Observability & Monitoring
Structured logging, Sentry error tracking, correlation IDs, APM (Application Performance Monitoring), DB metrics, health checks, alerting
1What is observability in the context of a Django application?
What is observability in the context of a Django application?
Resposta
Observability is the ability to understand the internal state of a system from its external outputs. It relies on three pillars: logs (events), metrics (numerical data) and traces (request paths). Unlike simple monitoring that checks if a system works, observability enables diagnosing why a problem occurs.
2What are the three pillars of observability?
What are the three pillars of observability?
Resposta
The three pillars of observability are logs (recording discrete events), metrics (numerical data aggregated over time) and traces (tracking a request's path through services). These three elements combined enable understanding the behavior of a distributed system.
3How to configure structured logging in Django with JSON format?
How to configure structured logging in Django with JSON format?
Resposta
Structured logging consists of emitting logs as structured data (JSON) rather than free text. This facilitates automated analysis by tools like ELK or Datadog. The python-json-logger library is commonly used with Django's standard logging system to format logs as JSON.
What is the main advantage of structured logging compared to traditional text logs?
What is a correlation ID and why is it essential in a distributed architecture?
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