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Overview
Private actions allow you to run actions against services in your private network, such as Kubernetes clusters, internal hosts, databases, and internal APIs, without exposing those services to the public internet. You run them through a private action runner that you deploy in your environment, either inside the Datadog Agent (recommended) or as a standalone runner. Datadog products that use private actions include Workflow Automation, App Builder, Datadog MCP, and Bits AI investigations.
Private actions rely on two layers:
- Private action runner executes the actions. It runs in your network, receives action tasks from Datadog, runs each task against the target service, and returns the result to Datadog.
- The authorization layer is managed in Datadog. It defines which users and products can run which actions on which runners, and grants or denies each action before it reaches a runner. The actions a runner is allowed to run are also restricted on the Agent side, by the actions allowlist in the Agent configuration (
datadog.yaml).
Private action runner
The private action runner is the component you deploy in your environment to run private actions. It opens an outbound connection to Datadog, polls for action tasks, runs each task against the target service, and returns the result.
The private action runner is available in two forms: a standalone runner that you deploy and manage yourself, or a runner built into the Datadog Agent.
| Runner in the Datadog Agent | Standalone runner |
|---|
| What it is | A component of the Datadog Agent, turned on with a single configuration flag. | A dedicated container you can install and manage independently of the Datadog Agent. |
| Best when | You already run the Datadog Agent and want to manage the runner through the Agent life cycle. | You need an integration that is not yet available in the Agent. |
| Status | Recommended for new deployments. | Supported (maintenance mode). |
Datadog recommends running the private action runner in the Datadog Agent
For installation steps, see Set up a private action runner in the Datadog Agent or Set up a standalone runner.
Authorization models
Datadog offers two authorization models. The model a runner uses is set when the runner is enrolled, and it follows from the runner’s ownership. For more information, see Enrollment and ownership.
- Execution Policies apply to runners in the Datadog Agent and are built for managing access at scale. Instead of creating a separate connection for each integration on each runner, you use Agent tags to target one or more sets of runners. Execution Policies also give you fine-grained control: you can allow or deny specific actions or sets of actions, and apply integration-specific scopes, such as the target Kubernetes namespaces for a Kubernetes action.
- Connections are available for both the runner in the Agent and the standalone runner. They can be attached to at most a single runner. A connection can store credentials for a service.
To compare the two models and decide which one applies to your runner, see Authorize private actions.
Next steps
- New to private actions: Follow Getting started with private actions to deploy a runner and run your first action.
- You have a runner in the Datadog Agent and want fleet-wide access control: Authorize it with Execution Policies.
- You have a runner in the Agent or a standalone runner and want to authorize a single runner: Authorize it with Connections.
Further reading
Additional helpful documentation, links, and articles:
