python-observability-patterns
SolidObservability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.
Install
Quality Score: 85/100
Skill Content
Details
- Author
- aiskillstore
- Repository
- aiskillstore/marketplace
- Created
- 7 months ago
- Last Updated
- today
- Language
- Python
- License
- None
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
observability-logging-metrics-tracing
Add or review logging, metrics, or tracing so production behavior is diagnosable — structured logs, correlation IDs, RED/USE metrics, and OpenTelemetry spans. Use when instrumenting code, debugging a production issue, or wiring monitoring. Triggers on logging, metrics, tracing, observability, instrument, debug production, monitoring.
observability
Structured logging, debugging (pdb/ipdb), profiling (cProfile/line_profiler), and performance monitoring. Use when adding logging, debugging issues, or optimizing performance. TRIGGER when: logging, debug, profiling, performance monitoring, metrics, stack trace. DO NOT TRIGGER when: feature implementation, testing, documentation, config changes.
principle-observability
Observability principles — logs vs metrics vs traces, structured logging, distributed tracing, span/trace context, cardinality control, OpenTelemetry, SLI/SLO/SLA, RED method, USE method, alerting on symptoms vs causes. Auto-load when adding logging, choosing a metric, instrumenting distributed tracing, debating cardinality, defining SLIs/SLOs, designing alerts, or discussing observability budgets.