opentelemetry-python
OpenTelemetry Python is the official reference implementation of the OpenTelemetry API and SDK for Python, providing libraries for collecting traces, metrics, and logs from applications. It enables teams to instrument Python code and export observability data to various backends without vendor lock-in.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | open-telemetry/opentelemetry-python |
| Owner | open-telemetry |
| Primary language | Python |
| License | Apache-2.0 — OSI-approved |
| Stars | 2.5k |
| Forks | 931 |
| Open issues | 419 |
| Latest release | v1.43.0 (2026-06-24) |
| Last updated | 2026-07-06 |
| Source | https://github.com/open-telemetry/opentelemetry-python |
What opentelemetry-python is
The project consists of modular packages (opentelemetry-api, opentelemetry-sdk) following the OpenTelemetry specification, with separate exporter and propagator packages for integration with different backends. Traces and Metrics are stable; Logs are in development with planned breaking changes. Minimum Python 3.10+, actively maintained with weekly community meetings.
Get the opentelemetry-python source
Clone the repository and explore it locally.
git clone https://github.com/open-telemetry/opentelemetry-python.gitcd opentelemetry-python# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Separate library dependencies (opentelemetry-api) from SDK (opentelemetry-sdk); libraries should depend only on API to defer SDK choice to applications, reducing transitive bloat.
- Logs signal will introduce breaking changes during stabilization; pin major versions and monitor release notes if using experimental log instrumentation.
- Manual instrumentation requires explicit span/metric creation; auto-instrumentation for popular frameworks is available in opentelemetry-python-contrib, not in this core repo.
- Context propagation and trace correlation require configuration of appropriate propagators (W3C Trace Context, Jaeger, etc.); default propagator choice affects distributed tracing correctness.
- Exporter selection and configuration (batch vs. on-demand, endpoint, authentication) must align with backend availability and network topology; test exporter reliability in your environment.
When to avoid it — and what to weigh
- Logs Signal Production Dependencies — If your application requires production-grade log collection today, defer adoption. Logs signal is marked 'Development' with breaking changes planned; use stable Traces and Metrics only.
- Python < 3.10 Environments — Project requires Python 3.10+. Older Python versions are unsupported within 6 months of their end-of-life; legacy applications on Python 3.8–3.9 cannot use current releases.
- Minimal Dependencies / Constraint-Heavy Environments — OpenTelemetry introduces additional runtime dependencies and initialization overhead. Highly resource-constrained environments (embedded, serverless with tight memory limits) may need careful profiling.
- Proprietary / Non-Standard Observability Workflows — OpenTelemetry is standards-based and compatible with standard backends. Highly customized in-house telemetry pipelines may require significant adapter work or may not benefit from the ecosystem.
License & commercial use
Licensed under Apache License 2.0 (Apache-2.0), a permissive open-source license that permits commercial use, modification, and distribution with attribution and liability disclaimers.
Apache-2.0 explicitly permits commercial use, derivative works, and proprietary integration. No copyleft restrictions. Suitable for commercial products and closed-source applications. However, consult your legal team for indemnification and warranty implications in high-risk deployments.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Strong |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Strong |
| Assessment confidence | High |
No security vulnerabilities disclosed in the provided data. Project holds OpenSSF Best Practices badge, suggesting security process maturity. Considerations: (1) Exporter endpoints must be secured (TLS, authentication); misconfiguration could expose telemetry in transit. (2) Instrumentation may emit sensitive data (PII, tokens) in trace/metric tags; require data sanitization policies in instrumentation code. (3) Python version support aligns with security patch cycles; applications on unsupported versions face known vulnerabilities. (4) Dependencies are modular; audit exporter and propagator transitive dependencies for supply-chain risk.
Alternatives to consider
Datadog APM SDK (dd-trace-py)
Vendor-specific but tightly integrated with Datadog platform; simpler setup if already committed to Datadog, but locks you into that backend and pricing model.
Elastic APM Agent for Python
Tailored to Elastic Stack; strong Elasticsearch integration and Kibana visualization, but requires commitment to Elastic ecosystem and offers less flexibility for multi-vendor setups.
Jaeger Python Client (jaeger-client)
Lightweight, Jaeger-specific; good for organizations standardized on Jaeger, but lacks the multi-signal (metrics, logs) and multi-backend flexibility of OpenTelemetry.
Build on opentelemetry-python with DEV.co software developers
Ready to adopt vendor-neutral instrumentation? Review the getting-started guide, assess exporter compatibility with your backend, and pilot with a non-critical service to validate integration and performance impact.
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opentelemetry-python FAQ
Do I have to use the opentelemetry-sdk, or can I use a third-party SDK?
Is the Logs signal production-ready?
What Python versions are supported?
Does OpenTelemetry automatically instrument my code?
Work with a software development agency
DEV.co helps companies turn open-source tools like opentelemetry-python into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source observability stack.
Evaluate OpenTelemetry Python for Your Observability Stack
Ready to adopt vendor-neutral instrumentation? Review the getting-started guide, assess exporter compatibility with your backend, and pilot with a non-critical service to validate integration and performance impact.