01Module 02 - Python Observability OverviewStructured logging, metrics, distributed tracing, error tracking, and health checks - the three pillars of production observability in Python.02Structured LoggingPython logging module internals, structlog, JSON logs, correlation IDs, log levels, and log aggregation - from print() to production-grade structured logs.03Metrics with PrometheusPrometheus client library, counter/gauge/histogram/summary, FastAPI instrumentation, custom metrics, alerting rules, and Grafana dashboards.04Distributed TracingOpenTelemetry, Jaeger, trace context propagation, custom spans, baggage, and sampling strategies for Python microservices.05Error TrackingSentry integration, custom error grouping, breadcrumbs, release tracking, and building production error workflows in Python.06Health Checks and ReadinessLiveness vs readiness probes, dependency health checks, health check libraries, SLOs, and building production-grade health endpoints in Python.
