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cloudwatch

@itsmostafa · 收录于 1 周前 · 上游提交 2 个月前

AWS CloudWatch monitoring for logs, metrics, alarms, and dashboards. Use when setting up monitoring, creating alarms, querying logs with Insights, configuring metric filters, building dashboards, or troubleshooting application issues.

适合你,如果正在使用 AWS 并需要集中监控云资源

/ 下载安装
cloudwatch.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add itsmostafa/aws-agent-skills/cloudwatch
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- itsmostafa/aws-agent-skills/cloudwatch
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify itsmostafa/aws-agent-skills/cloudwatch
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 4ab904a · 表述以原文为准
它做什么

装上后,Claude 能帮你管理 AWS CloudWatch 监控,包括查看指标、查询日志、创建告警、设置仪表盘和排查问题。

什么时候触发

当你需要设置 AWS 资源监控、创建告警、用 Insights 查询日志、配置指标筛选、构建仪表盘或排查应用问题时触发。

装好后可以这样说
Claude 会生成对应的 CLI 或 boto3 命令。
Claude 会生成仪表盘 JSON 和创建命令。
技能原文 SKILL.md作者撰写 · MIT · 4ab904a

AWS CloudWatch

Amazon CloudWatch provides monitoring and observability for AWS resources and applications. It collects metrics, logs, and events, enabling you to monitor, troubleshoot, and optimize your AWS environment.

Table of Contents
  • [Core Concepts](#core-concepts)
  • [Common Patterns](#common-patterns)
  • [CLI Reference](#cli-reference)
  • [Best Practices](#best-practices)
  • [Troubleshooting](#troubleshooting)
  • [References](#references)
Core Concepts
Metrics

Time-ordered data points published to CloudWatch. Key components:

  • Namespace: Container for metrics (e.g., AWS/Lambda)
  • Metric name: Name of the measurement (e.g., Invocations)
  • Dimensions: Name-value pairs for filtering (e.g., FunctionName=MyFunc)
  • Statistics: Aggregations (Sum, Average, Min, Max, SampleCount, pN)
Logs

Log data from AWS services and applications:

  • Log groups: Collections of log streams
  • Log streams: Sequences of log events from same source
  • Log events: Individual log entries with timestamp and message
Alarms

Automated actions based on metric thresholds:

  • States: OK, ALARM, INSUFFICIENT_DATA
  • Actions: SNS notifications, Auto Scaling, EC2 actions
Common Patterns
Create a Metric Alarm

AWS CLI:

# CPU utilization alarm for EC2
aws cloudwatch put-metric-alarm \
  --alarm-name "HighCPU-i-1234567890abcdef0" \
  --metric-name CPUUtilization \
  --namespace AWS/EC2 \
  --statistic Average \
  --period 300 \
  --threshold 80 \
  --comparison-operator GreaterThanThreshold \
  --evaluation-periods 2 \
  --dimensions Name=InstanceId,Value=i-1234567890abcdef0 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:alerts \
  --ok-actions arn:aws:sns:us-east-1:123456789012:alerts

boto3:

import boto3

cloudwatch = boto3.client('cloudwatch')

cloudwatch.put_metric_alarm(
    AlarmName='HighCPU-i-1234567890abcdef0',
    MetricName='CPUUtilization',
    Namespace='AWS/EC2',
    Statistic='Average',
    Period=300,
    Threshold=80.0,
    ComparisonOperator='GreaterThanThreshold',
    EvaluationPeriods=2,
    Dimensions=[
        {'Name': 'InstanceId', 'Value': 'i-1234567890abcdef0'}
    ],
    AlarmActions=['arn:aws:sns:us-east-1:123456789012:alerts'],
    OKActions=['arn:aws:sns:us-east-1:123456789012:alerts']
)
Lambda Error Rate Alarm
aws cloudwatch put-metric-alarm \
  --alarm-name "LambdaErrorRate-MyFunction" \
  --metrics '[
    {
      "Id": "errors",
      "MetricStat": {
        "Metric": {
          "Namespace": "AWS/Lambda",
          "MetricName": "Errors",
          "Dimensions": [{"Name": "FunctionName", "Value": "MyFunction"}]
        },
        "Period": 60,
        "Stat": "Sum"
      },
      "ReturnData": false
    },
    {
      "Id": "invocations",
      "MetricStat": {
        "Metric": {
          "Namespace": "AWS/Lambda",
          "MetricName": "Invocations",
          "Dimensions": [{"Name": "FunctionName", "Value": "MyFunction"}]
        },
        "Period": 60,
        "Stat": "Sum"
      },
      "ReturnData": false
    },
    {
      "Id": "errorRate",
      "Expression": "errors/invocations*100",
      "Label": "Error Rate",
      "ReturnData": true
    }
  ]' \
  --threshold 5 \
  --comparison-operator GreaterThanThreshold \
  --evaluation-periods 3 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:alerts
Query Logs with Insights
# Find errors in Lambda logs
aws logs start-query \
  --log-group-name /aws/lambda/MyFunction \
  --start-time $(date -d '1 hour ago' +%s) \
  --end-time $(date +%s) \
  --query-string '
    fields @timestamp, @message
    | filter @message like /ERROR/
    | sort @timestamp desc
    | limit 50
  '

# Get query results
aws logs get-query-results --query-id <query-id>

boto3:

import boto3
import time

logs = boto3.client('logs')

# Start query
response = logs.start_query(
    logGroupName='/aws/lambda/MyFunction',
    startTime=int(time.time()) - 3600,
    endTime=int(time.time()),
    queryString='''
        fields @timestamp, @message
        | filter @message like /ERROR/
        | sort @timestamp desc
        | limit 50
    '''
)

query_id = response['queryId']

# Wait for results
while True:
    result = logs.get_query_results(queryId=query_id)
    if result['status'] == 'Complete':
        break
    time.sleep(1)

for row in result['results']:
    print(row)
Create Metric Filter

Extract metrics from log patterns:

# Create metric filter for error count
aws logs put-metric-filter \
  --log-group-name /aws/lambda/MyFunction \
  --filter-name ErrorCount \
  --filter-pattern "ERROR" \
  --metric-transformations \
    metricName=ErrorCount,metricNamespace=MyApp,metricValue=1,defaultValue=0
Publish Custom Metrics
import boto3

cloudwatch = boto3.client('cloudwatch')

cloudwatch.put_metric_data(
    Namespace='MyApp',
    MetricData=[
        {
            'MetricName': 'OrdersProcessed',
            'Value': 1,
            'Unit': 'Count',
            'Dimensions': [
                {'Name': 'Environment', 'Value': 'Production'},
                {'Name': 'OrderType', 'Value': 'Standard'}
            ]
        }
    ]
)
Create Dashboard
cat > dashboard.json << 'EOF'
{
  "widgets": [
    {
      "type": "metric",
      "x": 0, "y": 0, "width": 12, "height": 6,
      "properties": {
        "title": "Lambda Invocations",
        "metrics": [
          ["AWS/Lambda", "Invocations", "FunctionName", "MyFunction"]
        ],
        "period": 60,
        "stat": "Sum",
        "region": "us-east-1"
      }
    },
    {
      "type": "log",
      "x": 12, "y": 0, "width": 12, "height": 6,
      "properties": {
        "title": "Recent Errors",
        "query": "SOURCE '/aws/lambda/MyFunction' | filter @message like /ERROR/ | limit 20",
        "region": "us-east-1"
      }
    }
  ]
}
EOF

aws cloudwatch put-dashboard \
  --dashboard-name MyAppDashboard \
  --dashboard-body file://dashboard.json
CLI Reference
Metrics Commands

| Command | Description | |---------|-------------| | aws cloudwatch put-metric-data | Publish custom metrics | | aws cloudwatch get-metric-data | Retrieve metric values | | aws cloudwatch get-metric-statistics | Get aggregated statistics | | aws cloudwatch list-metrics | List available metrics |

Alarms Commands

| Command | Description | |---------|-------------| | aws cloudwatch put-metric-alarm | Create or update alarm | | aws cloudwatch describe-alarms | List alarms | | aws cloudwatch set-alarm-state | Manually set alarm state | | aws cloudwatch delete-alarms | Delete alarms |

Logs Commands

| Command | Description | |---------|-------------| | aws logs create-log-group | Create log group | | aws logs put-log-events | Write log events | | aws logs filter-log-events | Search log events | | aws logs start-query | Start Insights query | | aws logs put-metric-filter | Create metric filter | | aws logs put-retention-policy | Set log retention |

Best Practices
Metrics
  • Use dimensions wisely — too many creates metric explosion
  • Aggregate before publishing — batch custom metrics
  • Use high-resolution metrics (1-second) only when needed
  • Set meaningful units for custom metrics
Alarms
  • Use composite alarms for complex conditions
  • Set appropriate evaluation periods to avoid flapping
  • Include OK actions to track recovery
  • Use anomaly detection for dynamic thresholds
Logs
  • Set retention policies — don't keep logs forever
  • Use structured logging (JSON) for better querying
  • Create metric filters for key events
  • Use Contributor Insights for top-N analysis
Cost Optimization
  • Delete unused dashboards
  • Reduce log retention for non-critical logs
  • Avoid high-resolution metrics unless necessary
  • Use log subscription filters instead of polling
Troubleshooting
Missing Metrics

Causes:

  • Service not publishing yet (wait 1-5 minutes)
  • Wrong namespace/dimensions
  • Detailed monitoring not enabled (EC2)

Debug:

# List metrics for a namespace
aws cloudwatch list-metrics \
  --namespace AWS/Lambda \
  --dimensions Name=FunctionName,Value=MyFunction
Alarm Stuck in INSUFFICIENT_DATA

Causes:

  • Metric not being published
  • Dimensions mismatch
  • Evaluation period too short

Debug:

# Check if metric has data
aws cloudwatch get-metric-statistics \
  --namespace AWS/Lambda \
  --metric-name Invocations \
  --dimensions Name=FunctionName,Value=MyFunction \
  --start-time $(date -d '1 hour ago' -u +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 60 \
  --statistics Sum
Log Events Not Appearing

Causes:

  • IAM permissions missing
  • CloudWatch Logs agent not running
  • Log group doesn't exist

Debug:

# Check log streams
aws logs describe-log-streams \
  --log-group-name /aws/lambda/MyFunction \
  --order-by LastEventTime \
  --descending \
  --limit 5
High CloudWatch Costs

Check usage:

# Get PutLogEvents usage
aws cloudwatch get-metric-statistics \
  --namespace AWS/Logs \
  --metric-name IncomingBytes \
  --dimensions Name=LogGroupName,Value=/aws/lambda/MyFunction \
  --start-time $(date -d '7 days ago' -u +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 86400 \
  --statistics Sum
References
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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