Kubernetes library injection

This directory contains scripts and a Docker image for providing the ddtrace package via a Kubernetes init container which allows users to easily instrument Python applications without requiring changes to the application image.

The Dockerfile defines the image that is published for ddtrace which is used as a Kubernetes InitContainer. Kubernetes runs it before deployment pods start. It is responsible for providing the files necessary to run ddtrace in an arbitrary downstream application container. It also provides a script to copy the necessary files to a given directory.

The dl_wheels.py script provides a portable set of ddtrace wheels. It is responsible for downloading the published wheels of ddtrace and its dependencies.

The Datadog Admission Controller injects the InitContainer with a new volume mount to the application deployment. The script to copy files out of the InitContainer is run to copy the files to the volume. The PYTHONPATH environment variable is injected into the application container along with the volume mount.

The files copied to the volume are:

• sitecustomize.py: Python module that gets run automatically on interpreter startup when it is detected in the PYTHONPATH. When executed, it updates the Python path further to include the ddtrace_pkgs/ directory and then calls import ddtrace.bootstrap.sitecustomize which performs automatic instrumentation.
• ddtrace_pkgs/: Directory containing the ddtrace package and its dependencies for each Python version, platform and architecture.

The PYTHONPATH environment variable is set to the shared volume directory which contains sitecustomize.py and ddtrace_pkgs. The environment variable is injected into the the application container. This enables the sitecustomize.py file to execute on any Python interpreter startup which results in the automatic instrument being applied to the application.