1. Dashboard Rule#

Folder: Compute
Dashboard: ECS Service - Overview

Rows:
    Service Health:
        desired 是否满足，CPU / memory 是否接近瓶颈，container 是否频繁 restart

    Scaling Signals:
        running / desired / pending 的关系，CPU / memory 长期趋势，deployment / capacity gap 症状

为什么不保留四层:

ECS service 原生 CloudWatch metrics 不多。
如果没有接入 ALB metrics 和应用 Prometheus metrics，拆成 Overview / Drilldown / Capacity / Debug 很容易重复。

所以 ECS service 这类 dashboard 更适合压成 1 到 2 个 row：
    第一行回答服务当前是否健康
    第二行回答是否需要扩缩容，或者 deployment / capacity provider 是否有问题

2. Overview#

Panel Metrics Why
Service running tasks RunningTaskCount, DesiredTaskCount running 小于 desired 是服务容量不足或部署异常
CPU usage CPUUtilization ECS service 的 compute saturation
Memory usage MemoryUtilization ECS service 最常见 scaling / OOM signal
Request rate app http_requests_total or ALB RequestCount 没有流量上下文时 CPU / memory 很难判断
Error rate app 5xx or ALB HTTPCode_Target_5XX_Count 用户侧失败信号
Latency app latency p95/p99 or ALB TargetResponseTime 用户侧慢请求信号

request / error / latency 来源:

ECS namespace:
    不提供完整 request / error / latency。
    ECS metrics 主要回答 service / task 资源和运行状态。

ALB, if service is HTTP behind ALB:
    RequestCount
    HTTPCode_Target_5XX_Count
    HTTPCode_ELB_5XX_Count
    TargetResponseTime

App metrics, recommended:
    http_requests_total
    http_request_duration_seconds
    error counter by route / status / exception

3. Dashboard Panels#

Row Panel Metrics Why
Service Health Running vs desired tasks RunningTaskCount, DesiredTaskCount 第一优先级先看服务有没有满足 desired
Service Health CPU utilization CPUUtilization 判断 CPU 是否接近 target tracking 或 service saturation
Service Health Memory utilization MemoryUtilization 最常见的 ECS autoscaling / OOM 风险信号
Service Health Pending task count PendingTaskCount 发现部署卡住、容量不足、任务无法及时拉起
Scaling Signals Task count by service RunningTaskCount, DesiredTaskCount, PendingTaskCount 区分扩容中、部署卡住、capacity 不足
Scaling Signals CPU / memory trend CPUUtilization, MemoryUtilization 判断现有 scaling target 是否合适
Scaling Signals Scaling / deployment symptoms DesiredTaskCount - RunningTaskCount, PendingTaskCount 快速识别 desired-running gap 和 pending 压力

4. YACE Metrics#

如果 ECS dashboard 使用 aws_ecs_* metrics，需要 YACE 采集 AWS/ECS。应用请求量、错误率、延迟仍然建议由应用 /metrics 或 ALB metrics 提供。

YACE config:

apiVersion: v1alpha1
sts-region: ap-northeast-1
discovery:
  jobs:
    - type: AWS/ECS
      regions:
        - ap-northeast-1
      customTags:
        - key: environment
          value: uat
      period: 300
      length: 600
      nilToZero: true
      metrics:
        - name: CPUUtilization
          statistics: [Average]
        - name: MemoryUtilization
          statistics: [Average]
    - type: ECS/ContainerInsights
      regions:
        - ap-northeast-1
      customTags:
        - key: environment
          value: uat
      period: 300
      length: 600
      nilToZero: true
      metrics:
        - name: RunningTaskCount
          statistics: [Average]
        - name: DesiredTaskCount
          statistics: [Average]
        - name: PendingTaskCount
          statistics: [Average]

Container Insights note:

下面这些指标不属于标准 AWS/ECS 这段 YACE 配置:
    RunningTaskCount
    DesiredTaskCount
    PendingTaskCount

它们来自:
    ECS/ContainerInsights

如果 dashboard 要展示 task count / pending，
需要同时采:
    AWS/ECS
    ECS/ContainerInsights

如果 ECS service behind ALB，并且 dashboard 要显示 request / error / latency，YACE 还需要采集 AWS/ApplicationELB。ALB 的详细 YACE 配置见 ALB YACE Dashboard。

确认 metric name:

{__name__=~"aws_ecs_.*"}

5. Do Not Put In Overview#

不要放:
    每个 container 的所有 cgroup counters
    runtime GC / heap / goroutine / event loop 全量明细
    每个 deployment event 的长文本

原因:
    ECS overview 应该优先回答 desired 是否满足、资源是否饱和、用户体验是否变差
Backward Dashboard PromQL Reference YACE Dashboard Forward