Observability¶
Monitoring, logging, and observability practices for production systems.
Three Pillars of Observability¶
Metrics¶
- System Performance: CPU, memory, disk, network
- Application Metrics: Response time, throughput, error rates
- Business Metrics: User engagement, conversion rates
- Time Series Data: Historical trends and patterns
Logs¶
- Application Logs: Debug and error information
- System Logs: OS and infrastructure events
- Audit Logs: Security and compliance tracking
- Structured Logging: JSON format for better parsing
Traces¶
- Distributed Tracing: Request flow across services
- Performance Analysis: Identify bottlenecks
- Error Tracking: Root cause analysis
- Service Dependencies: Understand system interactions
Tools Overview¶
Prometheus¶
- Metrics Collection: Pull-based monitoring system
- PromQL: Powerful query language
- Alerting: Rule-based alert generation
- Service Discovery: Automatic target discovery
Grafana¶
- Visualization: Rich dashboards and charts
- Data Sources: Multiple backend support
- Alerting: Visual alert management
- Templating: Dynamic dashboard creation
ELK Stack¶
- Elasticsearch: Search and analytics engine
- Logstash: Log processing pipeline
- Kibana: Data visualization platform
- Beats: Lightweight data shippers
Monitoring Strategy¶
Golden Signals¶
- Latency: Response time of requests
- Traffic: Rate of requests per second
- Errors: Rate of failed requests
- Saturation: Resource utilization
SLI/SLO/SLA¶
- SLI: Service Level Indicators (metrics)
- SLO: Service Level Objectives (targets)
- SLA: Service Level Agreements (contracts)
Best Practices¶
- Monitor What Matters: Focus on user-impacting metrics
- Set Meaningful Alerts: Avoid alert fatigue
- Use Dashboards: Visual representation of system health
- Implement Logging Standards: Consistent log formats
- Practice Incident Response: Prepare for outages