| Column Name | Column Data Type |
|---|
account_ids Input Column
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. | VARCHAR[] |
Show child fields- account_ids[]
|
auto_scaling_group_arns Input Column
The Amazon Resource Name (ARN) of the Auto Scaling groups for which to return recommendations. | VARCHAR[] |
Show child fields- auto_scaling_group_arns[]
|
filters Input Column
An array of objects to specify a filter that returns a more specific list of Auto Scaling group recommendations. | STRUCT(
"name" VARCHAR,
"values" VARCHAR[]
)[] |
Show child fields- filters[]
Show child fields- filters[].name
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. - filters[].values[]
|
max_results Input Column
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. | BIGINT |
next_token Input Column
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. | VARCHAR |
recommendation_preferences Input Column
An object to specify the preferences for the Auto Scaling group recommendations to return in the response. | STRUCT(
"cpu_vendor_architectures" VARCHAR[]
) |
Show child fields- recommendation_preferences.cpu_vendor_architectures[]
|
_aws_profile Input Column
The AWS profile defines the AWS identity used. It can be defined via credentials or by assuming a IAM role. | STRUCT(
"type" VARCHAR,
"name" VARCHAR,
"account_id" VARCHAR,
"via_profile_name" VARCHAR,
"assumed_role_arn" VARCHAR,
"organization" STRUCT(
"account_name" VARCHAR,
"id" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[],
"master_account" STRUCT(
"id" VARCHAR,
"email" VARCHAR
),
"parents" STRUCT(
"type" VARCHAR,
"id" VARCHAR,
"name" VARCHAR,
"tags" STRUCT(
"key" VARCHAR,
"value" VARCHAR
)[]
)[]
)
) |
Show child fields- _aws_profile.account_id
The AWS account id - _aws_profile.assumed_role_arn
The ARN of the assumed role - _aws_profile.name
The unique name of the profile. - _aws_profile.organization
Information about this profile's membership in the AWS organization. Show child fields- _aws_profile.organization.account_name
The name of account speciifed by the organization - _aws_profile.organization.id
The organization id - _aws_profile.organization.master_account
Show child fields- _aws_profile.organization.master_account.email
The organization master account email address - _aws_profile.organization.master_account.id
The organization master account id
- _aws_profile.organization.parents[]
Show child fields- _aws_profile.organization.parents[].id
The id of the parent - _aws_profile.organization.parents[].name
The name of the parent - _aws_profile.organization.parents[].tags[]
Show child fields- _aws_profile.organization.parents[].tags[].key
- _aws_profile.organization.parents[].tags[].value
- _aws_profile.organization.parents[].type
The type of parent can be an organization unit or a root
- _aws_profile.organization.tags[]
Show child fields- _aws_profile.organization.tags[].key
- _aws_profile.organization.tags[].value
- _aws_profile.type
The type of profile, either 'credentials' or 'assumed_role' - _aws_profile.via_profile_name
This IAM role for this profile is assumed by first utilizing another profile with this name to obtain credentials.
|
_aws_region Input Column
The AWS region to use. | VARCHAR |
auto_scaling_group_recommendations
An array of objects that describe Auto Scaling group recommendations. | STRUCT(
"account_id" VARCHAR,
"auto_scaling_group_arn" VARCHAR,
"auto_scaling_group_name" VARCHAR,
"finding" VARCHAR,
"utilization_metrics" STRUCT(
"name" VARCHAR,
"statistic" VARCHAR,
"value" DOUBLE
)[],
"look_back_period_in_days" DOUBLE,
"current_configuration" STRUCT(
"desired_capacity" BIGINT,
"min_size" BIGINT,
"max_size" BIGINT,
"instance_type" VARCHAR
),
"current_instance_gpu_info" STRUCT(
"gpus" STRUCT(
"gpu_count" BIGINT,
"gpu_memory_size_in_mi_b" BIGINT
)[]
),
"recommendation_options" STRUCT(
"configuration" STRUCT(
"desired_capacity" BIGINT,
"min_size" BIGINT,
"max_size" BIGINT,
"instance_type" VARCHAR
),
"instance_gpu_info" STRUCT(
"gpus" STRUCT(
"gpu_count" BIGINT,
"gpu_memory_size_in_mi_b" BIGINT
)[]
),
"projected_utilization_metrics" STRUCT(
"name" VARCHAR,
"statistic" VARCHAR,
"value" DOUBLE
)[],
"performance_risk" DOUBLE,
"rank" BIGINT,
"savings_opportunity" STRUCT(
"savings_opportunity_percentage" DOUBLE,
"estimated_monthly_savings" STRUCT(
"currency" VARCHAR,
"value" DOUBLE
)
),
"savings_opportunity_after_discounts" STRUCT(
"savings_opportunity_percentage" DOUBLE,
"estimated_monthly_savings" STRUCT(
"currency" VARCHAR,
"value" DOUBLE
)
),
"migration_effort" VARCHAR
)[],
"last_refresh_timestamp" TIMESTAMP_S,
"current_performance_risk" VARCHAR,
"effective_recommendation_preferences" STRUCT(
"cpu_vendor_architectures" VARCHAR[],
"enhanced_infrastructure_metrics" VARCHAR,
"inferred_workload_types" VARCHAR,
"external_metrics_preference" STRUCT(
"source" VARCHAR
),
"look_back_period" VARCHAR,
"utilization_preferences" STRUCT(
"metric_name" VARCHAR,
"metric_parameters" STRUCT(
"threshold" VARCHAR,
"headroom" VARCHAR
)
)[],
"preferred_resources" STRUCT(
"name" VARCHAR,
"include_list" VARCHAR[],
"effective_include_list" VARCHAR[],
"exclude_list" VARCHAR[]
)[],
"savings_estimation_mode" STRUCT(
"source" VARCHAR
)
),
"inferred_workload_types" VARCHAR[]
)[] |
Show child fields- auto_scaling_group_recommendations[]
Show child fields- auto_scaling_group_recommendations[].account_id
The Amazon Web Services account ID of the Auto Scaling group. - auto_scaling_group_recommendations[].auto_scaling_group_arn
The Amazon Resource Name (ARN) of the Auto Scaling group. - auto_scaling_group_recommendations[].auto_scaling_group_name
The name of the Auto Scaling group. - auto_scaling_group_recommendations[].current_configuration
An array of objects that describe the current configuration of the Auto Scaling group. Show child fields- auto_scaling_group_recommendations[].current_configuration.desired_capacity
The desired capacity, or number of instances, for the Auto Scaling group. - auto_scaling_group_recommendations[].current_configuration.instance_type
The instance type for the Auto Scaling group. - auto_scaling_group_recommendations[].current_configuration.max_size
The maximum size, or maximum number of instances, for the Auto Scaling group. - auto_scaling_group_recommendations[].current_configuration.min_size
The minimum size, or minimum number of instances, for the Auto Scaling group.
- auto_scaling_group_recommendations[].current_instance_gpu_info
Describes the GPU accelerator settings for the current instance type of the Auto Scaling group. Show child fields- auto_scaling_group_recommendations[].current_instance_gpu_info.gpus[]
Show child fields- auto_scaling_group_recommendations[].current_instance_gpu_info.gpus[].gpu_count
The number of GPUs for the instance type. - auto_scaling_group_recommendations[].current_instance_gpu_info.gpus[].gpu_memory_size_in_mi_b
The total size of the memory for the GPU accelerators for the instance type, in MiB.
- auto_scaling_group_recommendations[].current_performance_risk
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. - auto_scaling_group_recommendations[].effective_recommendation_preferences
An object that describes the effective recommendation preferences for the Auto Scaling group. Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.cpu_vendor_architectures[]
- auto_scaling_group_recommendations[].effective_recommendation_preferences.enhanced_infrastructure_metrics
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. - auto_scaling_group_recommendations[].effective_recommendation_preferences.external_metrics_preference
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. Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.external_metrics_preference.source
Contains the source options for external metrics preferences.
- auto_scaling_group_recommendations[].effective_recommendation_preferences.inferred_workload_types
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. - auto_scaling_group_recommendations[].effective_recommendation_preferences.look_back_period
The number of days the utilization metrics of the Amazon Web Services resource are analyzed. - auto_scaling_group_recommendations[].effective_recommendation_preferences.preferred_resources[]
Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.preferred_resources[].effective_include_list[]
- auto_scaling_group_recommendations[].effective_recommendation_preferences.preferred_resources[].exclude_list[]
- auto_scaling_group_recommendations[].effective_recommendation_preferences.preferred_resources[].include_list[]
- auto_scaling_group_recommendations[].effective_recommendation_preferences.preferred_resources[].name
The name of the preferred resource list.
- auto_scaling_group_recommendations[].effective_recommendation_preferences.savings_estimation_mode
Describes the savings estimation mode applied for calculating savings opportunity for a resource. Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.savings_estimation_mode.source
Describes the source for calculating the savings opportunity for Amazon EC2 instances.
- auto_scaling_group_recommendations[].effective_recommendation_preferences.utilization_preferences[]
Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.utilization_preferences[].metric_name
The name of the resource utilization metric name to customize. - auto_scaling_group_recommendations[].effective_recommendation_preferences.utilization_preferences[].metric_parameters
The parameters to set when customizing the resource utilization thresholds. Show child fields- auto_scaling_group_recommendations[].effective_recommendation_preferences.utilization_preferences[].metric_parameters.headroom
The headroom value in percentage used for the specified metric parameter. The following lists the valid values for CPU and memory utilization. - auto_scaling_group_recommendations[].effective_recommendation_preferences.utilization_preferences[].metric_parameters.threshold
The threshold value used for the specified metric parameter. You can only specify the threshold value for CPU utilization.
- auto_scaling_group_recommendations[].finding
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. - auto_scaling_group_recommendations[].inferred_workload_types[]
- auto_scaling_group_recommendations[].last_refresh_timestamp
The timestamp of when the Auto Scaling group recommendation was last generated. - auto_scaling_group_recommendations[].look_back_period_in_days
The number of days for which utilization metrics were analyzed for the Auto Scaling group. - auto_scaling_group_recommendations[].recommendation_options[]
Show child fields- auto_scaling_group_recommendations[].recommendation_options[].configuration
An array of objects that describe an Auto Scaling group configuration. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].configuration.desired_capacity
The desired capacity, or number of instances, for the Auto Scaling group. - auto_scaling_group_recommendations[].recommendation_options[].configuration.instance_type
The instance type for the Auto Scaling group. - auto_scaling_group_recommendations[].recommendation_options[].configuration.max_size
The maximum size, or maximum number of instances, for the Auto Scaling group. - auto_scaling_group_recommendations[].recommendation_options[].configuration.min_size
The minimum size, or minimum number of instances, for the Auto Scaling group.
- auto_scaling_group_recommendations[].recommendation_options[].instance_gpu_info
Describes the GPU accelerator settings for the recommended instance type of the Auto Scaling group. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].instance_gpu_info.gpus[]
Show child fields- auto_scaling_group_recommendations[].recommendation_options[].instance_gpu_info.gpus[].gpu_count
The number of GPUs for the instance type. - auto_scaling_group_recommendations[].recommendation_options[].instance_gpu_info.gpus[].gpu_memory_size_in_mi_b
The total size of the memory for the GPU accelerators for the instance type, in MiB.
- auto_scaling_group_recommendations[].recommendation_options[].migration_effort
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. - auto_scaling_group_recommendations[].recommendation_options[].performance_risk
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. - auto_scaling_group_recommendations[].recommendation_options[].projected_utilization_metrics[]
Show child fields- auto_scaling_group_recommendations[].recommendation_options[].projected_utilization_metrics[].name
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. - auto_scaling_group_recommendations[].recommendation_options[].projected_utilization_metrics[].statistic
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. - auto_scaling_group_recommendations[].recommendation_options[].projected_utilization_metrics[].value
The value of the utilization metric.
- auto_scaling_group_recommendations[].recommendation_options[].rank
The rank of the Auto Scaling group recommendation option. The top recommendation option is ranked as 1. - auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity
An object that describes the savings opportunity for the Auto Scaling group recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity.estimated_monthly_savings
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.. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity.estimated_monthly_savings.currency
The currency of the estimated monthly savings. - auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity.estimated_monthly_savings.value
The value of the estimated monthly savings.
- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity.savings_opportunity_percentage
The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer recommendations for a given resource.
- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity_after_discounts
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. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity_after_discounts.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 pricing discounts. Show child fields- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity_after_discounts.estimated_monthly_savings.currency
The currency of the estimated monthly savings. - auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity_after_discounts.estimated_monthly_savings.value
The value of the estimated monthly savings.
- auto_scaling_group_recommendations[].recommendation_options[].savings_opportunity_after_discounts.savings_opportunity_percentage
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.
- auto_scaling_group_recommendations[].utilization_metrics[]
Show child fields- auto_scaling_group_recommendations[].utilization_metrics[].name
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. - auto_scaling_group_recommendations[].utilization_metrics[].statistic
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. - auto_scaling_group_recommendations[].utilization_metrics[].value
The value of the utilization metric.
|
errors
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. | STRUCT(
"identifier" VARCHAR,
"code" VARCHAR,
"message" VARCHAR
)[] |
Show child fields- errors[]
Show child fields- errors[].code
The error code. - errors[].identifier
The ID of the error. - errors[].message
The message, or reason, for the error.
|