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This page walks Technology Partners through the specific steps to create and submit an integration or Marketplace offering to Datadog.
Follow the instructions to create either an Agent-based integration, or an API-based integration.
If you are creating an Agent-based integration, follow the steps outlined.
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. This code is hosted in GitHub.
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).
See Agent Check Documentation to learn how to set up an Agent Check and return to this page to proceed with the rest of the steps.
If you are creating an API-based integration, you are required to use OAuth. Follow the steps outlined.
OAuth is a standard that integrations can use to provide client applications with secure delegated access. OAuth works over HTTPS and authorizes devices, APIs, servers, and applications with access tokens rather than credentials.
See OAuth Client Documentation to set up your OAuth Integration and return to this page to proceed with the rest of the steps.
If your platform is incompatible with OAuth, reach out to the Datadog Ecosystems team for an exception.
Information about the Datadog data types helps users understand what your integration does. If you are pulling data out of Datadog, specify the specific data type under the queried data section. If you are sending data to Datadog, specify the specific data type under the submitted data section. Certain fields may require more information.
If your integration sends in metrics:
metadata.csv file.Example:
| metric_name | metric_type | interval | unit_name | per_unit_name | description | orientation | integration | short_name | curated_metric | sample_tags |
|---|---|---|---|---|---|---|---|---|---|---|
| <partner_name>.<category>.<measurement> | Select from the following list | Collection interval in seconds | Select from following list | Unit sub-division | Short description | Value indicating trend | integration ID | human-readable abbreviated version without integration name | internal use, leave blank | list of example tags |
| datadog.system.cpu.usage | gauge | 60 | percent | The percentage of total CPU used | 0 | datadog | sys cpu usage | “host_name,region” |
If your integration sends in logs, a log pipeline is required.
Datadog Integrations support out-of-the-box content that is ready to use upon installation. Include content such as dashboards, monitor templates, and SIEM detection rules to help users find value in your integration.
Provide contact details to your support team.
For the initial launch, leave it as is. For future updates, specify feature additions, changes, fixes, and removals as new versions.
Additional helpful documentation, links, and articles:
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