Getting Started with Feature Flag Data in RUM

Feature flag tracking is available in the RUM Browser SDK. To start, set up RUM browser monitoring. You need the Browser RUM SDK version >= 4.25.0.

To start collecting feature flag data, initialize the RUM SDK and configure the enableExperimentalFeatures initialization parameter with ["feature_flags"].

  import { datadogRum } from '@datadog/browser-rum';

  // Initialize Datadog Browser SDK
  datadogRum.init({
    ...
    enableExperimentalFeatures: ["feature_flags"],
    ...
});

window.DD_RUM.onReady(function() {
    window.DD_RUM.init({
      ...
      enableExperimentalFeatures: ["feature_flags"],
      ...
    })
})

window.DD_RUM &&
    window.DD_RUM.init({
      ...
      enableExperimentalFeatures: ["feature_flags"],
      ...
    })

Feature flag tracking is available in the RUM iOS SDK. To start, set up RUM iOS monitoring. You need the iOS RUM SDK version >= 1.16.0.

Feature flag tracking is available in the RUM Android SDK. To start, set up RUM Android monitoring. You need the Android RUM SDK version >= 1.18.0.

Feature flag tracking is available for your Flutter applications. To start, set up RUM Flutter monitoring. You need the Flutter Plugin version >= 1.3.2.

Feature flag tracking is available for your React Native applications. To start, set up RUM React Native monitoring. You need the React Native RUM SDK version >= 1.7.0.

Initialize Amplitude’s SDK and and create an exposure listener reporting feature flag evaluations to Datadog using the following snippet of code:

For more information about initializing Amplitude’s SDK, see Amplitude’s JavaScript SDK documentation.

  const experiment = Experiment.initialize("CLIENT_DEPLOYMENT_KEY", {
    exposureTrackingProvider: {
      track(exposure: Exposure)  {
        // Send the feature flag when Amplitude reports the exposure
        datadogRum.addFeatureFlagEvaluation(exposure.flag_key, exposure.variant);
      }
    }
  })

Initialize Amplitude’s SDK and create an inspector reporting feature flag evaluations to Datadog using the snippet of code below.

For more information about initializing Amplitude’s SDK, see Amplitude’s iOS SDK documentation.

  class DatadogExposureTrackingProvider : ExposureTrackingProvider {
    func track(exposure: Exposure) {
      // Send the feature flag when Amplitude reports the exposure
      if let variant = exposure.variant {
        Global.rum.addFeatureFlagEvaluation(name: exposure.flagKey, value: variant)
      }
    }
  }

  // In initialization:
  ExperimentConfig config = ExperimentConfigBuilder()
    .exposureTrackingProvider(DatadogExposureTrackingProvider(analytics))
    .build()

Initialize Amplitude’s SDK and create an inspector reporting feature flag evaluations to Datadog using the snippet of code below.

For more information about initializing Amplitude’s SDK, see Amplitude’s Android SDK documentation.

  internal class DatadogExposureTrackingProvider : ExposureTrackingProvider {
    override fun track(exposure: Exposure) {
        // Send the feature flag when Amplitude reports the exposure
        GlobalRumMonitor.get().addFeatureFlagEvaluation(
            exposure.flagKey,
            exposure.variant.orEmpty()
        )
    }
  }

  // In initialization:
  val config = ExperimentConfig.Builder()
      .exposureTrackingProvider(DatadogExposureTrackingProvider())
      .build()

Amplitude does not support this integration. Create a ticket with Amplitude to request this feature.

Each time a feature flag is evaluated, add the following function to send the feature flag information to RUM:

datadogRum.addFeatureFlagEvaluation(key, value);

Each time a feature flag is evaluated, add the following function to send the feature flag information to RUM:

Global.rum.addFeatureFlagEvaluation(key, value);

Each time a feature flag is evaluated, add the following function to send the feature flag information to RUM:

GlobalRumMonitor.get().addFeatureFlagEvaluation(key, value);

Each time a feature flag is evaluated, add the following function to send the feature flag information to RUM:

DatadogSdk.instance.rum?.addFeatureFlagEvaluation(key, value);

Each time a feature flag is evaluated, add the following function to send the feature flag information to RUM:

DdRum.addFeatureFlagEvaluation(key, value);

Initialize DevCycle’s SDK and subscribe to the variableEvaluated event, choosing to subscribe to all variable evaluations variableEvaluated:* or particular variable evaluations variableEvaluated:my-variable-key.

For more information about initializing DevCycle’s SDK, see DevCycle’s JavaScript SDK documentation and for more information about DevCycle’s event system, see DevCycle’s SDK Event Documentation.

const user = { user_id: "<USER_ID>" };
const dvcOptions = { ... };
const dvcClient = initialize("<DVC_CLIENT_SDK_KEY>", user, dvcOptions);
...
dvcClient.subscribe(
    "variableEvaluated:*",
    (key, variable) => {
        // track all variable evaluations
        datadogRum.addFeatureFlagEvaluation(key, variable.value);
    }
)
...
dvcClient.subscribe(
    "variableEvaluated:my-variable-key",
    (key, variable) => {
        // track a particular variable evaluation
        datadogRum.addFeatureFlagEvaluation(key, variable.value);
    }
)

DevCycle does not support this integration. Create a ticket with DevCycle to request this feature.

DevCycle does not support this integration. Create a ticket with DevCycle to request this feature.

DevCycle does not support this integration. Create a ticket with DevCycle to request this feature.

DevCycle does not support this integration. Create a ticket with DevCycle to request this feature.

Initialize Flagsmith’s SDK with the datadogRum option, which reports feature flag evaluations to Datadog using the snippet of code shown below.

Optionally, you can configure the client so that Flagsmith traits are sent to Datadog via datadogRum.setUser(). For more information about initializing Flagsmith’s SDK, check out Flagsmith’s JavaScript SDK documentation.

 // Initialize the Flagsmith SDK
 flagsmith.init({
     datadogRum: {
         client: datadogRum,
         trackTraits: true,
     },
     ...
 })

Flagsmith does not support this integration. Create a ticket with Flagsmith to request this feature.

Flagsmith does not support this integration. Create a ticket with Flagsmith to request this feature.

Flagsmith does not support this integration. Create a ticket with Flagsmith to request this feature.

Flagsmith does not currently support this integration. Create a ticket with Flagsmith to request this feature.

Initialize LaunchDarkly’s SDK and create an inspector reporting feature flags evaluations to Datadog using the snippet of code shown below.

For more information about initializing LaunchDarkly’s SDK, see LaunchDarkly’s JavaScript SDK documentation.

const client = LDClient.initialize("<CLIENT_SIDE_ID>", "<CONTEXT>", {
  inspectors: [
    {
      type: "flag-used",
      name: "dd-inspector",
      method: (key: string, detail: LDClient.LDEvaluationDetail) => {
        datadogRum.addFeatureFlagEvaluation(key, detail.value);
      },
    },
  ],
});

LaunchDarkly does not support this integration. Create a ticket with LaunchDarkly to request this feature.

LaunchDarkly does not support this integration. Create a ticket with LaunchDarkly to request this feature.

LaunchDarkly does not support this integration. Create a ticket with LaunchDarkly to request this feature.

LaunchDarkly does not currently support this integration. Create a ticket with LaunchDarkly to request this feature.

Initialize Split’s SDK and and create an impression listener reporting feature flag evaluations to Datadog using the following snippet of code:

For more information about initializing Split’s SDK, see Split’s JavaScript SDK documentation.

const factory = SplitFactory({
    core: {
      authorizationKey: "<APP_KEY>",
      key: "<USER_ID>",
    },
    impressionListener: {
      logImpression(impressionData) {
          datadogRum
              .addFeatureFlagEvaluation(
                  impressionData.impression.feature,
                  impressionData.impression.treatment
              );
    },
  },
});

const client = factory.client();

Initialize Split’s SDK and create an inspector reporting feature flag evaluations to Datadog using the snippet of code below.

For more information about initializing Split’s SDK, see Split’s iOS SDK documentation.

  let config = SplitClientConfig()
  // Send the feature flag when Split reports the impression
  config.impressionListener = { impression in
      if let feature = impression.feature,
          let treatment = impression.treatment {
          Global.rum.addFeatureFlagEvaluation(name: feature, value: treatment)
      }
  }

Initialize Split’s SDK and create an inspector reporting feature flag evaluations to Datadog using the snippet of code below.

For more information about initializing Split’s SDK, see Split’s Android SDK documentation.

  internal class DatadogSplitImpressionListener : ImpressionListener {
    override fun log(impression: Impression) {
        // Send the feature flag when Split reports the impression
        GlobalRumMonitor.get().addFeatureFlagEvaluation(
            impression.split(),
            impression.treatment()
        )
    }
    override fun close() {
    }
  }

  // In initialization:
  val apikey = BuildConfig.SPLIT_API_KEY
  val config = SplitClientConfig.builder()
      .impressionListener(DatadogSplitImpressionListener())
      .build()

Initialize Split’s SDK and create an inspector reporting feature flag evaluations to Datadog using the snippet of code below.

For more information about initializing Split’s SDK, see Split’s Flutter plugin documentation.

  StreamSubscription<Impression> impressionsStream = _split.impressionsStream().listen((impression) {
    // Send the feature flag when Split reports the impression
    final split = impression.split;
    final treatment = impression.treatment;
    if (split != null && treatment != null) {
      DatadogSdk.instance.rum?.addFeatureFlagEvaluation(split, treatment);
    }
  });

Initialize Split’s SDK and and create an impression listener reporting feature flag evaluations to Datadog using the following snippet of code:

For more information about initializing Split’s SDK, see Split’s React Native SDK documentation.

const factory = SplitFactory({
    core: {
      authorizationKey: "<APP_KEY>",
      key: "<USER_ID>",
    },
    impressionListener: {
      logImpression(impressionData) {
          DdRum
              .addFeatureFlagEvaluation(
                  impressionData.impression.feature,
                  impressionData.impression.treatment
              );
    },
  },
});

const client = factory.client();

Feature flag tracking is available in the RUM Browser SDK. For detailed set up instructions, visit Getting started with feature flag data in RUM.

1. Update your Browser RUM SDK version 4.25.0 or above.

2. Initialize the RUM SDK and configure the enableExperimentalFeatures initialization parameter with ["feature_flags"].

3. Initialize Statsig’s SDK (>= v4.34.0) and implement the gateEvaluationCallback option as shown below:

    await statsig.initialize('client-<STATSIG CLIENT KEY>',
    {userID: '<USER ID>'},
    {     
        gateEvaluationCallback: (key, value) => {
            datadogRum.addFeatureFlagEvaluation(key, value);
        }
    }
    ); 
   

Statsig does not support this integration. Contact support@statsig.com to request this feature.

Statsig does not support this integration. Contact support@statsig.com to request this feature.

Statsig does not support this integration. Contact support@statsig.com to request this feature.

Statsig does not currently support this integration. Contact support@statsig.com to request this feature.