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python-observability

Python observability patterns including structured logging, metrics

by wshobsonFree

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#1805in AI Skills
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Description

python-observability is an agent skill from the wshobson/agents collection for instrumenting Python applications with structured logs, metri…

Highlights

  • Structured JSON logging
  • Prometheus metrics collection
  • Distributed tracing across services
  • Correlation ID propagation
  • Guidance for production debugging and dashboards
  • Installs with the skills CLI

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python-observability FAQ

What does observability add?

Structured logs, metrics and traces that let you understand what happened in production without deploying new code.

Why structured logs?

Logs emitted as JSON with consistent fields can be searched and alerted on, as the skill explains.

What are correlation IDs?

IDs passed along a chain of requests so one request can be followed across services.

Which metrics system does it mention?

Prometheus, along with distributed tracing across services.

How do I install it?

Run npx skills add https://github.com/wshobson/agents --skill python-observability.

What security audits does it have?

skills.sh lists three audits: Gen Agent Trust Hub Pass, Socket Pass and Snyk Pass.

What are the best python-observability alternatives?

Popular alternatives to python-observability include observability-and-instrumentation, distributed-tracing and golang-samber-slog. See all python-observability alternatives

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