Skip to content
All Skills

Observability Edot Python Instrument

Instrument a Python application with the Elastic Distribution of OpenTelemetry (EDOT) Python agent for automatic tracing, metrics, and logs. Use when adding observability to a Python service that has no existing APM agent.

Software Engineering|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "observability-edot-python-instrument-42aa5d53" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
# EDOT Python Instrumentation

Read the setup guide before making changes:

- [EDOT Python setup](https://www.elastic.co/docs/reference/opentelemetry/edot-sdks/python/setup)
- [EDOT Python configuration](https://www.elastic.co/docs/reference/opentelemetry/edot-sdks/python/configuration)
- [OpenTelemetry Python auto-instrumentation](https://opentelemetry.io/docs/zero-code/python/)

## Guidelines

1. Install `elastic-opentelemetry` via pip (add to `requirements.txt` or equivalent)
1. Run `edot-bootstrap --action=install` during image build to install auto-instrumentation packages for detected
   libraries
1. Wrap the application entrypoint with `opentelemetry-instrument` — e.g. `opentelemetry-instrument gunicorn app:app` or
   `opentelemetry-instrument python app.py`. Without this, no telemetry is collected
1. Set exactly three required environment variables:
   - `OTEL_SERVICE_NAME`
   - `OTEL_EXPORTER_OTLP_ENDPOINT` — must be the **managed OTLP endpoint** or **EDOT Collector** URL. Never use an APM
     Server URL (no `apm-server`, no `:8200`, no `/intake/v2/events`)
   - `OTEL_EXPORTER_OTLP_HEADERS` — `"Authorization=ApiKey <key>"` or `"Authorization=Bearer <token>"`
1. Do NOT set `OTEL_TRACES_EXPORTER`, `OTEL_METRICS_EXPORTER`, or `OTEL_LOGS_EXPORTER` — the defaults are already
   correct
1. Do NOT add code-level SDK setup (no `TracerProvider`, no `configure_azure_monitor`, etc.) —
   `opentelemetry-instrument` handles everything
1. Never run both classic `elastic-apm` and EDOT on the same application

## Examples

See the [EDOT Python setup guide](https://www.elastic.co/docs/reference/opentelemetry/edot-sdks/python/setup) for
complete examples.
#elastic#elasticsearch#kibana#observability#performance#optimizationpythonpipelasticedot-bootstrapopentelemetry-instrument

Related Skills

More skills in Software Engineering

Accessibility Standards

Comprehensive web accessibility standards based on WCAG 2.2 AA, with 38+ anti-patterns, legal enforcement context (EAA, ADA Title II), WAI-ARIA patterns, and framework-specific fixes for modern web frameworks and libraries.

#github-copilot#accessibilityMIT

Accord

Authoring unified specification packages across Business/Development/Design teams via staged elaboration (L0 Vision → L1 Requirements → L2 Team Detail → L3 Acceptance Criteria). No code. Use when authoring cross-team specs, building L0-L3 packages, or aligning Biz/Dev/Design on a single source of truth.

#broad-capability#developmentMIT

Acquire Codebase Knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

#github-copilot#documentationMIT

Acreadiness Assess

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

#github-copilot#planningMIT

Acreadiness Generate Instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

#github-copilot#skillMIT

Acreadiness Policy

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

#github-copilot#planningMIT