ComputeOptimizer / Client / get_lambda_function_recommendations

get_lambda_function_recommendations#

ComputeOptimizer.Client.get_lambda_function_recommendations(**kwargs)#

Returns Lambda function recommendations.

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

See also: AWS API Documentation

Request Syntax

response = client.get_lambda_function_recommendations(
    functionArns=[
        'string',
    ],
    accountIds=[
        'string',
    ],
    filters=[
        {
            'name': 'Finding'|'FindingReasonCode',
            'values': [
                'string',
            ]
        },
    ],
    nextToken='string',
    maxResults=123
)
Parameters:

  • functionArns (list) –

    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.

    • (string) –

  • accountIds (list) –

    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.

    • (string) –

  • filters (list) –

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

    • (dict) –

      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.

      • name (string) –

        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.

      • 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:

        • 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.

        • (string) –

  • nextToken (string) – The token to advance to the next page of function recommendations.

  • maxResults (integer) –

    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.

Return type:

dict

Returns:

Response Syntax

{
    'nextToken': 'string',
    'lambdaFunctionRecommendations': [
        {
            'functionArn': 'string',
            'functionVersion': 'string',
            'accountId': 'string',
            'currentMemorySize': 123,
            'numberOfInvocations': 123,
            'utilizationMetrics': [
                {
                    'name': 'Duration'|'Memory',
                    'statistic': 'Maximum'|'Average',
                    'value': 123.0
                },
            ],
            'lookbackPeriodInDays': 123.0,
            'lastRefreshTimestamp': datetime(2015, 1, 1),
            'finding': 'Optimized'|'NotOptimized'|'Unavailable',
            'findingReasonCodes': [
                'MemoryOverprovisioned'|'MemoryUnderprovisioned'|'InsufficientData'|'Inconclusive',
            ],
            'memorySizeRecommendationOptions': [
                {
                    'rank': 123,
                    'memorySize': 123,
                    'projectedUtilizationMetrics': [
                        {
                            'name': 'Duration',
                            'statistic': 'LowerBound'|'UpperBound'|'Expected',
                            'value': 123.0
                        },
                    ],
                    'savingsOpportunity': {
                        'savingsOpportunityPercentage': 123.0,
                        'estimatedMonthlySavings': {
                            'currency': 'USD'|'CNY',
                            'value': 123.0
                        }
                    },
                    'savingsOpportunityAfterDiscounts': {
                        'savingsOpportunityPercentage': 123.0,
                        'estimatedMonthlySavings': {
                            'currency': 'USD'|'CNY',
                            'value': 123.0
                        }
                    }
                },
            ],
            'currentPerformanceRisk': 'VeryLow'|'Low'|'Medium'|'High',
            'effectiveRecommendationPreferences': {
                'savingsEstimationMode': {
                    'source': 'PublicPricing'|'CostExplorerRightsizing'|'CostOptimizationHub'
                }
            },
            'tags': [
                {
                    'key': 'string',
                    'value': 'string'
                },
            ]
        },
    ]
}

Response Structure

  • (dict) –

    • nextToken (string) –

      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.

    • lambdaFunctionRecommendations (list) –

      An array of objects that describe function recommendations.

      • (dict) –

        Describes an Lambda function recommendation.

        • functionArn (string) –

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

        • functionVersion (string) –

          The version number of the current function.

        • accountId (string) –

          The Amazon Web Services account ID of the function.

        • currentMemorySize (integer) –

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

        • numberOfInvocations (integer) –

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

        • utilizationMetrics (list) –

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

          • (dict) –

            Describes a utilization metric of an Lambda function.

            • name (string) –

              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.

            • 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 function.

        • lastRefreshTimestamp (datetime) –

          The timestamp of when the function recommendation was last generated.

        • finding (string) –

          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.

          Note

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

        • findingReasonCodes (list) –

          The reason for the finding classification of the function.

          Note

          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.

          • (string) –

        • memorySizeRecommendationOptions (list) –

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

          • (dict) –

            Describes a recommendation option for an Lambda function.

            • rank (integer) –

              The rank of the function recommendation option.

              The top recommendation option is ranked as 1.

            • memorySize (integer) –

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

            • projectedUtilizationMetrics (list) –

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

              • (dict) –

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

                • name (string) –

                  The name of the projected utilization metric.

                • statistic (string) –

                  The statistic of the projected utilization metric.

                • value (float) –

                  The values of the projected utilization metrics.

            • savingsOpportunity (dict) –

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

              • savingsOpportunityPercentage (float) –

                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.

              • estimatedMonthlySavings (dict) –

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

                • currency (string) –

                  The currency of the estimated monthly savings.

                • value (float) –

                  The value of the estimated monthly savings.

        • currentPerformanceRisk (string) –

          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.

        • effectiveRecommendationPreferences (dict) –

          Describes the effective recommendation preferences for Lambda functions.

          • savingsEstimationMode (dict) –

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

            • source (string) –

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

        • tags (list) –

          A list of tags assigned to your Lambda function recommendations.

          • (dict) –

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

            • key (string) –

              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.

            • value (string) –

              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.

Exceptions