ComputeOptimizer / Client / get_auto_scaling_group_recommendations

get_auto_scaling_group_recommendations#

ComputeOptimizer.Client.get_auto_scaling_group_recommendations(**kwargs)#

Returns Auto Scaling group recommendations.

Compute Optimizer generates recommendations for Amazon EC2 Auto Scaling groups that meet a specific set of requirements. For more information, see the Supported resources and requirements in the Compute Optimizer User Guide.

Request Syntax

response = client.get_auto_scaling_group_recommendations(
    accountIds=[
        'string',
    ],
    autoScalingGroupArns=[
        'string',
    ],
    nextToken='string',
    maxResults=123,
    filters=[
        {
            'name': 'Finding'|'FindingReasonCodes'|'RecommendationSourceType'|'InferredWorkloadTypes',
            'values': [
                'string',
            ]
        },
    ],
    recommendationPreferences={
        'cpuVendorArchitectures': [
            'AWS_ARM64'|'CURRENT',
        ]
    }
)

Parameters:

accountIds (list) –
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.
- (string) –
autoScalingGroupArns (list) –
The Amazon Resource Name (ARN) of the Auto Scaling groups for which to return recommendations.
- (string) –
nextToken (string) – The token to advance to the next page of Auto Scaling group recommendations.
maxResults (integer) –
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.
filters (list) –
An array of objects to specify a filter that returns a more specific list of Auto Scaling group recommendations.
- (dict) –
  
  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.
  - name (string) –
    
    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.
  - values (list) –
    
    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.
    - (string) –
recommendationPreferences (dict) –
An object to specify the preferences for the Auto Scaling group recommendations to return in the response.
- cpuVendorArchitectures (list) –
  
  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.
  - (string) –

Return type:

dict

Returns:

Response Syntax

{
    'nextToken': 'string',
    'autoScalingGroupRecommendations': [
        {
            'accountId': 'string',
            'autoScalingGroupArn': 'string',
            'autoScalingGroupName': 'string',
            'finding': 'Underprovisioned'|'Overprovisioned'|'Optimized'|'NotOptimized',
            'utilizationMetrics': [
                {
                    'name': 'Cpu'|'Memory'|'EBS_READ_OPS_PER_SECOND'|'EBS_WRITE_OPS_PER_SECOND'|'EBS_READ_BYTES_PER_SECOND'|'EBS_WRITE_BYTES_PER_SECOND'|'DISK_READ_OPS_PER_SECOND'|'DISK_WRITE_OPS_PER_SECOND'|'DISK_READ_BYTES_PER_SECOND'|'DISK_WRITE_BYTES_PER_SECOND'|'NETWORK_IN_BYTES_PER_SECOND'|'NETWORK_OUT_BYTES_PER_SECOND'|'NETWORK_PACKETS_IN_PER_SECOND'|'NETWORK_PACKETS_OUT_PER_SECOND'|'GPU_PERCENTAGE'|'GPU_MEMORY_PERCENTAGE',
                    'statistic': 'Maximum'|'Average',
                    'value': 123.0
                },
            ],
            'lookBackPeriodInDays': 123.0,
            'currentConfiguration': {
                'desiredCapacity': 123,
                'minSize': 123,
                'maxSize': 123,
                'instanceType': 'string'
            },
            'currentInstanceGpuInfo': {
                'gpus': [
                    {
                        'gpuCount': 123,
                        'gpuMemorySizeInMiB': 123
                    },
                ]
            },
            'recommendationOptions': [
                {
                    'configuration': {
                        'desiredCapacity': 123,
                        'minSize': 123,
                        'maxSize': 123,
                        'instanceType': 'string'
                    },
                    'instanceGpuInfo': {
                        'gpus': [
                            {
                                'gpuCount': 123,
                                'gpuMemorySizeInMiB': 123
                            },
                        ]
                    },
                    'projectedUtilizationMetrics': [
                        {
                            'name': 'Cpu'|'Memory'|'EBS_READ_OPS_PER_SECOND'|'EBS_WRITE_OPS_PER_SECOND'|'EBS_READ_BYTES_PER_SECOND'|'EBS_WRITE_BYTES_PER_SECOND'|'DISK_READ_OPS_PER_SECOND'|'DISK_WRITE_OPS_PER_SECOND'|'DISK_READ_BYTES_PER_SECOND'|'DISK_WRITE_BYTES_PER_SECOND'|'NETWORK_IN_BYTES_PER_SECOND'|'NETWORK_OUT_BYTES_PER_SECOND'|'NETWORK_PACKETS_IN_PER_SECOND'|'NETWORK_PACKETS_OUT_PER_SECOND'|'GPU_PERCENTAGE'|'GPU_MEMORY_PERCENTAGE',
                            'statistic': 'Maximum'|'Average',
                            'value': 123.0
                        },
                    ],
                    'performanceRisk': 123.0,
                    'rank': 123,
                    'savingsOpportunity': {
                        'savingsOpportunityPercentage': 123.0,
                        'estimatedMonthlySavings': {
                            'currency': 'USD'|'CNY',
                            'value': 123.0
                        }
                    },
                    'savingsOpportunityAfterDiscounts': {
                        'savingsOpportunityPercentage': 123.0,
                        'estimatedMonthlySavings': {
                            'currency': 'USD'|'CNY',
                            'value': 123.0
                        }
                    },
                    'migrationEffort': 'VeryLow'|'Low'|'Medium'|'High'
                },
            ],
            'lastRefreshTimestamp': datetime(2015, 1, 1),
            'currentPerformanceRisk': 'VeryLow'|'Low'|'Medium'|'High',
            'effectiveRecommendationPreferences': {
                'cpuVendorArchitectures': [
                    'AWS_ARM64'|'CURRENT',
                ],
                'enhancedInfrastructureMetrics': 'Active'|'Inactive',
                'inferredWorkloadTypes': 'Active'|'Inactive',
                'externalMetricsPreference': {
                    'source': 'Datadog'|'Dynatrace'|'NewRelic'|'Instana'
                },
                'lookBackPeriod': 'DAYS_14'|'DAYS_32'|'DAYS_93',
                'utilizationPreferences': [
                    {
                        'metricName': 'CpuUtilization'|'MemoryUtilization',
                        'metricParameters': {
                            'threshold': 'P90'|'P95'|'P99_5',
                            'headroom': 'PERCENT_30'|'PERCENT_20'|'PERCENT_10'|'PERCENT_0'
                        }
                    },
                ],
                'preferredResources': [
                    {
                        'name': 'Ec2InstanceTypes',
                        'includeList': [
                            'string',
                        ],
                        'effectiveIncludeList': [
                            'string',
                        ],
                        'excludeList': [
                            'string',
                        ]
                    },
                ],
                'savingsEstimationMode': {
                    'source': 'PublicPricing'|'CostExplorerRightsizing'|'CostOptimizationHub'
                }
            },
            'inferredWorkloadTypes': [
                'AmazonEmr'|'ApacheCassandra'|'ApacheHadoop'|'Memcached'|'Nginx'|'PostgreSql'|'Redis'|'Kafka'|'SQLServer',
            ]
        },
    ],
    'errors': [
        {
            'identifier': 'string',
            'code': 'string',
            'message': 'string'
        },
    ]
}

Response Structure

(dict) –
- nextToken (string) –
  
  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.
- autoScalingGroupRecommendations (list) –
  
  An array of objects that describe Auto Scaling group recommendations.
  - (dict) –
    
    Describes an Auto Scaling group recommendation.
    - accountId (string) –
      
      The Amazon Web Services account ID of the Auto Scaling group.
    - autoScalingGroupArn (string) –
      
      The Amazon Resource Name (ARN) of the Auto Scaling group.
    - autoScalingGroupName (string) –
      
      The name of the Auto Scaling group.
    - finding (string) –
      
      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.
    - utilizationMetrics (list) –
      
      An array of objects that describe the utilization metrics of the Auto Scaling group.
      - (dict) –
        
        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.
        
        name (string) –
        
        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
        
        Note
        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.
        
        Note
        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.
        
        statistic (string) –
        
        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.
        
        value (float) –
        
        The value of the utilization metric.
    - lookBackPeriodInDays (float) –
      
      The number of days for which utilization metrics were analyzed for the Auto Scaling group.
    - currentConfiguration (dict) –
      
      An array of objects that describe the current configuration of the Auto Scaling group.
      - desiredCapacity (integer) –
        
        The desired capacity, or number of instances, for the Auto Scaling group.
      - minSize (integer) –
        
        The minimum size, or minimum number of instances, for the Auto Scaling group.
      - maxSize (integer) –
        
        The maximum size, or maximum number of instances, for the Auto Scaling group.
      - instanceType (string) –
        
        The instance type for the Auto Scaling group.
    - currentInstanceGpuInfo (dict) –
      
      Describes the GPU accelerator settings for the current instance type of the Auto Scaling group.
      - gpus (list) –
        
        Describes the GPU accelerators for the instance type.
        
        (dict) –
        
        Describes the GPU accelerators for the instance type.
        
        gpuCount (integer) –
        
        The number of GPUs for the instance type.
        
        gpuMemorySizeInMiB (integer) –
        
        The total size of the memory for the GPU accelerators for the instance type, in MiB.
    - recommendationOptions (list) –
      
      An array of objects that describe the recommendation options for the Auto Scaling group.
      - (dict) –
        
        Describes a recommendation option for an Auto Scaling group.
        
        configuration (dict) –
        
        An array of objects that describe an Auto Scaling group configuration.
        
        desiredCapacity (integer) –
        
        The desired capacity, or number of instances, for the Auto Scaling group.
        
        minSize (integer) –
        
        The minimum size, or minimum number of instances, for the Auto Scaling group.
        
        maxSize (integer) –
        
        The maximum size, or maximum number of instances, for the Auto Scaling group.
        
        instanceType (string) –
        
        The instance type for the Auto Scaling group.
        
        instanceGpuInfo (dict) –
        
        Describes the GPU accelerator settings for the recommended instance type of the Auto Scaling group.
        
        gpus (list) –
        
        Describes the GPU accelerators for the instance type.
        
        (dict) –
        
        Describes the GPU accelerators for the instance type.
        
        gpuCount (integer) –
        
        The number of GPUs for the instance type.
        
        gpuMemorySizeInMiB (integer) –
        
        The total size of the memory for the GPU accelerators for the instance type, in MiB.
        
        projectedUtilizationMetrics (list) –
        
        An array of objects that describe the projected utilization metrics of the Auto Scaling group recommendation option.
        
        Note
        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.
        
        (dict) –
        
        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.
        
        name (string) –
        
        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
        
        Note
        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.
        
        Note
        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.
        
        statistic (string) –
        
        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.
        
        value (float) –
        
        The value of the utilization metric.
        
        performanceRisk (float) –
        
        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.
        
        rank (integer) –
        
        The rank of the Auto Scaling group recommendation option.
        
        The top recommendation option is ranked as 1.
        
        savingsOpportunity (dict) –
        
        An object that describes the savings opportunity for the Auto Scaling group recommendation option. Savings opportunity includes the estimated monthly savings amount and percentage.
        
        savingsOpportunityPercentage (float) –
        
        The estimated monthly savings possible as a percentage of monthly cost by adopting Compute Optimizer recommendations for a given resource.
        
        estimatedMonthlySavings (dict) –
        
        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..
        
        currency (string) –
        
        The currency of the estimated monthly savings.
        
        value (float) –
        
        The value of the estimated monthly savings.
        
        savingsOpportunityAfterDiscounts (dict) –
        
        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.
        
        savingsOpportunityPercentage (float) –
        
        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.
        
        estimatedMonthlySavings (dict) –
        
        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.
        
        currency (string) –
        
        The currency of the estimated monthly savings.
        
        value (float) –
        
        The value of the estimated monthly savings.
        
        migrationEffort (string) –
        
        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.
    - lastRefreshTimestamp (datetime) –
      
      The timestamp of when the Auto Scaling group recommendation was last generated.
    - currentPerformanceRisk (string) –
      
      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.
    - effectiveRecommendationPreferences (dict) –
      
      An object that describes the effective recommendation preferences for the Auto Scaling group.
      - cpuVendorArchitectures (list) –
        
        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.
        
        (string) –
      - enhancedInfrastructureMetrics (string) –
        
        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.
      - inferredWorkloadTypes (string) –
        
        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.
      - externalMetricsPreference (dict) –
        
        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.
        
        source (string) –
        
        Contains the source options for external metrics preferences.
      - lookBackPeriod (string) –
        
        The number of days the utilization metrics of the Amazon Web Services resource are analyzed.
      - utilizationPreferences (list) –
        
        The resource’s CPU and memory utilization preferences, such as threshold and headroom, that are used to generate rightsizing recommendations.
        
        Note
        This preference is only available for the Amazon EC2 instance resource type.
        
        (dict) –
        
        The preference to control the resource’s CPU utilization threshold, CPU utilization headroom, and memory utilization headroom.
        
        Note
        This preference is only available for the Amazon EC2 instance resource type.
        
        metricName (string) –
        
        The name of the resource utilization metric name to customize.
        
        metricParameters (dict) –
        
        The parameters to set when customizing the resource utilization thresholds.
        
        threshold (string) –
        
        The threshold value used for the specified metric parameter.
        
        Note
        You can only specify the threshold value for CPU utilization.
        
        headroom (string) –
        
        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
      - preferredResources (list) –
        
        The resource type values that are considered as candidates when generating rightsizing recommendations.
        
        (dict) –
        
        Describes the effective preferred resources that Compute Optimizer considers as rightsizing recommendation candidates.
        
        Note
        Compute Optimizer only supports Amazon EC2 instance types.
        
        name (string) –
        
        The name of the preferred resource list.
        
        includeList (list) –
        
        The list of preferred resource values that you want considered as rightsizing recommendation candidates.
        
        (string) –
        
        effectiveIncludeList (list) –
        
        The expanded version of your preferred resource’s include list.
        
        (string) –
        
        excludeList (list) –
        
        The list of preferred resources values that you want excluded from rightsizing recommendation candidates.
        
        (string) –
      - savingsEstimationMode (dict) –
        
        Describes the savings estimation mode applied for calculating savings opportunity for a resource.
        
        source (string) –
        
        Describes the source for calculating the savings opportunity for Amazon EC2 instances.
    - inferredWorkloadTypes (list) –
      
      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.
      - (string) –
- errors (list) –
  
  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.
  - (dict) –
    
    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.
    - identifier (string) –
      
      The ID of the error.
    - code (string) –
      
      The error code.
    - message (string) –
      
      The message, or reason, for the error.

Exceptions

ComputeOptimizer.Client.exceptions.OptInRequiredException
ComputeOptimizer.Client.exceptions.InternalServerException
ComputeOptimizer.Client.exceptions.ServiceUnavailableException
ComputeOptimizer.Client.exceptions.AccessDeniedException
ComputeOptimizer.Client.exceptions.InvalidParameterValueException
ComputeOptimizer.Client.exceptions.ResourceNotFoundException
ComputeOptimizer.Client.exceptions.MissingAuthenticationToken
ComputeOptimizer.Client.exceptions.ThrottlingException