This page walks Technology Partners through how to create a Datadog Agent integration, which you can list as out-of-the-box on the Integrations page, or for a price on the Marketplace page. Agent-based integrations
Agent-based integrations use the Datadog Agent to submit data through checks written by the developer. Checks can emit metrics, events, and service checks into a customer’s Datadog account. The Agent itself can submit logs as well, but that is configured outside of the check.
The implementation code for these integrations is hosted by Datadog. Agent integrations are best suited for collecting data from systems or applications that live in a local area network (LAN) or virtual private cloud (VPC). Creating an Agent integration requires you to publish and deploy your solution as a Python wheel (.whl).
You can include out-of-the-box assets such as monitors, dashboards, and log pipelines with your Agent-based integration. When a user clicks Install on your integration tile, they are prompted to follow the setup instructions, and all out-of-the-box dashboards will appear in their account. Other assets, such as log pipelines, will appear for users after proper installation and configuration of the integration. Development process
The process to build an Agent-based integration looks like this:
The required Datadog Agent integration development tools include the following:
Select a tab for instructions on building an out-of-the-box Agent-based integration on the Integrations page, or an Agent-based integration on the Marketplace page.
To build an out-of-the-box integration:
Create a dd directory:
mkdir $HOME/dd && cd $HOME/dd
The Datadog Development Toolkit expects you to work in the $HOME/dd/ directory. This is not mandatory, but working in a different directory requires additional configuration steps.
git clone git@github.com:<YOUR USERNAME>/integrations-extras.git
Create a feature branch to work in:
git switch -c <YOUR INTEGRATION NAME> origin/master
Configure the developer tool
The Agent Integration Developer Tool allows you to create scaffolding when you are developing an integration by generating a skeleton of your integration tile’s assets and metadata. For instructions on installing the tool, see Install the Datadog Agent Integration Developer Tool.
To configure the tool for the integrations-extras repository:
Optionally, if your integrations-extras repo is somewhere other than $HOME/dd/, adjust the ddev configuration file:
ddev config set extras "/path/to/integrations-extras"
Set integrations-extras as the default working repository:
ddev config set repo extras
Create your integration
Once you’ve downloaded Docker, installed an appropriate version of Python, and prepared your development environment, you can start creating an Agent-based integration.
The following instructions use an example integration called Awesome. Follow along using the code from Awesome, or replace Awesome with your own code, as well as the name of your integration within the commands. For example, use ddev create <your-integration-name> instead of ddev create Awesome. Create scaffolding for your integration
The ddev create command runs an interactive tool that creates the basic file and path structure (or scaffolding) necessary for an Agent-based integration.
Before you create your first integration directory, try a dry-run using the -n/--dry-run flag, which doesn’t write anything to the disk:
ddev create -n Awesome
This command displays the path where the files would have been written, as well as the structure itself. Make sure the path in the first line of output matches your repository location.
Run the command without the -n flag. The tool asks you for an email and name and then creates the files you need to get started with an integration. If you are creating an integration for the Datadog Marketplace, ensure that your directory follows the pattern of {partner name}_{integration name}.
ddev create Awesome