Overview

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

Setup

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.

Installing

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. The package URL is https://github.com/DataDog/unity-package.git.

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

4. 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")
        }
   }
   

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.

Specify Datadog settings in the Unity UI

After installing the Datadog Unity SDK, you need to set Datadog’s settings in the Unity UI. Navigate to your Project Settings and click on the Datadog section on the left hand side. You will see the following screen:

The following parameters are available:

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.

Using Datadog

Setting tracking consent

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.

DatadogSdk.Instance.SetTrackingConsent(TrackingConsent.Granted);

Logging

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:

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()
{
    NetworkInfoEnabled = 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 },
        }
    },
});

The following parameters are available when creating a new logger:

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.

Sending data when device is offline

RUM ensures availability of data when your user device is offline. In case of low-network areas, or when the device battery is too low, all the RUM events are first stored on the local device in batches.

Each batch follows the intake specification. They are sent as soon as the network is available, and the battery is high enough to ensure the Datadog SDK does not impact the end user’s experience. If the network is not available while your application is in the foreground, or if an upload of data fails, the batch is kept until it can be sent successfully.

This means that even if users open your application while offline, no data is lost. To ensure the SDK does not use too much disk space, the data on the disk is automatically discarded if it gets too old.