{ "$schema": "https://json-structure.org/meta/core/v0/#", "$id": "https://raw.githubusercontent.com/api-evangelist/amazon-compute-optimizer/refs/heads/main/json-structure/compute-optimizer-ecs-service-recommendation-structure.json", "name": "ECSServiceRecommendation", "description": " Describes an Amazon ECS service recommendation. ", "type": "object", "properties": { "serviceArn": { "allOf": [ { "$ref": "#/components/schemas/ServiceArn" }, { "description": "
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
The launch type the Amazon ECS service is using.
Compute Optimizer only supports the Fargate launch type.
The finding classification of an Amazon ECS service.
Findings for Amazon ECS services include:
Underprovisioned \u2014 When Compute Optimizer detects that there\u2019s not enough memory or CPU, an Amazon ECS service is considered under-provisioned. An under-provisioned service might result in poor application performance.
Overprovisioned \u2014 When Compute Optimizer detects that there\u2019s excessive memory or CPU, an Amazon ECS service is considered over-provisioned. An over-provisioned service might result in additional infrastructure costs.
Optimized \u2014 When both the CPU and memory of your Amazon ECS service meet the performance requirements of your workload, the service is considered optimized.
The reason for the finding classification of an Amazon ECS service.
Finding reason codes for Amazon ECS services include:
CPUUnderprovisioned \u2014 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 \u2014 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 \u2014 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 \u2014 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.