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python-observability

Instrument Python applications with structured logging, metrics, and distributed tracing.

1|Updated Apr 27, 2026
Search Tags:#logging#python#metrics#observability#tracing#opentelemetry
One-click install
npx skills add https://github.com/haxlys/skills --skill python-observability-haxlys
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-observability
Source: https://github.com/haxlys/skills/tree/main/vendored/wshobson-agents/plugins/python-development/skills/python-observability
Command: npx skills add https://github.com/haxlys/skills --skill python-observability-haxlys

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python applications struggle to be observable, making debugging production issues slow and uncertain.

Core Features & Use Cases

  • Structured Logging: Emit JSON logs with consistent fields to support filtering and correlation.
  • Distributed Tracing: Propagate traces across services to diagnose latency and failures.
  • Metrics & Dashboards: Collect key metrics for dashboards and alerts.
  • Use Case: Instrument a microservice to correlate logs, metrics, and traces in a single view for incident analysis.

Quick Start

Configure a starter observability setup for a Python project to enable structured logging, metrics, and tracing.

Frequently Asked Questions about python-observability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is structured logging and how does it improve Python observability?▼

Distributed tracing propagates traces across Python microservices to diagnose latency and failures. It uses correlation IDs and optional OpenTelemetry tracing to provide an end-to-end view, correlating logs, metrics, and traces for incident analysis.

How do I instrument a Python microservice for logs, metrics, and tracing?▼

To instrument a Python microservice, configure a starter observability setup to emit JSON-structured logs, collect key metrics for dashboards, and propagate traces across services. This correlates all telemetry in a single view for incident analysis.

Can I use OpenTelemetry tracing with my existing Python application?▼

Yes, you can use OpenTelemetry tracing with your Python application. The setup provides optional OpenTelemetry tracing to propagate correlation IDs and traces across services, diagnosing latency and failures without disrupting current operations.

Does this observability setup require specific dependencies for Python apps?▼

No specific dependencies are required to start. You can configure a starter observability setup directly in your Python project to enforce JSON-structured logs, consistent field naming, and correlation IDs for immediate production debugging.

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