (*

    The token to advance to the next page of Auto Scaling group recommendations.

    *)
  5. auto_scaling_group_arns : auto_scaling_group_arns option;
    (*

    The Amazon Resource Name (ARN) of the Auto Scaling groups for which to return recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The ID of the Amazon Web Services account for which to return Auto Scaling group recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to return Auto Scaling group recommendations.

    Only one account ID can be specified per request.

    *)
}
type nonrec file_format =
  1. | CSV
type nonrec exportable_volume_field =
  1. | EFFECTIVE_RECOMMENDATION_PREFERENCES_LOOKBACK_PERIOD
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  3. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  4. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  5. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  6. | CURRENT_CONFIGURATION_ROOT_VOLUME
  7. | ROOT_VOLUME
  8. | TAGS
  9. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  10. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  11. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  12. | CURRENT_PERFORMANCE_RISK
  13. | LAST_REFRESH_TIMESTAMP
  14. | RECOMMENDATION_OPTIONS_PERFORMANCE_RISK
  15. | RECOMMENDATION_OPTIONS_MONTHLY_PRICE
  16. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_SIZE
  17. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_BURST_THROUGHPUT
  18. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_BURST_IOPS
  19. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_BASELINE_THROUGHPUT
  20. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_BASELINE_IOPS
  21. | RECOMMENDATION_OPTIONS_CONFIGURATION_VOLUME_TYPE
  22. | CURRENT_MONTHLY_PRICE
  23. | CURRENT_CONFIGURATION_VOLUME_SIZE
  24. | CURRENT_CONFIGURATION_VOLUME_BURST_THROUGHPUT
  25. | CURRENT_CONFIGURATION_VOLUME_BURST_IOPS
  26. | CURRENT_CONFIGURATION_VOLUME_BASELINE_THROUGHPUT
  27. | CURRENT_CONFIGURATION_VOLUME_BASELINE_IOPS
  28. | CURRENT_CONFIGURATION_VOLUME_TYPE
  29. | LOOKBACK_PERIOD_IN_DAYS
  30. | UTILIZATION_METRICS_VOLUME_THROUGHPUT_EXCEEDED_MAXIMUM
  31. | UTILIZATION_METRICS_VOLUME_IOPS_EXCEEDED_MAXIMUM
  32. | UTILIZATION_METRICS_VOLUME_WRITE_BYTES_PER_SECOND_MAXIMUM
  33. | UTILIZATION_METRICS_VOLUME_READ_BYTES_PER_SECOND_MAXIMUM
  34. | UTILIZATION_METRICS_VOLUME_WRITE_OPS_PER_SECOND_MAXIMUM
  35. | UTILIZATION_METRICS_VOLUME_READ_OPS_PER_SECOND_MAXIMUM
  36. | FINDING
  37. | VOLUME_ARN
  38. | ACCOUNT_ID
type nonrec exportable_volume_fields = exportable_volume_field list
type nonrec exportable_rdsdb_field =
  1. | PROMOTION_TIER
  2. | DB_CLUSTER_IDENTIFIER
  3. | TAGS
  4. | LAST_REFRESH_TIMESTAMP
  5. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  6. | EFFECTIVE_RECOMMENDATION_PREFERENCES_LOOKBACK_PERIOD
  7. | EFFECTIVE_RECOMMENDATION_PREFERENCES_ENHANCED_INFRASTRUCTURE_METRICS
  8. | EFFECTIVE_RECOMMENDATION_PREFERENCES_CPU_VENDOR_ARCHITECTURES
  9. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  10. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  11. | STORAGE_RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  12. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  13. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  14. | STORAGE_RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  15. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_CLUSTER_STORAGE_IO_ON_DEMAND_MONTHLY_COST
  16. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_CLUSTER_STORAGE_ON_DEMAND_MONTHLY_COST
  17. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_CLUSTER_INSTANCE_ON_DEMAND_MONTHLY_COST
  18. | STORAGE_RECOMMENDATION_OPTIONS_ON_DEMAND_MONTHLY_PRICE
  19. | INSTANCE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  20. | INSTANCE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  21. | INSTANCE_RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  22. | INSTANCE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  23. | INSTANCE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  24. | INSTANCE_RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  25. | INSTANCE_RECOMMENDATION_OPTIONS_INSTANCE_ON_DEMAND_HOURLY_PRICE
  26. | STORAGE_RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_VOLUME_IOPS_COST_VARIATION
  27. | STORAGE_RECOMMENDATION_OPTIONS_RANK
  28. | STORAGE_RECOMMENDATION_OPTIONS_STORAGE_THROUGHPUT
  29. | STORAGE_RECOMMENDATION_OPTIONS_IOPS
  30. | STORAGE_RECOMMENDATION_OPTIONS_MAX_ALLOCATED_STORAGE
  31. | STORAGE_RECOMMENDATION_OPTIONS_ALLOCATED_STORAGE
  32. | STORAGE_RECOMMENDATION_OPTIONS_STORAGE_TYPE
  33. | INSTANCE_RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_CPU_MAXIMUM
  34. | INSTANCE_RECOMMENDATION_OPTIONS_PERFORMANCE_RISK
  35. | INSTANCE_RECOMMENDATION_OPTIONS_RANK
  36. | INSTANCE_RECOMMENDATION_OPTIONS_DB_INSTANCE_CLASS
  37. | STORAGE_FINDING_REASON_CODES
  38. | STORAGE_FINDING
  39. | INSTANCE_FINDING_REASON_CODES
  40. | INSTANCE_FINDING
  41. | UTILIZATION_METRICS_VOLUME_WRITE_IOPS_AVERAGE
  42. | UTILIZATION_METRICS_VOLUME_READ_IOPS_AVERAGE
  43. | UTILIZATION_METRICS_VOLUME_BYTES_USED_AVERAGE
  44. | UTILIZATION_METRICS_WRITE_IOPS_EPHEMERAL_STORAGE_MAXIMUM
  45. | UTILIZATION_METRICS_READ_IOPS_EPHEMERAL_STORAGE_MAXIMUM
  46. | UTILIZATION_METRICS_AURORA_MEMORY_NUM_KILL_QUERY_TOTAL_MAXIMUM
  47. | UTILIZATION_METRICS_AURORA_MEMORY_NUM_KILL_CONN_TOTAL_MAXIMUM
  48. | UTILIZATION_METRICS_AURORA_MEMORY_NUM_DECLINED_SQL_TOTAL_MAXIMUM
  49. | UTILIZATION_METRICS_AURORA_MEMORY_HEALTH_STATE_MAXIMUM
  50. | UTILIZATION_METRICS_STORAGE_NETWORK_TRANSMIT_THROUGHPUT_MAXIMUM
  51. | UTILIZATION_METRICS_STORAGE_NETWORK_RECEIVE_THROUGHPUT_MAXIMUM
  52. | UTILIZATION_METRICS_DATABASE_CONNECTIONS_MAXIMUM
  53. | UTILIZATION_METRICS_EBS_VOLUME_WRITE_THROUGHPUT_MAXIMUM
  54. | UTILIZATION_METRICS_EBS_VOLUME_READ_THROUGHPUT_MAXIMUM
  55. | UTILIZATION_METRICS_EBS_VOLUME_WRITE_IOPS_MAXIMUM
  56. | UTILIZATION_METRICS_EBS_VOLUME_READ_IOPS_MAXIMUM
  57. | UTILIZATION_METRICS_NETWORK_TRANSMIT_THROUGHPUT_MAXIMUM
  58. | UTILIZATION_METRICS_NETWORK_RECEIVE_THROUGHPUT_MAXIMUM
  59. | UTILIZATION_METRICS_EBS_VOLUME_STORAGE_SPACE_UTILIZATION_MAXIMUM
  60. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  61. | UTILIZATION_METRICS_CPU_MAXIMUM
  62. | CURRENT_INSTANCE_PERFORMANCE_RISK
  63. | CURRENT_STORAGE_ESTIMATED_CLUSTER_STORAGE_IO_ON_DEMAND_MONTHLY_COST
  64. | CURRENT_STORAGE_ESTIMATED_CLUSTER_STORAGE_ON_DEMAND_MONTHLY_COST
  65. | CURRENT_STORAGE_ESTIMATED_CLUSTER_INSTANCE_ON_DEMAND_MONTHLY_COST
  66. | LOOKBACK_PERIOD_IN_DAYS
  67. | CURRENT_STORAGE_ON_DEMAND_MONTHLY_PRICE
  68. | CURRENT_INSTANCE_ON_DEMAND_HOURLY_PRICE
  69. | CURRENT_STORAGE_ESTIMATED_MONTHLY_VOLUME_IOPS_COST_VARIATION
  70. | CURRENT_STORAGE_CONFIGURATION_STORAGE_THROUGHPUT
  71. | CURRENT_STORAGE_CONFIGURATION_IOPS
  72. | CURRENT_STORAGE_CONFIGURATION_MAX_ALLOCATED_STORAGE
  73. | CURRENT_STORAGE_CONFIGURATION_ALLOCATED_STORAGE
  74. | CURRENT_STORAGE_CONFIGURATION_STORAGE_TYPE
  75. | CURRENT_DB_INSTANCE_CLASS
  76. | CLUSTER_WRITER
  77. | MULTI_AZ_DB_INSTANCE
  78. | IDLE
  79. | ENGINE_VERSION
  80. | ENGINE
  81. | ACCOUNT_ID
  82. | RESOURCE_ARN
type nonrec exportable_rdsdb_fields = exportable_rdsdb_field list
type nonrec exportable_license_field =
  1. | TAGS
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  3. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  4. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  5. | RECOMMENDATION_OPTIONS_LICENSE_MODEL
  6. | RECOMMENDATION_OPTIONS_LICENSE_EDITION
  7. | RECOMMENDATION_OPTIONS_OPERATING_SYSTEM
  8. | CURRENT_LICENSE_CONFIGURATION_METRICS_SOURCE
  9. | CURRENT_LICENSE_CONFIGURATION_LICENSE_VERSION
  10. | CURRENT_LICENSE_CONFIGURATION_LICENSE_MODEL
  11. | CURRENT_LICENSE_CONFIGURATION_LICENSE_EDITION
  12. | CURRENT_LICENSE_CONFIGURATION_LICENSE_NAME
  13. | CURRENT_LICENSE_CONFIGURATION_OPERATING_SYSTEM
  14. | CURRENT_LICENSE_CONFIGURATION_INSTANCE_TYPE
  15. | CURRENT_LICENSE_CONFIGURATION_NUMBER_OF_CORES
  16. | LICENSE_FINDING_REASON_CODES
  17. | LICENSE_FINDING
  18. | LAST_REFRESH_TIMESTAMP
  19. | LOOKBACK_PERIOD_IN_DAYS
  20. | RESOURCE_ARN
  21. | ACCOUNT_ID
type nonrec exportable_license_fields = exportable_license_field list
type nonrec exportable_lambda_function_field =
  1. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  3. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  4. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  5. | TAGS
  6. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  7. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  8. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  9. | CURRENT_PERFORMANCE_RISK
  10. | LAST_REFRESH_TIMESTAMP
  11. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_DURATION_EXPECTED
  12. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_DURATION_UPPER_BOUND
  13. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_DURATION_LOWER_BOUND
  14. | RECOMMENDATION_OPTIONS_COST_HIGH
  15. | RECOMMENDATION_OPTIONS_COST_LOW
  16. | RECOMMENDATION_OPTIONS_CONFIGURATION_MEMORY_SIZE
  17. | CURRENT_COST_AVERAGE
  18. | CURRENT_COST_TOTAL
  19. | CURRENT_CONFIGURATION_TIMEOUT
  20. | CURRENT_CONFIGURATION_MEMORY_SIZE
  21. | LOOKBACK_PERIOD_IN_DAYS
  22. | UTILIZATION_METRICS_MEMORY_AVERAGE
  23. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  24. | UTILIZATION_METRICS_DURATION_AVERAGE
  25. | UTILIZATION_METRICS_DURATION_MAXIMUM
  26. | NUMBER_OF_INVOCATIONS
  27. | FINDING_REASON_CODES
  28. | FINDING
  29. | FUNCTION_VERSION
  30. | FUNCTION_ARN
  31. | ACCOUNT_ID
type nonrec exportable_lambda_function_fields = exportable_lambda_function_field list
type nonrec exportable_instance_field =
  1. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  3. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  4. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  5. | EFFECTIVE_RECOMMENDATION_PREFERENCES_UTILIZATION_PREFERENCES
  6. | EFFECTIVE_RECOMMENDATION_PREFERENCES_LOOKBACK_PERIOD
  7. | EFFECTIVE_RECOMMENDATION_PREFERENCES_PREFERRED_RESOURCES
  8. | IDLE
  9. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_GPU_MEMORY_PERCENTAGE_MAXIMUM
  10. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_GPU_PERCENTAGE_MAXIMUM
  11. | UTILIZATION_METRICS_GPU_MEMORY_PERCENTAGE_MAXIMUM
  12. | UTILIZATION_METRICS_GPU_PERCENTAGE_MAXIMUM
  13. | RECOMMENDATION_OPTIONS_INSTANCE_GPU_INFO
  14. | CURRENT_INSTANCE_GPU_INFO
  15. | EXTERNAL_METRIC_STATUS_REASON
  16. | EXTERNAL_METRIC_STATUS_CODE
  17. | INSTANCE_STATE
  18. | TAGS
  19. | EFFECTIVE_RECOMMENDATION_PREFERENCES_EXTERNAL_METRICS_SOURCE
  20. | RECOMMENDATION_OPTIONS_MIGRATION_EFFORT
  21. | INFERRED_WORKLOAD_TYPES
  22. | EFFECTIVE_RECOMMENDATION_PREFERENCES_INFERRED_WORKLOAD_TYPES
  23. | EFFECTIVE_RECOMMENDATION_PREFERENCES_ENHANCED_INFRASTRUCTURE_METRICS
  24. | EFFECTIVE_RECOMMENDATION_PREFERENCES_CPU_VENDOR_ARCHITECTURES
  25. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  26. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  27. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  28. | CURRENT_PERFORMANCE_RISK
  29. | LAST_REFRESH_TIMESTAMP
  30. | RECOMMENDATIONS_SOURCES_RECOMMENDATION_SOURCE_TYPE
  31. | RECOMMENDATIONS_SOURCES_RECOMMENDATION_SOURCE_ARN
  32. | RECOMMENDATION_OPTIONS_STANDARD_THREE_YEAR_NO_UPFRONT_RESERVED_PRICE
  33. | RECOMMENDATION_OPTIONS_STANDARD_ONE_YEAR_NO_UPFRONT_RESERVED_PRICE
  34. | RECOMMENDATION_OPTIONS_ON_DEMAND_PRICE
  35. | RECOMMENDATION_OPTIONS_NETWORK
  36. | RECOMMENDATION_OPTIONS_STORAGE
  37. | RECOMMENDATION_OPTIONS_MEMORY
  38. | RECOMMENDATION_OPTIONS_VCPUS
  39. | RECOMMENDATION_OPTIONS_PERFORMANCE_RISK
  40. | RECOMMENDATION_OPTIONS_PLATFORM_DIFFERENCES
  41. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_MEMORY_MAXIMUM
  42. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_CPU_MAXIMUM
  43. | RECOMMENDATION_OPTIONS_INSTANCE_TYPE
  44. | CURRENT_NETWORK
  45. | CURRENT_STORAGE
  46. | CURRENT_MEMORY
  47. | CURRENT_VCPUS
  48. | CURRENT_STANDARD_THREE_YEAR_NO_UPFRONT_RESERVED_PRICE
  49. | CURRENT_STANDARD_ONE_YEAR_NO_UPFRONT_RESERVED_PRICE
  50. | CURRENT_ON_DEMAND_PRICE
  51. | UTILIZATION_METRICS_NETWORK_PACKETS_OUT_PER_SECOND_MAXIMUM
  52. | UTILIZATION_METRICS_NETWORK_PACKETS_IN_PER_SECOND_MAXIMUM
  53. | UTILIZATION_METRICS_NETWORK_OUT_BYTES_PER_SECOND_MAXIMUM
  54. | UTILIZATION_METRICS_NETWORK_IN_BYTES_PER_SECOND_MAXIMUM
  55. | UTILIZATION_METRICS_DISK_WRITE_BYTES_PER_SECOND_MAXIMUM
  56. | UTILIZATION_METRICS_DISK_READ_BYTES_PER_SECOND_MAXIMUM
  57. | UTILIZATION_METRICS_DISK_WRITE_OPS_PER_SECOND_MAXIMUM
  58. | UTILIZATION_METRICS_DISK_READ_OPS_PER_SECOND_MAXIMUM
  59. | UTILIZATION_METRICS_EBS_WRITE_BYTES_PER_SECOND_MAXIMUM
  60. | UTILIZATION_METRICS_EBS_READ_BYTES_PER_SECOND_MAXIMUM
  61. | UTILIZATION_METRICS_EBS_WRITE_OPS_PER_SECOND_MAXIMUM
  62. | UTILIZATION_METRICS_EBS_READ_OPS_PER_SECOND_MAXIMUM
  63. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  64. | UTILIZATION_METRICS_CPU_MAXIMUM
  65. | CURRENT_INSTANCE_TYPE
  66. | LOOKBACK_PERIOD_IN_DAYS
  67. | Finding_Reason_Codes
  68. | FINDING
  69. | INSTANCE_NAME
  70. | INSTANCE_ARN
  71. | ACCOUNT_ID
type nonrec exportable_instance_fields = exportable_instance_field list
type nonrec exportable_idle_field =
  1. | TAGS
  2. | FINDING_DESCRIPTION
  3. | FINDING
  4. | UTILIZATION_METRICS_DATABASE_CONNECTIONS_SUM
  5. | UTILIZATION_METRICS_CURR_CONNECTIONS_SUM
  6. | UTILIZATION_METRICS_ELASTI_CACHE_PROCESSING_UNITS_SUM
  7. | UTILIZATION_METRICS_SET_TYPE_CMDS_SUM
  8. | UTILIZATION_METRICS_GET_TYPE_CMDS_SUM
  9. | UTILIZATION_METRICS_INVOCATIONS_SUM
  10. | UTILIZATION_METRICS_USER_CONNECTED_SUM
  11. | UTILIZATION_METRICS_IS_IDLE_MINIMUM
  12. | UTILIZATION_METRICS_KEYSPACE_MISSES_SUM
  13. | UTILIZATION_METRICS_KEYSPACE_HITS_SUM
  14. | UTILIZATION_METRICS_CACHE_MISSES_SUM
  15. | UTILIZATION_METRICS_CACHE_HITS_SUM
  16. | UTILIZATION_METRICS_ENGINE_CPU_UTILIZATION_MAXIMUM
  17. | UTILIZATION_METRICS_NEW_CONNECTIONS_SUM
  18. | UTILIZATION_METRICS_CONSUMED_WRITE_CAPACITY_UNITS_SUM
  19. | UTILIZATION_METRICS_CONSUMED_READ_CAPACITY_UNITS_SUM
  20. | UTILIZATION_METRICS_PACKETS_IN_FROM_DESTINATION_MAXIMUM
  21. | UTILIZATION_METRICS_PACKETS_IN_FROM_SOURCE_MAXIMUM
  22. | UTILIZATION_METRICS_ACTIVE_CONNECTION_COUNT_MAXIMUM
  23. | UTILIZATION_METRICS_VOLUME_WRITE_OPS_PER_SECOND_MAXIMUM
  24. | UTILIZATION_METRICS_VOLUME_READ_OPS_PER_SECOND_MAXIMUM
  25. | UTILIZATION_METRICS_EBS_VOLUME_WRITE_IOPS_MAXIMUM
  26. | UTILIZATION_METRICS_EBS_VOLUME_READ_IOPS_MAXIMUM
  27. | UTILIZATION_METRICS_DATABASE_CONNECTIONS_MAXIMUM
  28. | UTILIZATION_METRICS_NETWORK_IN_BYTES_PER_SECOND_MAXIMUM
  29. | UTILIZATION_METRICS_NETWORK_OUT_BYTES_PER_SECOND_MAXIMUM
  30. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  31. | UTILIZATION_METRICS_CPU_MAXIMUM
  32. | SAVINGS_OPPORTUNITY_AFTER_DISCOUNT
  33. | SAVINGS_OPPORTUNITY
  34. | LOOKBACK_PERIOD_IN_DAYS
  35. | LAST_REFRESH_TIMESTAMP
  36. | RESOURCE_TYPE
  37. | RESOURCE_ID
  38. | RESOURCE_ARN
  39. | ACCOUNT_ID
type nonrec exportable_idle_fields = exportable_idle_field list
type nonrec exportable_ecs_service_field =
  1. | EFFECTIVE_RECOMMENDATION_PREFERENCES_LOOKBACK_PERIOD
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  3. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  4. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  5. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  6. | TAGS
  7. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_MEMORY_MAXIMUM
  8. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_CPU_MAXIMUM
  9. | RECOMMENDATION_OPTIONS_CONTAINER_RECOMMENDATIONS
  10. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  11. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  12. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  13. | RECOMMENDATION_OPTIONS_CPU
  14. | RECOMMENDATION_OPTIONS_MEMORY
  15. | FINDING_REASON_CODES
  16. | FINDING
  17. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  18. | UTILIZATION_METRICS_CPU_MAXIMUM
  19. | CURRENT_SERVICE_CONTAINER_CONFIGURATIONS
  20. | CURRENT_SERVICE_CONFIGURATION_AUTO_SCALING_CONFIGURATION
  21. | CURRENT_SERVICE_CONFIGURATION_TASK_DEFINITION_ARN
  22. | CURRENT_SERVICE_CONFIGURATION_CPU
  23. | CURRENT_SERVICE_CONFIGURATION_MEMORY
  24. | CURRENT_PERFORMANCE_RISK
  25. | LAUNCH_TYPE
  26. | LAST_REFRESH_TIMESTAMP
  27. | LOOKBACK_PERIOD_IN_DAYS
  28. | SERVICE_ARN
  29. | ACCOUNT_ID
type nonrec exportable_ecs_service_fields = exportable_ecs_service_field list
type nonrec exportable_auto_scaling_group_field =
  1. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE_AFTER_DISCOUNTS
  2. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY_AFTER_DISCOUNTS
  3. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_AFTER_DISCOUNTS_PERCENTAGE
  4. | EFFECTIVE_RECOMMENDATION_PREFERENCES_SAVINGS_ESTIMATION_MODE
  5. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_GPU_MEMORY_MAXIMUM
  6. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_GPU_MAXIMUM
  7. | UTILIZATION_METRICS_GPU_MEMORY_PERCENTAGE_MAXIMUM
  8. | UTILIZATION_METRICS_GPU_PERCENTAGE_MAXIMUM
  9. | RECOMMENDATION_OPTIONS_INSTANCE_GPU_INFO
  10. | CURRENT_INSTANCE_GPU_INFO
  11. | RECOMMENDATION_OPTIONS_MIGRATION_EFFORT
  12. | INFERRED_WORKLOAD_TYPES
  13. | EFFECTIVE_RECOMMENDATION_PREFERENCES_LOOKBACK_PERIOD
  14. | EFFECTIVE_RECOMMENDATION_PREFERENCES_PREFERRED_RESOURCES
  15. | EFFECTIVE_RECOMMENDATION_PREFERENCES_INFERRED_WORKLOAD_TYPES
  16. | EFFECTIVE_RECOMMENDATION_PREFERENCES_ENHANCED_INFRASTRUCTURE_METRICS
  17. | EFFECTIVE_RECOMMENDATION_PREFERENCES_CPU_VENDOR_ARCHITECTURES
  18. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_VALUE
  19. | RECOMMENDATION_OPTIONS_ESTIMATED_MONTHLY_SAVINGS_CURRENCY
  20. | RECOMMENDATION_OPTIONS_SAVINGS_OPPORTUNITY_PERCENTAGE
  21. | CURRENT_PERFORMANCE_RISK
  22. | LAST_REFRESH_TIMESTAMP
  23. | RECOMMENDATION_OPTIONS_NETWORK
  24. | RECOMMENDATION_OPTIONS_STORAGE
  25. | RECOMMENDATION_OPTIONS_MEMORY
  26. | RECOMMENDATION_OPTIONS_VCPUS
  27. | RECOMMENDATION_OPTIONS_STANDARD_THREE_YEAR_NO_UPFRONT_RESERVED_PRICE
  28. | RECOMMENDATION_OPTIONS_STANDARD_ONE_YEAR_NO_UPFRONT_RESERVED_PRICE
  29. | RECOMMENDATION_OPTIONS_ON_DEMAND_PRICE
  30. | RECOMMENDATION_OPTIONS_PERFORMANCE_RISK
  31. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_MEMORY_MAXIMUM
  32. | RECOMMENDATION_OPTIONS_PROJECTED_UTILIZATION_METRICS_CPU_MAXIMUM
  33. | RECOMMENDATION_OPTIONS_CONFIGURATION_TYPE
  34. | RECOMMENDATION_OPTIONS_CONFIGURATION_MIXED_INSTANCE_TYPES
  35. | RECOMMENDATION_OPTIONS_CONFIGURATION_ALLOCATION_STRATEGY
  36. | RECOMMENDATION_OPTIONS_CONFIGURATION_ESTIMATED_INSTANCE_HOUR_REDUCTION_PERCENTAGE
  37. | RECOMMENDATION_OPTIONS_CONFIGURATION_MAX_SIZE
  38. | RECOMMENDATION_OPTIONS_CONFIGURATION_MIN_SIZE
  39. | RECOMMENDATION_OPTIONS_CONFIGURATION_DESIRED_CAPACITY
  40. | RECOMMENDATION_OPTIONS_CONFIGURATION_INSTANCE_TYPE
  41. | CURRENT_NETWORK
  42. | CURRENT_STORAGE
  43. | CURRENT_MEMORY
  44. | CURRENT_VCPUS
  45. | CURRENT_STANDARD_THREE_YEAR_NO_UPFRONT_RESERVED_PRICE
  46. | CURRENT_STANDARD_ONE_YEAR_NO_UPFRONT_RESERVED_PRICE
  47. | CURRENT_ON_DEMAND_PRICE
  48. | CURRENT_CONFIGURATION_TYPE
  49. | CURRENT_CONFIGURATION_MIXED_INSTANCE_TYPES
  50. | CURRENT_CONFIGURATION_ALLOCATION_STRATEGY
  51. | CURRENT_CONFIGURATION_MAX_SIZE
  52. | CURRENT_CONFIGURATION_MIN_SIZE
  53. | CURRENT_CONFIGURATION_DESIRED_CAPACITY
  54. | CURRENT_CONFIGURATION_INSTANCE_TYPE
  55. | LOOKBACK_PERIOD_IN_DAYS
  56. | UTILIZATION_METRICS_NETWORK_PACKETS_OUT_PER_SECOND_MAXIMUM
  57. | UTILIZATION_METRICS_NETWORK_PACKETS_IN_PER_SECOND_MAXIMUM
  58. | UTILIZATION_METRICS_NETWORK_OUT_BYTES_PER_SECOND_MAXIMUM
  59. | UTILIZATION_METRICS_NETWORK_IN_BYTES_PER_SECOND_MAXIMUM
  60. | UTILIZATION_METRICS_DISK_WRITE_BYTES_PER_SECOND_MAXIMUM
  61. | UTILIZATION_METRICS_DISK_READ_BYTES_PER_SECOND_MAXIMUM
  62. | UTILIZATION_METRICS_DISK_WRITE_OPS_PER_SECOND_MAXIMUM
  63. | UTILIZATION_METRICS_DISK_READ_OPS_PER_SECOND_MAXIMUM
  64. | UTILIZATION_METRICS_EBS_WRITE_BYTES_PER_SECOND_MAXIMUM
  65. | UTILIZATION_METRICS_EBS_READ_BYTES_PER_SECOND_MAXIMUM
  66. | UTILIZATION_METRICS_EBS_WRITE_OPS_PER_SECOND_MAXIMUM
  67. | UTILIZATION_METRICS_EBS_READ_OPS_PER_SECOND_MAXIMUM
  68. | UTILIZATION_METRICS_MEMORY_MAXIMUM
  69. | UTILIZATION_METRICS_CPU_MAXIMUM
  70. | FINDING
  71. | AUTO_SCALING_GROUP_NAME
  72. | AUTO_SCALING_GROUP_ARN
  73. | ACCOUNT_ID
type nonrec exportable_auto_scaling_group_fields = exportable_auto_scaling_group_field list
type nonrec export_rds_database_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    To view the status of an export job, use the DescribeRecommendationExportJobs action and specify the job ID.

    *)
}
type nonrec export_rds_database_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
  2. include_member_accounts : include_member_accounts option;
    (*

    If your account is the management account or the delegated administrator of an organization, this parameter indicates whether to include recommendations for resources in all member accounts of the organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    If this parameter is omitted, recommendations for member accounts of the organization aren't included in the export file.

    If this parameter or the account ID parameter is omitted, recommendations for member accounts aren't included in the export.

    *)
  3. file_format : file_format option;
    (*

    The format of the export file.

    The CSV file is the only export file format currently supported.

    *)
  4. s3_destination_config : s3_destination_config;
  5. fields_to_export : exportable_rdsdb_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  6. filters : rdsdb_recommendation_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of Amazon Aurora and RDS recommendations.

    *)
  7. account_ids : account_ids option;
    (*

    The Amazon Web Services account IDs for the export Amazon Aurora and RDS database recommendations.

    If your account is the management account or the delegated administrator of an organization, use this parameter to specify the member account you want to export recommendations to.

    This parameter can't be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    If this parameter or the include member accounts parameter is omitted, the recommendations for member accounts aren't included in the export.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_license_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    To view the status of an export job, use the DescribeRecommendationExportJobs action and specify the job ID.

    *)
}
type nonrec export_license_recommendations_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to include recommendations for resources in all member accounts of the organization if your account is the management account of an organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    If this parameter is omitted, recommendations for member accounts of the organization aren't included in the export file .

    This parameter cannot be specified together with the account IDs parameter. The parameters are mutually exclusive.

    *)
  2. file_format : file_format option;
    (*

    The format of the export file.

    A CSV file is the only export format currently supported.

    *)
  3. s3_destination_config : s3_destination_config;
  4. fields_to_export : exportable_license_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  5. filters : license_recommendation_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of license recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The IDs of the Amazon Web Services accounts for which to export license recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to export recommendations.

    This parameter can't be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    If this parameter is omitted, recommendations for member accounts aren't included in the export.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_lambda_function_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    Use the DescribeRecommendationExportJobs action, and specify the job ID to view the status of an export job.

    *)
}
type nonrec export_lambda_function_recommendations_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to include recommendations for resources in all member accounts of the organization if your account is the management account of an organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    Recommendations for member accounts of the organization are not included in the export file if this parameter is omitted.

    This parameter cannot be specified together with the account IDs parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the account IDs parameter, is omitted.

    *)
  2. file_format : file_format option;
    (*

    The format of the export file.

    The only export file format currently supported is Csv.

    *)
  3. s3_destination_config : s3_destination_config;
  4. fields_to_export : exportable_lambda_function_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  5. filters : lambda_function_recommendation_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of Lambda function recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The IDs of the Amazon Web Services accounts for which to export Lambda function recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to export recommendations.

    This parameter cannot be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the include member accounts parameter, is omitted.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_idle_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    To view the status of an export job, use the DescribeRecommendationExportJobs action and specify the job ID.

    *)
}
type nonrec export_idle_recommendations_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    If your account is the management account or the delegated administrator of an organization, this parameter indicates whether to include recommendations for resources in all member accounts of the organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    If this parameter is omitted, recommendations for member accounts of the organization aren't included in the export file.

    If this parameter or the account ID parameter is omitted, recommendations for member accounts aren't included in the export.

    *)
  2. file_format : file_format option;
    (*

    The format of the export file. The CSV file is the only export file format currently supported.

    *)
  3. s3_destination_config : s3_destination_config;
  4. fields_to_export : exportable_idle_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  5. filters : idle_recommendation_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of idle resource recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The Amazon Web Services account IDs for the export idle resource recommendations.

    If your account is the management account or the delegated administrator of an organization, use this parameter to specify the member account you want to export recommendations to.

    This parameter can't be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    If this parameter or the include member accounts parameter is omitted, the recommendations for member accounts aren't included in the export.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_ecs_service_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    To view the status of an export job, use the DescribeRecommendationExportJobs action and specify the job ID.

    *)
}
type nonrec export_ecs_service_recommendations_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    If your account is the management account or the delegated administrator of an organization, this parameter indicates whether to include recommendations for resources in all member accounts of the organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    If this parameter is omitted, recommendations for member accounts of the organization aren't included in the export file.

    If this parameter or the account ID parameter is omitted, recommendations for member accounts aren't included in the export.

    *)
  2. file_format : file_format option;
    (*

    The format of the export file.

    The CSV file is the only export file format currently supported.

    *)
  3. s3_destination_config : s3_destination_config;
  4. fields_to_export : exportable_ecs_service_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  5. filters : ecs_service_recommendation_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of Amazon ECS service recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The Amazon Web Services account IDs for the export Amazon ECS service recommendations.

    If your account is the management account or the delegated administrator of an organization, use this parameter to specify the member account you want to export recommendations to.

    This parameter can't be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    If this parameter or the include member accounts parameter is omitted, the recommendations for member accounts aren't included in the export.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_ec2_instance_recommendations_response = {
  1. s3_destination : s3_destination option;
    (*

    An object that describes the destination Amazon S3 bucket of a recommendations export file.

    *)
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    Use the DescribeRecommendationExportJobs action, and specify the job ID to view the status of an export job.

    *)
}
type nonrec export_ec2_instance_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
    (*

    An object to specify the preferences for the Amazon EC2 instance recommendations to export.

    *)
  2. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to include recommendations for resources in all member accounts of the organization if your account is the management account of an organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    Recommendations for member accounts of the organization are not included in the export file if this parameter is omitted.

    Recommendations for member accounts are not included in the export if this parameter, or the account IDs parameter, is omitted.

    *)
  3. file_format : file_format option;
    (*

    The format of the export file.

    The only export file format currently supported is Csv.

    *)
  4. s3_destination_config : s3_destination_config;
    (*

    An object to specify the destination Amazon Simple Storage Service (Amazon S3) bucket name and key prefix for the export job.

    You must create the destination Amazon S3 bucket for your recommendations export before you create the export job. Compute Optimizer does not create the S3 bucket for you. After you create the S3 bucket, ensure that it has the required permissions policy to allow Compute Optimizer to write the export file to it. If you plan to specify an object prefix when you create the export job, you must include the object prefix in the policy that you add to the S3 bucket. For more information, see Amazon S3 Bucket Policy for Compute Optimizer in the Compute Optimizer User Guide.

    *)
  5. fields_to_export : exportable_instance_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  6. filters : filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of instance recommendations.

    *)
  7. account_ids : account_ids option;
    (*

    The IDs of the Amazon Web Services accounts for which to export instance recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to export recommendations.

    This parameter cannot be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the include member accounts parameter, is omitted.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_ebs_volume_recommendations_response = {
  1. s3_destination : s3_destination option;
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    Use the DescribeRecommendationExportJobs action, and specify the job ID to view the status of an export job.

    *)
}
type nonrec export_ebs_volume_recommendations_request = {
  1. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to include recommendations for resources in all member accounts of the organization if your account is the management account of an organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    Recommendations for member accounts of the organization are not included in the export file if this parameter is omitted.

    This parameter cannot be specified together with the account IDs parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the account IDs parameter, is omitted.

    *)
  2. file_format : file_format option;
    (*

    The format of the export file.

    The only export file format currently supported is Csv.

    *)
  3. s3_destination_config : s3_destination_config;
  4. fields_to_export : exportable_volume_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  5. filters : ebs_filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of Amazon EBS volume recommendations.

    *)
  6. account_ids : account_ids option;
    (*

    The IDs of the Amazon Web Services accounts for which to export Amazon EBS volume recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to export recommendations.

    This parameter cannot be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the include member accounts parameter, is omitted.

    You can specify multiple account IDs per request.

    *)
}
type nonrec export_auto_scaling_group_recommendations_response = {
  1. s3_destination : s3_destination option;
    (*

    An object that describes the destination Amazon S3 bucket of a recommendations export file.

    *)
  2. job_id : job_id option;
    (*

    The identification number of the export job.

    Use the DescribeRecommendationExportJobs action, and specify the job ID to view the status of an export job.

    *)
}
type nonrec export_auto_scaling_group_recommendations_request = {
  1. recommendation_preferences : recommendation_preferences option;
    (*

    An object to specify the preferences for the Auto Scaling group recommendations to export.

    *)
  2. include_member_accounts : include_member_accounts option;
    (*

    Indicates whether to include recommendations for resources in all member accounts of the organization if your account is the management account of an organization.

    The member accounts must also be opted in to Compute Optimizer, and trusted access for Compute Optimizer must be enabled in the organization account. For more information, see Compute Optimizer and Amazon Web Services Organizations trusted access in the Compute Optimizer User Guide.

    Recommendations for member accounts of the organization are not included in the export file if this parameter is omitted.

    This parameter cannot be specified together with the account IDs parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the account IDs parameter, is omitted.

    *)
  3. file_format : file_format option;
    (*

    The format of the export file.

    The only export file format currently supported is Csv.

    *)
  4. s3_destination_config : s3_destination_config;
    (*

    An object to specify the destination Amazon Simple Storage Service (Amazon S3) bucket name and key prefix for the export job.

    You must create the destination Amazon S3 bucket for your recommendations export before you create the export job. Compute Optimizer does not create the S3 bucket for you. After you create the S3 bucket, ensure that it has the required permissions policy to allow Compute Optimizer to write the export file to it. If you plan to specify an object prefix when you create the export job, you must include the object prefix in the policy that you add to the S3 bucket. For more information, see Amazon S3 Bucket Policy for Compute Optimizer in the Compute Optimizer User Guide.

    *)
  5. fields_to_export : exportable_auto_scaling_group_fields option;
    (*

    The recommendations data to include in the export file. For more information about the fields that can be exported, see Exported files in the Compute Optimizer User Guide.

    *)
  6. filters : filters option;
    (*

    An array of objects to specify a filter that exports a more specific set of Auto Scaling group recommendations.

    *)
  7. account_ids : account_ids option;
    (*

    The IDs of the Amazon Web Services accounts for which to export Auto Scaling group recommendations.

    If your account is the management account of an organization, use this parameter to specify the member account for which you want to export recommendations.

    This parameter cannot be specified together with the include member accounts parameter. The parameters are mutually exclusive.

    Recommendations for member accounts are not included in the export if this parameter, or the include member accounts parameter, is omitted.

    You can specify multiple account IDs per request.

    *)
}
type nonrec describe_recommendation_export_jobs_response = {
  1. next_token : next_token option;
    (*

    The token to use to advance to the next page of export jobs.

    This value is null when there are no more pages of export jobs to return.

    *)
  2. recommendation_export_jobs : recommendation_export_jobs option;
    (*

    An array of objects that describe recommendation export jobs.

    *)
}
type nonrec describe_recommendation_export_jobs_request = {
  1. max_results : max_results option;
    (*

    The maximum number of export jobs to return with a single request.

    To retrieve the remaining results, make another request with the returned nextToken value.

    *)
  2. next_token : next_token option;
    (*

    The token to advance to the next page of export jobs.

    *)
  3. filters : job_filters option;
    (*

    An array of objects to specify a filter that returns a more specific list of export jobs.

    *)
  4. job_ids : job_ids option;
    (*

    The identification numbers of the export jobs to return.

    An export job ID is returned when you create an export using the ExportAutoScalingGroupRecommendations or ExportEC2InstanceRecommendations actions.

    All export jobs created in the last seven days are returned if this parameter is omitted.

    *)
}
type nonrec delete_recommendation_preferences_response = unit
type nonrec delete_recommendation_preferences_request = {
  1. recommendation_preference_names : recommendation_preference_names;
    (*

    The name of the recommendation preference to delete.

    *)
  2. scope : scope option;
    (*

    An object that describes the scope of the recommendation preference to delete.

    You can delete recommendation preferences that are created at the organization level (for management accounts of an organization only), account level, and resource level. For more information, see Activating enhanced infrastructure metrics in the Compute Optimizer User Guide.

    *)
  3. resource_type : resource_type;
    (*

    The target resource type of the recommendation preference to delete.

    The Ec2Instance option encompasses standalone instances and instances that are part of Auto Scaling groups. The AutoScalingGroup option encompasses only instances that are part of an Auto Scaling group.

    *)
}