Co-Pilot
Updated 12 hours ago

cloudwatch

Iitsmostafa
1.0k
itsmostafa/aws-agent-skills/skills/cloudwatch
80
Agent Score

💡 Summary

A comprehensive skill for monitoring AWS resources using CloudWatch, covering logs, metrics, alarms, and dashboards.

🎯 Target Audience

Cloud EngineersDevOps EngineersSREs (Site Reliability Engineers)Backend Developers managing AWS infrastructureIT Operations Managers

🤖 AI Roast:It's essentially a well-organized cheat sheet for CloudWatch commands, proving that sometimes the best skill is knowing how to read the manual.

Security AnalysisLow Risk

The skill executes AWS CLI commands and boto3 calls, which require IAM credentials with broad CloudWatch permissions. The main risk is credential exposure or privilege escalation if the agent's environment is compromised. Mitigation: Use temporary, scoped IAM credentials with least-privilege policies instead of long-lived access keys.


name: cloudwatch description: 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. last_updated: "2026-01-07" doc_source: https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/

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

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

5-Dim Analysis
Clarity9/10
Novelty4/10
Utility10/10
Completeness9/10
Maintainability8/10
Pros & Cons

Pros

  • Extensive coverage of CloudWatch features with practical examples.
  • Clear CLI and boto3 code snippets for immediate implementation.
  • Includes troubleshooting guides and best practices for real-world use.

Cons

  • Primarily a documentation wrapper with limited novel automation.
  • Assumes pre-existing AWS CLI/boto3 setup and IAM knowledge.
  • Could benefit from more advanced automation or integration patterns.

Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.

Copyright belongs to the original author itsmostafa.