Datadog Agent

The present repository contains the source code of the Datadog Agent version 7 and version 6. Please refer to the Agent user documentation for information about differences between Agent v5, Agent v6 and Agent v7. Additionally, we provide a list of prepackaged binaries for an easy install process here

Note: the source code of Datadog Agent v5 is located in the dd-agent repository.

Documentation

The general documentation of the project, including instructions for installation and development, is located under the docs directory of the present repo.

Getting started

To build the Agent you need:

• Go 1.13 or later. You'll also need to set your $GOPATH and have $GOPATH/bin in your path.
• Python 2.7 or 3.7+ along with development libraries.
• Python dependencies. You may install these with pip install -r requirements.txt This will also pull in Invoke if not yet installed.
• CMake version 3.12 or later and a C++ compiler

Note: you may want to use a python virtual environment to avoid polluting your system-wide python environment with the agent build/dev dependencies. You can create a virtual environment using virtualenv and then use the invoke parameter --python-home-2=<venv_path> and/or --python-home-3=<venv_path> (depending on the python versions you are using) to use the virtual environment's interpreter and libraries. By default, this environment is only used for dev dependencies listed in requirements.txt.

Note: You may have previously installed invoke via brew on MacOS, or pip in any other platform. We recommend you use the version pinned in the requirements file for a smooth development/build experience.

Builds and tests are orchestrated with invoke, type invoke --list on a shell to see the available tasks.

To start working on the Agent, you can build the master branch:

1. Checkout the repo: git clone https://github.com/DataDog/datadog-agent.git $GOPATH/src/github.com/DataDog/datadog-agent.
2. cd into the project folder: cd $GOPATH/src/github.com/DataDog/datadog-agent.
3. Install project's dependencies: invoke deps. Make sure that $GOPATH/bin is in your $PATH otherwise this step might fail.
4. Create a development datadog.yaml configuration file in dev/dist/datadog.yaml, containing a valid API key: api_key: <API_KEY>
5. Build the agent with invoke agent.build --build-exclude=systemd. By default, the Agent will be built to use Python 3 but you can select which Python version you want to use:
   • invoke agent.build --python-runtimes 2 for Python2 only
   • invoke agent.build --python-runtimes 3 for Python3 only
   • invoke agent.build --python-runtimes 2,3 for both Python2 and Python3 You can specify a custom Python location for the agent (useful when using virtualenvs): invoke agent.build --python-runtimes 2,3 --python-home-2=$GOPATH/src/github.com/DataDog/datadog-agent/venv2 --python-home-3=$GOPATH/src/github.com/DataDog/datadog-agent/venv3. Running invoke agent.build:
   • Discards any changes done in bin/agent/dist.
   • Builds the Agent and writes the binary to bin/agent/agent.
   • Copies files from dev/dist to bin/agent/dist. See https://github.com/DataDog/datadog-agent/blob/master/dev/dist/README.md for more information. If you built an older version of the agent, you may have the error make: *** No targets specified and no makefile found. Stop.. To solve the issue, you should remove CMakeCache.txt from rtloader folder with rm rtloader/CMakeCache.txt.

Please refer to the Agent Developer Guide for more details. For instructions on setting up a windows dev environment, refer to Windows Dev Env.

Run

You can run the agent with:

./bin/agent/agent run -c bin/agent/dist/datadog.yaml

The file bin/agent/dist/datadog.yaml is copied from dev/dist/datadog.yaml by invoke agent.build and must contain a valid api key.

Contributing code

You'll find information and help on how to contribute code to this project under the docs/dev directory of the present repo.