Practical Observability with Python

What is structured logging in Python? Learn how to replace text logs with JSON-based structured logging using Loguru for production observability.

How do you propagate request context in Python async applications? Learn how to use ContextVars to keep request IDs consistent across async tasks and threads.

How do you set up OpenTelemetry tracing in Python? Learn three levels of instrumentation: zero-code, programmatic and manual, with Jaeger visualization.

How do you trace requests across microservices in Python? Learn distributed tracing with OpenTelemetry, W3C Trace Context and automatic context propagation.

How do you add custom metrics with OpenTelemetry in Python? Learn to use Counters, Histograms and Gauges with Prometheus and Grafana for production monitoring.

How do you correlate logs, traces and metrics in OpenTelemetry? Learn the Pivot Workflow to drill from a Grafana dashboard spike to the exact log line that caused it.

How do you record errors properly with OpenTelemetry in Python? Learn why try/except blocks hide failures from dashboards and how to make every error visible in traces and metrics.

Why do you need the OpenTelemetry Collector? Learn the first-principles case for adding a Collector to your observability pipeline, with architecture diagrams and the 5-Why analysis.

How do you set up an OpenTelemetry Collector pipeline with Docker Compose? Step-by-step guide to configuring receivers, processors and exporters for Jaeger and Prometheus.

How do you deploy the OpenTelemetry Collector in production? Learn Agent vs Gateway topology, debugging tools, self-observability and production hardening strategies.

How do you sample traces and scrub PII with OpenTelemetry? Learn tail sampling to keep 100% of error traces and attribute redaction to remove sensitive data before export.

What is the RED method for monitoring? Learn how to build actionable Grafana dashboards using Rate, Errors and Duration metrics, extended with Cost and Quality for AI services.