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.
The general documentation of the project, including instructions for installation and development, is located under the docs directory of the present repo.
To build the Agent you need:
- Go 1.16 or later. You'll also need to set your
$GOPATH/binin your path.
- Python 3.7+ along with development libraries for tooling. You will also need Python 2.7 if you are building the Agent with Python 2 support.
- Python dependencies. You may install these with
pip install -r requirements.txtThis 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
(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
Note: You may have previously installed
invoke via brew on MacOS, or
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 --list on a shell
to see the available tasks.
To start working on the Agent, you can build the
Checkout the repo:
git clone https://github.com/DataDog/datadog-agent.git $GOPATH/src/github.com/DataDog/datadog-agent.
cd into the project folder:
Install go tools:
Install go dependencies:
invoke deps. Make sure that
$GOPATH/binis in your
$PATHotherwise this step might fail.
Create a development
datadog.yamlconfiguration file in
dev/dist/datadog.yaml, containing a valid API key:
Build the agent with
invoke agent.build --build-exclude=systemd.
By default, the Agent will be built to use Python 3 but you can select which Python version you want to use:
invoke agent.build --python-runtimes 2for Python2 only
invoke agent.build --python-runtimes 3for Python3 only
invoke agent.build --python-runtimes 2,3for both Python2 and Python3
You can specify a custom Python location for the agent (useful when using virtualenvs):
invoke agent.build \ --python-runtimes 2,3 \ --python-home-2=$GOPATH/src/github.com/DataDog/datadog-agent/venv2 \ --python-home-3=$GOPATH/src/github.com/DataDog/datadog-agent/venv3 .
- Discards any changes done in
- Builds the Agent and writes the binary to
- Copies files from
https://github.com/DataDog/datadog-agent/blob/main/dev/dist/README.mdfor 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
Run tests using
invoke test. During development, add the
--skip-linters option to skip straight to the tests.
invoke test --targets=./pkg/aggregator/... --skip-linters
When testing code that depends on rtloader, build and install it first.
invoke rtloader.make && invoke rtloader.install invoke test --targets=./pkg/collector/python --skip-linters
You can run the agent with:
./bin/agent/agent run -c bin/agent/dist/datadog.yaml
bin/agent/dist/datadog.yaml is copied from
invoke agent.build and must contain a valid api key.
You'll find information and help on how to contribute code to this project under
docs/dev directory of the present repo.