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Watadot Aws Cloudwatch

Observability and monitoring by Watadot Studio. Log tailing and metric extraction.
Watadot Studio 的可观测性与监控,支持日志追踪和指标提取。
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概述

AWS CloudWatch Skills

Observability and automated monitoring patterns.

🚀 Core Commands

Log Insights

# Live tail of a Log Group
aws logs tail /aws/lambda/<function-name> --follow

# Query logs for errors (last 1h)
aws logs filter-log-events --log-group-name <name> --filter-pattern "ERROR" --start-time $(date -d '1 hour ago' +%s000) --query "events[].message"

Metrics & Alarms

# List active alarms with state
aws cloudwatch describe-alarms --query "MetricAlarms[?StateValue==\`ALARM\`].{Name:AlarmName,Reason:StateReason}" --output table

# Get CPU utilization metric for EC2
aws cloudwatch get-metric-statistics --namespace AWS/EC2 --metric-name CPUUtilization --dimensions Name=InstanceId,Value=<id> --period 3600 --statistics Average --start-time 2026-03-15T00:00:00 --end-time 2026-03-16T00:00:00

Dashboard Orchestration

# List dashboard names
aws cloudwatch list-dashboards --query "DashboardEntries[].DashboardName"

🧠 Best Practices

  1. Retention Policies: Don't keep logs forever. Set retention (e.g., 14 days) to save storage costs.
  2. Log Streams: Use unique log stream names for different agent instances to avoid interleaving.
  3. Structured Logging: Log in JSON format to make filtering and automated analysis via OpenClaw easier.
  4. Alarms: Set up billing alarms to catch sudden spikes in AWS usage early.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 03:57 安全 安全

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