Datadog

Datadog is an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform. Datadog uses a Go-based agent, supports multiple cloud service providers including Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform and Red Hat OpenShift, and over 450 application integrations.

In Datadog:

Obtain and record the following details:

1. api-key: Follow the Datadog instructions here. In order to create an API key, the user will need the Manage API Keys permission.
2. application-key: Follow the Datadog instructions here. The Application key owner must have, at minimum, the DataDog Read Only Role.
3. product: A logical grouping to associate the integration with in the Relyance AI platform. If only one group of data will be used, you may wish to simply use your company name.
4. env: The Datadog environment that Relyance AI should monitor; in the screenshot below the value will be "prod".

Permissions Relyance needs

Datadog authorises by key pair rather than by scope:

Relyance requests read-only access. If the application key's owner later loses their role, the key stops working — so create it under an account that will outlast the person who set the integration up.

In Relyance AI:

1. Login to your Relyance AI account.
2. Navigate to the Settings (bottom-left corner).
3. Select Integrations.
4. Search and locate the Sentry integration card and click on it.
5. Click on the Add Connection button on the top right.
6. Provide a meaningful name for the integration and click on the Add button.
7. In the Overview section, select the integration features you wish to enable for the integration, review the Scope and Permission, and Endpoint details and click on Continue. For more details, seeIntegration Features.
8. In the Connection section, provide the appropriate values and click on Continue,
   • Connection Name: This property allows you to update the integration specified in Step 6. If you have multiple integrations for the same vendor, you may want to assign distinct names to each. This helps streamline filtering by Discovery Source across the Inventory, Visual Maps, Assets, and Data Flow Analysis pages.
   • Rescan Frequency: This property allows you to configure how often Relyance executes scans against this Vendor connection.
   • Business Atlas Associations (required): the business entities or products that newly discovered third parties, services and assets from this integration are attributed to. Choose at least one from the Select Associations dropdown — the wizard will not advance past this step without one. For more details, see Business Atlas.
9. In the Authentication section, provide the details captured from the Datadog application and click on Authenticate.
10. This step applies only if the Data Inspection check box was enabled in Step 7. In the Data Inspection section, provide the appropriate values and click on Continue,
    • Minimum Confidence Level: This property adjusts the sensitivity of the Data Inspection feature. Lower likelihoods (e.g., unlikely) offer more coverage but may produce false positives, while higher sensitivity (e.g., very likely) provides greater accuracy but less coverage.
11. Review the configuration summary from the Completion section and click on Finish.
12. Confirm the integration Status reflects Connected.

Authentication methods and fields

Pick one of these under Authentication Method on the connection wizard's Authentication step. This table is generated from the integration catalog, so it always matches what the form actually asks for.

Manage this integration with Terraform

Connections for this integration can be managed as code with the Relyance Terraform provider. Non-secret fields go in auth.params; secret fields go in auth.secrets_wo, which is write-only — never stored in Terraform state. Rotate secrets by bumping auth.secrets_wo_version.

resource "relyance_integration_connection" "datadog" {
  vendor = "datadog"
  name   = "<your connection name>"

  auth = {
    method = "account-credentials"
    params = {
      accounts = jsonencode([
        {
          api-key = ""
          application-key = ""
          datadog-url = "https://api.datadoghq.com/"
          env = ""
          product = ""
        }
      ])
      data_storage_location = "us"
    }
  }

  scans = { "data-inspection" = { enabled = true } }
}