Monitoring & Logging

Overview

Monitoring and logging (Observability) are critical for understanding the health and performance of your system in production. You cannot fix what you cannot measure. A robust observability stack helps you detect issues before your users do and provides the data needed for root cause analysis.

Key Concepts

1. The Four Golden Signals

  • Latency: Time it takes to service a request.
  • Traffic: Demand placed on the system (e.g., HTTP requests per second).
  • Errors: Rate of requests that fail (e.g., HTTP 500s).
  • Saturation: How "full" your service is (e.g., CPU/Memory usage).

2. Monitoring vs. Logging

  • Monitoring: Real-time dashboards and alerts based on metrics (e.g., Prometheus, Grafana).
  • Logging: Detailed records of events that occurred in the system (e.g., ELK Stack - Elasticsearch, Logstash, Kibana).

3. Distributed Tracing

A way to track a single request as it moves through multiple microservices.

  • Technologies: Jaeger, Zipkin, AWS X-Ray.

Trade-offs & Considerations

  • Cost: Storing large amounts of logs and metrics can be expensive. Log rotation and sampling are necessary.
  • Alert Fatigue: Too many alerts can lead to "noise," where developers start ignoring them. Alerts should be actionable.
  • Overhead: Adding extensive monitoring and tracing can add a small amount of latency to your application.

Further Reading