Lesson 11: Observability and Monitoring in Distributed Systems
Observability is a foundational pillar for maintaining reliable and scalable distributed systems. In this lesson, we explore the core concepts, tools, and best practices to monitor system health, trace issues, and gain visibility into complex microservices architectures.
1. Monitoring vs Observability
Explanation: Monitoring is the act of collecting and displaying system data, while observability is the ability to understand what’s happening inside a system from the outside.
- Monitoring: Predefined checks, metrics, and alerts.
- Observability: Deep system understanding via logs, metrics, and traces.
Example Use Case: An engineer uses monitoring to detect high CPU usage, but uses observability (logs and traces) to pinpoint the root cause in a downstream service.
2. The Three Pillars: Logs, Metrics, Traces
Explanation: A well-observed system provides all three pillars for complete visibility.
- Logs: Structured/unstructured text output for error tracking.
- Metrics: Numerical indicators (e.g., latency, error rates, CPU).
- Traces: End-to-end request journeys across services.
Example Use Case: Debugging a user request that failed due to a timeout by correlating metrics, logs, and distributed trace information.
3. Observability Tooling
Explanation: Tools help collect, store, and visualize observability data effectively.
- Prometheus: Time-series metrics collection and querying.
- Grafana: Dashboards and visualization for metrics.
- OpenTelemetry: Open standard for instrumentation (metrics, logs, traces).
- Jaeger/Zipkin: Distributed tracing tools.
Example Use Case: Setting up Prometheus and Grafana to monitor request latency across services and visualize performance over time.
4. Alerting and Dashboards
Explanation: Proactive alerting and intuitive dashboards empower teams to act before users are affected.
- Threshold Alerts: Triggered when a metric crosses a predefined threshold.
- Anomaly Detection: ML-based alerts for unexpected behaviors.
- Custom Dashboards: Tailored views for different teams (DevOps, SRE, backend).
Example Use Case: An SRE team configures alerts for 5xx error spikes and sets up dashboards by region for real-time incident response.
Conclusion
Observability is key to operating modern distributed systems reliably. With the right tools, practices, and a focus on the three pillars—logs, metrics, and traces—teams can build and operate systems with confidence, detect issues faster, and reduce downtime.