Get Ecs Service Recommendations

computeoptimizer_get_ecs_service_recommendations

R Documentation

Returns Amazon ECS service recommendations

Description

Returns Amazon ECS service recommendations.

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

Usage

computeoptimizer_get_ecs_service_recommendations(serviceArns, nextToken,
  maxResults, filters, accountIds)

Arguments

serviceArns

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

nextToken

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

maxResults

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.

filters

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

accountIds

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.

Value

A list with the following syntax:

list(
  nextToken = "string",
  ecsServiceRecommendations = list(
    list(
      serviceArn = "string",
      accountId = "string",
      currentServiceConfiguration = list(
        memory = 123,
        cpu = 123,
        containerConfigurations = list(
          list(
            containerName = "string",
            memorySizeConfiguration = list(
              memory = 123,
              memoryReservation = 123
            ),
            cpu = 123
          )
        ),
        autoScalingConfiguration = "TargetTrackingScalingCpu"|"TargetTrackingScalingMemory",
        taskDefinitionArn = "string"
      ),
      utilizationMetrics = list(
        list(
          name = "Cpu"|"Memory",
          statistic = "Maximum"|"Average",
          value = 123.0
        )
      ),
      lookbackPeriodInDays = 123.0,
      launchType = "EC2"|"Fargate",
      lastRefreshTimestamp = as.POSIXct(
        "2015-01-01"
      ),
      finding = "Optimized"|"Underprovisioned"|"Overprovisioned",
      findingReasonCodes = list(
        "MemoryOverprovisioned"|"MemoryUnderprovisioned"|"CPUOverprovisioned"|"CPUUnderprovisioned"
      ),
      serviceRecommendationOptions = list(
        list(
          memory = 123,
          cpu = 123,
          savingsOpportunity = list(
            savingsOpportunityPercentage = 123.0,
            estimatedMonthlySavings = list(
              currency = "USD"|"CNY",
              value = 123.0
            )
          ),
          savingsOpportunityAfterDiscounts = list(
            savingsOpportunityPercentage = 123.0,
            estimatedMonthlySavings = list(
              currency = "USD"|"CNY",
              value = 123.0
            )
          ),
          projectedUtilizationMetrics = list(
            list(
              name = "Cpu"|"Memory",
              statistic = "Maximum"|"Average",
              lowerBoundValue = 123.0,
              upperBoundValue = 123.0
            )
          ),
          containerRecommendations = list(
            list(
              containerName = "string",
              memorySizeConfiguration = list(
                memory = 123,
                memoryReservation = 123
              ),
              cpu = 123
            )
          )
        )
      ),
      currentPerformanceRisk = "VeryLow"|"Low"|"Medium"|"High",
      effectiveRecommendationPreferences = list(
        savingsEstimationMode = list(
          source = "PublicPricing"|"CostExplorerRightsizing"|"CostOptimizationHub"
        )
      ),
      tags = list(
        list(
          key = "string",
          value = "string"
        )
      )
    )
  ),
  errors = list(
    list(
      identifier = "string",
      code = "string",
      message = "string"
    )
  )
)

Request syntax

svc$get_ecs_service_recommendations(
  serviceArns = list(
    "string"
  ),
  nextToken = "string",
  maxResults = 123,
  filters = list(
    list(
      name = "Finding"|"FindingReasonCode",
      values = list(
        "string"
      )
    )
  ),
  accountIds = list(
    "string"
  )
)