Monitoring Skill

Implement monitoring, logging, and observability for applications.

When to Use

Use this skill when the user wants to:

• Set up metrics collection
• Create monitoring dashboards
• Configure alerting rules
• Implement structured logging
• Set up distributed tracing
• Work with observability tools
• Performance monitoring

Monitoring Stack Options

Agent-based

• Prometheus: Metrics collection
• Grafana: Visualization and dashboards
• Node Exporter: Node metrics
• CAdvisor: Container metrics

Serverless

• CloudWatch: AWS monitoring
• Cloud Logging: Google Cloud Logging
• App Insights: Azure Application Insights

Distributed Tracing

• Jaeger: OpenTracing compatible
• Zipkin: Distributed tracing
• OpenTelemetry: Tracing standard

Metrics Types

Metrics

• Counter: Monotonically increasing
• Gauge: Can go up or down
• Histogram: Value distribution
• Summary: Value distribution + quantiles

Logging

• Structured logs (JSON)
• Log levels (ERROR, WARN, INFO, DEBUG)
• Correlation IDs for tracing
• Log rotation and retention

Best Practices

• Log everything important: Errors, warnings, user actions
• Use meaningful log levels: Don’t spam with DEBUG
• Structure logs: JSON format with fields
• Don’t log secrets: Never log passwords, tokens, API keys
• Add context: Include request ID, user info, timestamps
• Monitor what matters: Core business metrics, errors, SLIs

Alerting Strategy

• Alarm on anomalies: Systematic errors, unusual patterns
• Set reasonable thresholds: Avoid alert fatigue
• Escalate appropriately: Critical issues get attention
• Keep SLOs in mind: Alerts should align with SLOs

Deliverables

• Monitoring configuration files
• Dashboard definition
• Alerting rules
• Log aggregation setup
• Documentation

Quality Checklist

• Critical metrics are monitored
• Alerts are actionable
• Logs are structured and searchable
• Metrics are properly labeled
• Distributed tracing is configured
• SLO/SLA alignment