otel-launcher-python
opentelemetry-python-contrib
otel-launcher-python | opentelemetry-python-contrib | |
---|---|---|
2 | 3 | |
18 | 617 | |
- | 4.7% | |
4.1 | 9.4 | |
6 months ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
otel-launcher-python
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Auto-Instrumentation Is Magic: Using OpenTelemetry Python with Lightstep
If you thought it was easy-peasey to send OTel data to Lightstep ร la auto-instrumentation agent, then itโs even easier to do it via the OTel Python Launcher! Think of it as an OTel wrapper to make it extra-easy to send data to Lightstep, by having a bunch of things pre-configured for you to lower that barrier to entry.
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Observability Mythbusters: OpenTelemetry to Lightstep 3 Ways in Go IS Possible!
We currently have Launchers for Go, Python, Java, and Node.JS.
opentelemetry-python-contrib
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OpenTelemetry for Python: The Hard Way
In my last blog post, I showed yโall how to instrument Python code with OpenTelemetry (OTel), ร la auto-instrumentation. You may also recall from that post that I recommended using the Python auto-instrumentation binary even for non-auto-instrumented libraries, because it abstracts all that pesky OTel config stuff so nicely. When you use it, along with any applicable Python auto-instrumentation libraries (installed courtesy of opentelemetry-bootstrap), it takes care of context propagation across related services for you.
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Auto-Instrumentation Is Magic: Using OpenTelemetry Python with Lightstep
More specifically, auto-instrumentation uses shims or bytecode instrumentation agents to intercept your code at runtime or at compile-time to add tracing and metrics instrumentation to the libraries and frameworks you depend on. The beauty of auto-instrumentation is that it requires a minimum amount of effort. Sit back, relax, and enjoy the show. A number of popular Python libraries are auto-instrumented, including Flask and Django. You can find the full list here.
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Do i really want to mess with OpenTelemetry, or just hook straight into Datadog
And sure, there's gaps and those are awful when you get to them. But writing minimal tracing integration is pretty easy. This is the full source of the psycopg2 instrumentation. https://github.com/open-telemetry/opentelemetry-python-contrib/blob/main/instrumentation/opentelemetry-instrumentation-psycopg2/src/opentelemetry/instrumentation/psycopg2/__init__.py
What are some alternatives?
otel-launcher-go - Launcher, a Lightstep Distro for OpenTelemetry Go ๐
vector - A high-performance observability data pipeline.
opentelemetry-examples - Example code and resources for working with OpenTelemetry, provided by Lightstep
debug-toolkit - A modern code-injection framework for Python. Like Pyrasite but Kubernetes-aware.
otel-launcher-java - Launcher, a Lightstep Distro for OpenTelemetry Java ๐
opentelemetry-python - OpenTelemetry Python API and SDK
opentelemetry.io - The OpenTelemetry website and documentation
thanos - Highly available Prometheus setup with long term storage capabilities. A CNCF Incubating project.
opentelemetry-specification - Specifications for OpenTelemetry
CPython - The Python programming language