Android SDK observability reference

Overview

This topic documents how to get started with the LaunchDarkly observability plugin for the Android SDK.

The Android SDK supports the observability plugin for error monitoring, logging, tracing, and session replay.

Prerequisites and dependencies

This reference guide assumes that you are somewhat familiar with the LaunchDarkly Android SDK.

The observability plugin is compatible with the Android SDK, version 5.9.0 and later.

The LaunchDarkly Android SDK is compatible with Android SDK versions 21 and higher (Android 5.0, Lollipop).

Get started

Follow these steps to get started:

• Install the plugin
• Initialize the Android SDK client
• Configure the plugin options
• Configure additional instrumentations
• Configure session replay
• Explore supported features
• Review observability data in LaunchDarkly

Install the plugin

LaunchDarkly uses a plugin to the Android SDK to provide observability.

The first step is to make both the SDK and the observability plugin available as dependencies.

Here’s how:

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implementation 'com.launchdarkly:launchdarkly-android-client-sdk:5.+'
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implementation 'com.launchdarkly:launchdarkly-observability-android:0.21.0'

Then, import the plugin into your code:

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import com.launchdarkly.sdk.*;
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import com.launchdarkly.sdk.android.*;
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import com.launchdarkly.observability.plugin.Observability;
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import com.launchdarkly.sdk.android.integrations.Plugin;

Initialize the client

Next, initialize the SDK and the plugin.

To initialize, you need your LaunchDarkly environment’s mobile key and the context for which you want to evaluate flags. This authorizes your application to connect to a particular environment within LaunchDarkly. To learn more, read Initialize the client in the Android SDK reference guide.

Here’s how to initialize the SDK and plugin:

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String mobileKey = "example-mobile-key";
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LDConfig ldConfig = new LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(Components.plugins().setPlugins(
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      Collections.singletonList<Plugin>(Observability(this.getApplication(), mobileKey))
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    ))
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    // other options
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    .build();
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// You'll need this context later, but you can ignore it for now.
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LDContext context = LDContext.create("example-context-key");
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LDClient client = LDClient.init(this.getApplication(), ldConfig, context, 0);

Configure the plugin options

You can configure options for the observability plugin when you initialize the SDK. The plugin constructor takes an optional object with the configuration details.

Here is an example:

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String mobileKey = "example-mobile-key";
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LDConfig ldConfig = new LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        Collections.singletonList<Plugin>(
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          Observability(
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            this.getApplication(),
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            mobileKey,
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            ObservabilityOptions(
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              resourceAttributes = Attributes.of(
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                AttributeKey.stringKey("serviceName"), "example-service"
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              )
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            )
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          )
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        )
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      )
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    )
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    .build();

For more information on plugin options, read Configuration for client-side observability.

Advanced configuration options

You can customize the observability plugin with additional options:

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val mobileKey = "example-mobile-key"
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val ldConfig = LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        listOf(
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          Observability(
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            this@BaseApplication,
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            mobileKey,
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            ObservabilityOptions(
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              serviceName = "my-android-app",
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              serviceVersion = "1.0.0",
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              debug = true,
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              logsApiLevel = ObservabilityOptions.LogLevel.WARN,
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              tracesApi = ObservabilityOptions.TracesApi(includeErrors = true, includeSpans = false),
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              metricsApi = ObservabilityOptions.MetricsApi.disabled(),
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              instrumentations = ObservabilityOptions.Instrumentations(
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                crashReporting = false,
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                activityLifecycle = true,
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                launchTime = true
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              ),
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              resourceAttributes = Attributes.of(
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                AttributeKey.stringKey("environment"), "production",
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                AttributeKey.stringKey("team"), "mobile"
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              ),
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              customHeaders = mapOf(
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                "X-Custom-Header" to "custom-value"
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              )
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            )
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          )
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        )
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      )
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    )
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    .build()

The available ObservabilityOptions configuration options are:

• logsApiLevel: Minimum log severity to export. Defaults to INFO. Set to ObservabilityOptions.LogLevel.NONE to disable log exporting.
• tracesApi: Controls trace recording. Defaults to enabled. Use ObservabilityOptions.TracesApi.disabled() to disable all tracing, or set includeErrors/includeSpans individually.
• metricsApi: Controls metric export. Defaults to enabled. Use ObservabilityOptions.MetricsApi.disabled() to disable metrics.
• instrumentations: Enables or disables specific automatic instrumentations:
  • crashReporting: If true, automatically reports uncaught exceptions as errors. Defaults to true.
  • activityLifecycle: If true, automatically starts spans for Android Activity lifecycle events. Defaults to true.
  • launchTime: If true, automatically measures and reports application startup time as metrics. Defaults to false.
• serviceName: The service name for the application. Defaults to “observability-android”.
• serviceVersion: The version of the service. Defaults to the SDK version.
• debug: Enables verbose internal logging and debug functionality. Defaults to false.
• resourceAttributes: Additional resource attributes to include in telemetry data.
• customHeaders: Custom headers to include with OTLP exports.

Configure additional instrumentations

To enable HTTP request instrumentation and user interaction instrumentation, add the following plugin and dependencies to your top level application’s Gradle file.

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plugins {
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    id 'net.bytebuddy.byte-buddy-gradle-plugin' version '1.+'
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}
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dependencies {
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    // Android HTTP Url instrumentation
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    implementation 'io.opentelemetry.android.instrumentation:httpurlconnection-library:0.11.0-alpha'
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    byteBuddy 'io.opentelemetry.android.instrumentation:httpurlconnection-agent:0.11.0-alpha'
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    // OkHTTP instrumentation
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    implementation 'io.opentelemetry.android.instrumentation:okhttp3-library:0.11.0-alpha'
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    byteBuddy 'io.opentelemetry.android.instrumentation:okhttp3-agent:0.11.0-alpha'
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}

Configure session replay

The Android SDK supports session replay, which captures snapshots of your app’s UI at regular intervals. This allows you to visually review user sessions in LaunchDarkly to better understand user behavior and diagnose issues.

To enable session replay, add the SessionReplay plugin to the plugins list after the Observability plugin. Session replay depends on the Observability plugin being present and initialized first.

Here’s how:

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import com.launchdarkly.observability.plugin.Observability
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import com.launchdarkly.observability.replay.plugin.SessionReplay
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val mobileKey = "example-mobile-key"
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val ldConfig = LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        listOf(
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          Observability(this@BaseApplication, mobileKey),
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          SessionReplay()  // depends on Observability being present first
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        )
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      )
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    )
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    .build()

Important notes:

• SessionReplay depends on Observability. If Observability is missing or listed after SessionReplay, the plugin logs an error and stays inactive.
• Observability runs fine without SessionReplay. Adding SessionReplay extends the Observability pipeline to include session recording.

Initialize the plugins after the SDK client

You can initialize the session replay plugin manually, after the SDK client is initialized.

This approach supports feature-flagged rollouts or dynamic initialization after end user consent. Set enabled to false in ReplayOptions, then call LDReplay.start() when you’re ready to begin recording.

First, configure the plugin with enabled = false:

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import com.launchdarkly.observability.plugin.Observability
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import com.launchdarkly.observability.replay.plugin.SessionReplay
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import com.launchdarkly.observability.replay.ReplayOptions
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val mobileKey = "example-mobile-key"
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val ldConfig = LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        listOf(
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          Observability(this@BaseApplication, mobileKey),
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          SessionReplay(
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            options = ReplayOptions(
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              enabled = false // Don't start recording automatically
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            )
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          )
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        )
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      )
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    )
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    .build()
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val context = LDContext.create("example-context-key")
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val client = LDClient.init(this@BaseApplication, ldConfig, context, 0)

Then, start the session replay plugin when appropriate, such as after receiving end user consent or when a feature flag enables session replay.

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import com.launchdarkly.observability.sdk.LDReplay
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// Start recording after user consent or feature flag check
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LDReplay.start()

This approach allows you to:

• Feature-flag the rollout of session replay to a subset of end users
• Wait for end user consent before starting data collection
• Dynamically enable session replay based on runtime conditions
• Maintain compliance with privacy regulations

Session replay configuration options

You can customize session replay behavior by passing a ReplayOptions object to the SessionReplay constructor:

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import com.launchdarkly.observability.plugin.Observability
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import com.launchdarkly.observability.replay.plugin.SessionReplay
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import com.launchdarkly.observability.replay.ReplayOptions
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import com.launchdarkly.observability.replay.PrivacyProfile
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val mobileKey = "example-mobile-key"
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val ldConfig = LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        listOf(
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          Observability(this@BaseApplication, mobileKey),
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          SessionReplay(
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            options = ReplayOptions(
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              privacyProfile = PrivacyProfile(
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                maskTextInputs = true,
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                maskText = true
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              ),
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              capturePeriodMillis = 1000,
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              debug = false
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            )
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          )
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        )
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      )
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    )
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    .build()

The available ReplayOptions configuration options are:

• privacyProfile: Controls how UI elements are masked in the replay. To learn more, read Privacy options.
• capturePeriodMillis: Period between UI captures in milliseconds. Defaults to 1000 (1 second).
• debug: Enables verbose logging when set to true. Defaults to false.

Note: Service configuration options like serviceName and serviceVersion are set in ObservabilityOptions, not in ReplayOptions.

Privacy options

The PrivacyProfile class controls how UI elements are masked during session replay. Session replay for Android uses Jetpack Compose semantics to identify and mask UI elements. By default, text inputs are masked to protect user privacy.

Here’s how to configure privacy settings:

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import com.launchdarkly.observability.plugin.Observability
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import com.launchdarkly.observability.replay.plugin.SessionReplay
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import com.launchdarkly.observability.replay.ReplayOptions
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import com.launchdarkly.observability.replay.PrivacyProfile
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val mobileKey = "example-mobile-key"
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val ldConfig = LDConfig.Builder(AutoEnvAttributes.Enabled)
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    .mobileKey(mobileKey)
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    .plugins(
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      Components.plugins().setPlugins(
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        listOf(
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          Observability(this@BaseApplication, mobileKey),
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          SessionReplay(
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            options = ReplayOptions(
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              privacyProfile = PrivacyProfile(
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                maskTextInputs = true,
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                maskText = false
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              )
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            )
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          )
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        )
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      )
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    )
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    .build()

The available privacy options are:

• maskTextInputs: When true, masks all text input fields including editable text and paste operations. Defaults to true.
• maskText: When true, masks all non-input text elements in the UI. Defaults to false.
• maskBySemanticsKeywords: When true, masks sensitive views that contain password fields or text matching sensitive keywords. Defaults to false.

Sensitive keywords

When maskBySemanticsKeywords is enabled, the SDK automatically masks any Compose UI text or content descriptions containing predetermined keywords. Keywords you specify are not case-sensitive. For the current set of keywords, read PrivacyProfile.

Common privacy configurations

For maximum privacy (recommended for production):

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privacyProfile = PrivacyProfile(
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  maskTextInputs = true,
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  maskText = true,
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  maskBySemanticsKeywords = true
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)

For debugging or development, you can turn masking off:

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privacyProfile = PrivacyProfile(
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  maskTextInputs = false,
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  maskText = false,
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  maskBySemanticsKeywords = false
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)

For selective masking, which masks inputs and sensitive data but shows regular text:

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privacyProfile = PrivacyProfile(
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  maskTextInputs = true,
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  maskText = false,
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  maskBySemanticsKeywords = true
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)

Custom masking with ldMask

In addition to the privacy profile settings, you can explicitly mask individual UI elements by using the .ldMask() modifier. This is useful when you need to mask specific sensitive fields while allowing other content to remain visible.

Masking XML views

For traditional Android XML-based views, you can mask any View by calling the .ldMask() extension function:

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import com.launchdarkly.observability.api.ldMask
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class LoginActivity : AppCompatActivity() {
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    override fun onCreate(savedInstanceState: Bundle?) {
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        super.onCreate(savedInstanceState)
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        setContentView(R.layout.activity_login)
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        val password = findViewById<EditText>(R.id.password)
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        password.ldMask() // mask this field in session replay
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    }
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}

Masking Jetpack Compose elements

For Jetpack Compose, you can add the .ldMask() modifier to any composable to mask it in session replay recordings:

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import com.launchdarkly.observability.api.ldMask
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@Composable
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fun CreditCardField() {
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    var number by remember { mutableStateOf("") }
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    TextField(
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        value = number,
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        onValueChange = { number = it },
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        modifier = Modifier
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            .fillMaxWidth()
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            .ldMask() // mask this composable in session replay
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    )
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}

Unmasking elements

You can also explicitly unmask elements that would otherwise be masked by the privacy profile settings using the .ldUnmask() modifier:

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import com.launchdarkly.observability.api.ldUnmask
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@Composable
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fun PublicInfoField() {
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    var info by remember { mutableStateOf("") }
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    TextField(
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        value = info,
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        onValueChange = { info = it },
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        modifier = Modifier
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            .fillMaxWidth()
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            .ldUnmask() // explicitly unmask this field
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    )
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}

The .ldMask() and .ldUnmask() modifiers give you fine-grained control over which UI elements are masked in session replay recordings, allowing you to balance privacy protection with useful debugging information.

For more information on session replay configuration, read Configuration for session replay.

Distributed tracing

To implement distributed tracing, all spans generated across different function calls and services for the same user request must share the same context.

While nested spans in the same synchronous scope automatically use the context of their parent span, the context is not automatically propagated when launching new coroutines or switching dispatchers. Use the OpenTelemetry Context API to capture and restore the parent span context explicitly in asynchronous code:

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import io.opentelemetry.context.Context;
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import io.opentelemetry.context.Scope;
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Span parentSpan = LDObserve.startSpan("parentSpan", Attributes.empty());
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try (Scope parentScope = parentSpan.makeCurrent()) {
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    Context context = Context.current();
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    new Thread(() -> {
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        try (Scope childScope = context.makeCurrent()) {
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            Span childSpan = LDObserve.startSpan("childSpan", Attributes.empty());
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            // do work
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            childSpan.end();
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        }
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    }).start();
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} finally {
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    parentSpan.end();
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}

Alternatively, you can store the current context and restore it later in a different scope:

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import io.opentelemetry.context.Context;
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import io.opentelemetry.context.Scope;
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Span parentSpan = LDObserve.startSpan("parentSpan", Attributes.empty());
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try (Scope parentScope = parentSpan.makeCurrent()) {
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    // Now parentSpan is active in Context.current()
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    Context ctx = Context.current();
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    // Later, in another thread, restore the context
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    executor.execute(() -> {
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        try (Scope scope = ctx.makeCurrent()) {
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            Span nestedSpan = LDObserve.startSpan("nestedSpan", Attributes.empty());
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            // do work — nestedSpan is a child of parentSpan
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            nestedSpan.end();
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        }
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    });
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} finally {
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    parentSpan.end();
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}}

To propagate a span context to an entirely different service, use the OpenTelemetry W3CTraceContextPropagator to inject the context into outgoing HTTP headers. Services that receive the headers can then extract and use the context.

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import io.opentelemetry.api.trace.propagation.W3CTraceContextPropagator;
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import io.opentelemetry.context.Context;
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import okhttp3.Request;
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W3CTraceContextPropagator propagator = W3CTraceContextPropagator.getInstance();
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Request.Builder requestBuilder = new Request.Builder().url(url);
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propagator.inject(
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    Context.current(),
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    requestBuilder,
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    (carrier, key, value) -> carrier.addHeader(key, value)
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);
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Request request = requestBuilder.build();

The above example adds header content similar to:

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traceparent: 00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01
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tracestate: (optional vendor data)

Services that receive the headers use the extract method from W3CTraceContextPropagator to obtain the trace context and use it as the parent context for new spans.

Explore supported features

The observability plugin supports the following features. After the SDK and plugins are initialized, you can access these from within your application:

• Configuration for client-side observability
• Configuration for session replay
• Errors
• Logs
• Metrics
• Tracing

Review observability data in LaunchDarkly

After you initialize the SDK and observability plugin, your application automatically starts sending observability data back to LaunchDarkly. You can review this information in the LaunchDarkly user interface. To learn how, read Observability.

The observability data collected includes:

• Error monitoring: Unhandled exceptions, crashes, and manually recorded errors with stack traces
• Logs: Application logs with configurable severity levels and custom attributes
• Traces: Distributed tracing data including span timing, nested operations, and custom instrumentation
• Metrics: Performance metrics, custom counters, histograms, and gauge measurements
• Session data: User session information including lifecycle events and timing

Specifically, the observability data includes events that LaunchDarkly uses to automatically create the following metrics:

• User error rate and crash frequency
• Application performance metrics such as launch time and session duration
• Feature flag evaluation context and timing
• Custom business metrics recorded through the SDK

To learn more about autogenerated metrics, read Observability autogenerated metrics.