Join the Beta!

Unity Monitoring is in private beta. To request access, reach out to Datadog support.

Datadog Real User Monitoring (RUM) enables you to visualize and analyze user journeys of your application’s individual users.


Datadog supports Unity Monitoring for iOS and Android for Unity LTS 2022+.

Datadog does not support Desktop (Windows, Mac, or Linux), console, or web deployments from Unity. If you have a game or application and want to use Datadog RUM to monitor its performance, create a ticket with Datadog support.

Specify application details in the UI

  1. In Datadog, navigate to Digital Experience > Add an Application.
  2. Choose Unity as the application type.
  3. Provide an application name to generate a unique Datadog application ID and client token.
  4. To disable automatic user data collection for either client IP or geolocation data, uncheck the boxes for those settings.

To ensure the safety of your data, you must use a client token. For more information about setting up a client token, see the Client Token documentation.

Sample RUM sessions

You can control the data your application sends to Datadog RUM during instrumentation of the RUM Unity SDK. Specify the Session Sample Rate as a percentage between 0 and 100 in the Project Settings window in Unity.


  1. Install External Dependency Manager for Unity (EDM4U). This can be done using Open UPM.

  2. Add the Datadog SDK Unity package from its Git URL at https://github.com/DataDog/unity-package.

  3. Configure your project to use Gradle templates, and enable both Custom Main Template and Custom Gradle Properties Template.

  4. In the iOS setting for External Dependency Manager (Assets > External Dependency Manager > iOS Resolver > Settings), disable the Link frameworks statically option and ensure that Allow the same pod to be in multiple targets is enabled.

  5. If you build and receive Duplicate class errors (common in Unity 2022.x), add the following block in the dependencies block in your mainTemplate.gradle:

    constraints {
         implementation("org.jetbrains.kotlin:kotlin-stdlib-jdk8:1.8.0") {
             because("kotlin-stdlib-jdk8 is now a part of kotlin-stdlib")
  6. After adding the Datadog Unity SDK, configure Datadog from your Project Settings:

    1. Enable Datadog and RUM
    2. Copy your Client Token and Application Id into the fields in the settings window.
    3. Verify that your Site is correct.

Using Datadog

In order to be compliant with data protection and privacy policies, the Datadog Unity SDK requires setting a tracking consent value.

The trackingConsent setting can be one of the following values:

  • TrackingConsent.Pending: The Unity SDK starts collecting and batching the data but does not send it to Datadog. The Unity SDK waits for the new tracking consent value to decide what to do with the batched data.
  • TrackingConsent.Granted: The Unity SDK starts collecting the data and sends it to Datadog.
  • TrackingConsent.NotGranted: The Unity SDK does not collect any data. No logs are sent to Datadog.

Before Datadog sends any data, we need to confirm the user’s Tracking Consent. This is set to TrackingConsent.Pending during initialization, and needs to be set to TrackingConsent.Granted before Datadog sends any information.



You can intercept and send logs from Unity’s default debug logger by enabling the option and threshold in your projects settings.

Datadog maps the Unity levels to the following in Datadog’s Logging Levels:

Unity LogTypeDatadog Log Level

You can access this default logger to add attributes or tags through the DatadogSdk.DefaultLogger property.

You can also create additional loggers for more fine grained control of thresholds, service names, logger names, or to supply additional attributes.

var logger = DatadogSdk.Instance.CreateLogger(new DatadogLoggingOptions()
    SendNetworkInfo = true,
    DatadogReportingThreshold = DdLogLevel.Debug,
logger.Info("Hello from Unity!");

logger.Debug("Hello with attributes", new()
    { "my_attribute", 122 },
    { "second_attribute", "with_value" },
    { "bool_attribute", true },
        "nested_attribute", new Dictionary<string, object>()
            { "internal_attribute", 1.234 },

Real User Monitoring (RUM)

Manual Scene (View) Tracking

To manually track new Scenes (Views in Datadog), use the StartView and StopView methods:

public void Start()
    DatadogSdk.Instance.Rum.StartView("My View", new()
        { "view_attribute": "active" }

Starting a new view automatically ends the previous view.

Automatic Scene Tracking

You can also set Enable Automatic Scene Tracking in your Project Settings to enable automatically tracking active scenes. This uses Unity’s SceneManager.activeSceneChanged event to automatically start new scenes.

Web Requests / Resource Tracking

Datadog offers DatadogTrackedWebRequest, which is a UnityWebRequest wrapper intended to be a drop-in replacement for UnityWebRequest. DatadogTrackedWebRequest enables Datadog Distributed Tracing.

To enable Datadog Distributed Tracing, you must set the First Party Hosts in your project settings to a domain that supports distributed tracing. You can also modify the sampling rate for distributed tracing by setting the Tracing Sampling Rate.

First Party Hosts does not allow wildcards, but matches any subdomains for a given domain. For example, api.example.com matches staging.api.example.com and prod.api.example.com, but not news.example.com.