Send traces to Datadog from your Android applications with Datadog’s dd-sdk-android-trace client-side tracing library and leverage the following features:

• Create custom spans for operations in your application.
• Add context and extra custom attributes to each span sent.
• Optimized network usage with automatic bulk posts.

개요

다음의 경우 OpenTelemetry API를 사용해 애플리케이션을 수동으로 계측해야 합니다.

• Datadog이 지원하는 라이브러리 계측을 사용하고 있지 않습니다.
• ddtrace 라이브러리의 기능을 확장하고 싶습니다.
• 애플리케이션 계측을 보다 세밀하게 제어해야 합니다.

ddtrace 라이브러리는 이러한 목표를 달성하는 데 도움이 됩니다. 다음 섹션에서는 커스텀 계측을 위해 Datadog과 OpenTelemetry API를 함께 사용하는 방법을 다룹니다.

The Datadog Tracer implements the OpenTelemetry standard, and Datadog recommends using it as an interface for tracing your application because it’s vendor-neutral, supports many languages and frameworks, and unifies traces, metrics, and logs under one standard. See instructions on setting up OpenTelemetry integration with the SDK.

Note: The OpenTelemetry specification library requires desugaring to be enabled for projects with a minSdk < 26. If you cannot enable desugaring in your project, you can still use the Trace product with the Datadog API instead.

Note: The Datadog API implementation helps you transition from OpenTracing to OpenTelemetry.

Setup

1. Add the Gradle dependency by declaring the library as a dependency in your build.gradle file:

dependencies {
  implementation "com.datadoghq:dd-sdk-android-trace:x.x.x"
}

2. Initialize Datadog SDK with your application context, tracking consent, and the Datadog client token. For security reasons, you must use a client token: you cannot use Datadog API keys to configure Datadog SDK as they would be exposed client-side in the Android application APK byte code. For more information about setting up a client token, see the client token documentation:

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
           clientToken = "<CLIENT_TOKEN>",
           env = "<ENV_NAME>",
           variant = "<APP_VARIANT_NAME>"
       ).build()

       Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
         .build();

       Datadog.initialize(this, configuration, trackingConsent);
   }
}

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
            clientToken = "<CLIENT_TOKEN>",
            env = "<ENV_NAME>",
            variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.EU1)
         .build()

     Datadog.initialize(this, configuration, trackingConsent)
   }
}

   public class SampleApplication extends Application {
       @Override
       public void onCreate() {
           super.onCreate();
           Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
             .useSite(DatadogSite.EU1)
             .build();

           Datadog.initialize(this, configuration, trackingConsent);
       }
   }

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
         clientToken = "<CLIENT_TOKEN>",
         env = "<ENV_NAME>",
         variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.US3)
         .build()

     Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
         .useSite(DatadogSite.US3)
         .build();

       Datadog.initialize(this, configuration, trackingConsent);
   }
}

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
         clientToken = "<CLIENT_TOKEN>",
         env = "<ENV_NAME>",
         variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.US5)
         .build()

     Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
         .useSite(DatadogSite.US5)
         .build();

       Datadog.initialize(this, configuration, trackingConsent);
   }
}

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
         clientToken = "<CLIENT_TOKEN>",
         env = "<ENV_NAME>",
         variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.US1_FED)
         .build()

     Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
         .useSite(DatadogSite.US1_FED)
         .build();
       Datadog.initialize(this, configuration, trackingConsent);
   }
}

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
         clientToken = "<CLIENT_TOKEN>",
         env = "<ENV_NAME>",
         variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.AP1)
         .build()

       Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
                       .useSite(DatadogSite.AP1)
                       .build();
       Datadog.initialize(this, configuration, trackingConsent);
   }
}

class SampleApplication : Application() {
   override fun onCreate() {
       super.onCreate()
       val configuration = Configuration.Builder(
         clientToken = "<CLIENT_TOKEN>",
         env = "<ENV_NAME>",
         variant = "<APP_VARIANT_NAME>"
       ).useSite(DatadogSite.AP2)
         .build()
       Datadog.initialize(this, configuration, trackingConsent)
   }
}

public class SampleApplication extends Application {
   @Override
   public void onCreate() {
       super.onCreate();
       Configuration configuration = new Configuration.Builder("<CLIENT_TOKEN>", "<ENV_NAME>", "<APP_VARIANT_NAME>")
         .useSite(DatadogSite.AP2)
         .build();

       Datadog.initialize(this, configuration, trackingConsent);
   }
}

To be compliant with the GDPR regulation, the SDK requires the tracking consent value at initialization. The tracking consent can be one of the following values:

• TrackingConsent.PENDING: The SDK starts collecting and batching the data but does not send it to the data collection endpoint. The SDK waits for the new tracking consent value to decide what to do with the batched data.
• TrackingConsent.GRANTED: The SDK starts collecting the data and sends it to the data collection endpoint.
• TrackingConsent.NOT_GRANTED: The SDK does not collect any data. You will not be able to manually send any logs, traces, or RUM events.

To update the tracking consent after the SDK is initialized, call: Datadog.setTrackingConsent(<NEW CONSENT>). The SDK changes its behavior according to the new consent. For example, if the current tracking consent is TrackingConsent.PENDING and you update it to:

• TrackingConsent.GRANTED: The SDK sends all current batched data and future data directly to the data collection endpoint.
• TrackingConsent.NOT_GRANTED: The SDK wipes all batched data and does not collect any future data.

Note: In the credentials required for initialization, your application variant name is also required, and should use your BuildConfig.FLAVOR value (or an empty string if you don’t have variants). This is important because it enables the right ProGuard mapping.txt file to be automatically uploaded at build time to be able to view de-obfuscated RUM error stack traces. For more information see the guide to uploading Android source mapping files.

Use the utility method isInitialized to check if the SDK is properly initialized:

if (Datadog.isInitialized()) {
// your code here
}

When writing your application, you can enable development logs by calling the setVerbosity method. All internal messages in the library with a priority equal to or higher than the provided level are then logged to Android’s Logcat:

Datadog.setVerbosity(Log.INFO)

3. Configure and enable Trace feature:

val traceConfig = TraceConfiguration.Builder().build()
Trace.enable(traceConfig)

TraceConfiguration traceConfig = TraceConfiguration.Builder().build();
Trace.enable(traceConfig);

4. Configure and register the DatadogTracer. You only need to do it once, usually in your application’s onCreate() method:

import com.datadog.android.trace.GlobalDatadogTracer
import com.datadog.android.trace.DatadogTracing

GlobalDatadogTracer.registerIfAbsent(
  DatadogTracing.newTracerBuilder()
    .build()
)

import com.datadog.android.trace.GlobalDatadogTracer;
import com.datadog.android.trace.DatadogTracing;

GlobalDatadogTracer.registerIfAbsent(
  DatadogTracing.newTracerBuilder(Datadog.getInstance()).build()
);

5. (Optional) - Set the partial flush threshold to optimize the SDK’s workload based on the number of spans your application generates. The library waits until the number of finished spans exceeds the threshold before writing them to disk. Setting this value to 1 writes each span as soon as it finishes.

val tracer = DatadogTracing.newTracerBuilder()
  .withPartialFlushMinSpans(10)
  .build()

DatadogTracer tracer = DatadogTracing.newTracerBuilder(Datadog.getInstance())
  .withPartialFlushMinSpans(10)
  .build();

6. Start a custom span using the following method:

val tracer = GlobalDatadogTracer.get()
val span = tracer.buildSpan("<SPAN_NAME>").start()
// Do something ...
// ...
// Then when the span should be closed
span.finish()

DatadogTracer tracer = GlobalDatadogTracer.get();
DatadogSpan span = tracer.buildSpan("<SPAN_NAME>").start();
// Do something ...
// ...
// Then when the span should be closed
span.finish();

7. To use scopes in synchronous calls:

val span = tracer.buildSpan("<SPAN_NAME1>").start()
try {
  val scope = tracer.activateSpan(span)
  scope?.use {
    // Do something ...
    // ...
    // Start a new Scope
    val childSpan = tracer.buildSpan("<SPAN_NAME2>").start()
    try {
      val innerScope = tracer.activateSpan(childSpan).use { innerScope ->
        // Do something ...
      }
    } catch (e: Throwable) {
      childSpan.logThrowable(e)
    } finally {
      childSpan.finish()
    }
  }
} catch (e: Error) {
}

DatadogSpan span = tracer.buildSpan("<SPAN_NAME1>").start();
try {
  DatadogScope scope = tracer.activateSpan(span);
  try {
    // Do something ...
    // ...
    // Start a new Scope
    DatadogSpan childSpan = tracer.buildSpan("<SPAN_NAME2>").start();
    try {
      DatadogScope innerScope = tracer.activateSpan(childSpan);
      try {
        // Do something ...
      }
      finally {
        innerScope.close();
      }
    } catch( Throwable e) {
      childSpan.logThrowable(e);
    } finally {
      childSpan.finish();
    }
  }
  finally {
    scope.close();
  }
} catch(Error e){
}

8. To use scopes in asynchronous calls:

val span = tracer.buildSpan("<SPAN_NAME1>").start()
try {
  val scope = tracer.activateSpan(span)
  scope.use {
    // Do something ...
    Thread {
      // Step 2: reactivate the Span in the worker thread
      tracer.activateSpan(span).use {
        // Do something ...
      }
    }.start()
  }
} catch (e: Throwable) {
  span.logThrowable(e)
} finally {
  span.finish()
}

DatadogSpan span = tracer.buildSpan("<SPAN_NAME1>").start();
try {
    DatadogScope scope = tracer.activateSpan(span);
    try {
        // Do something ...
        new Thread(() ->{
            // Step 2: reactivate the Span in the worker thread
            DatadogScope scopeContinuation = tracer.activateSpan(span);
            try {
                // Do something
            } finally {
                scope.close();
            }
        }).start();

    } finally {
        scope.close();
    }
} catch(Throwable e) {
        span.logThrowable(e);
} finally {
      span.finish();
}

9. (Optional) To manually distribute traces between your environments, for example frontend to backend:

   a. Inject tracer context in the client request.

val tracer = GlobalDatadogTracer.get()
val span = tracer.buildSpan("<SPAN_NAME>").start()
val tracedRequestBuilder = Request.Builder()
tracer.propagate().inject<Request.Builder?>(
  span.context(),
  tracedRequestBuilder
) { builder, key, value ->
  builder?.addHeader(key, value)
}
val request = tracedRequestBuilder.build()
// Dispatch the request and finish the span after.

DatadogTracer tracer = GlobalDatadogTracer.get();
DatadogSpan span = tracer.buildSpan("<SPAN_NAME>").start();
Request.Builder tracedRequestBuilder = new Request.Builder();
tracer.propagate().inject(
  span.context(),
  tracedRequestBuilder,
  new Function3<Request.Builder,String,String,Unit>(){
    @Override
    public Unit invoke(Request.Builder builder, String key, String value) {
      builder.addHeader(key, value);
      return Unit.INSTANCE;
    }
  });
Request request = tracedRequestBuilder.build();
// Dispatch the request and finish the span after.

b. Extract the client tracer context from headers in server code.

val tracer = GlobalDatadogTracer.get()
val extractedContext = tracer.propagate()
  .extract(request) { carrier, classifier ->
    val headers = carrier.headers.toMultimap()
      .map { it.key to it.value.joinToString(";") }
      .toMap()

    for ((key, value) in headers) classifier(key, value)
  }

val serverSpan = tracer.buildSpan("<SERVER_SPAN_NAME>").withParentContext(extractedContext).start()

DatadogTracer tracer = GlobalDatadogTracer.get();
DatadogSpanContext extractedContext = tracer.propagate()
  .extract(request,
    new Function2<Request, Function2<? super String, ? super String, Boolean>, Unit>() {
      @Override
      public Unit invoke(
        Request carrier,
        Function2<? super String, ? super String, Boolean> classifier
      ) {
        request.headers().forEach(pair -> {
          String key = pair.component1();
          String value = pair.component2();

          classifier.invoke(key, value);
        });

        return Unit.INSTANCE;
      }
    });
DatadogSpan serverSpan = tracer.buildSpan("<SERVER_SPAN_NAME>").withParentContext(extractedContext).start();

Note: For code bases using the OkHttp client, Datadog provides the implementation below.

10. (Optional) To provide additional tags alongside your span:

span.setTag("http.url", url)

11. (Optional) To mark a span as having an error, log it using corresponding methods:

span.logThrowable(throwable)

span.logErrorMessage(message)

12. If you need to modify some attributes in your Span events before batching you can do so by providing an implementation of SpanEventMapper when enabling Trace feature:

val traceConfig = TraceConfiguration.Builder()
  // ...
  .setEventMapper(spanEventMapper)
  .build()

TraceConfiguration config = new TraceConfiguration.Builder()
  // ...
  .setEventMapper(spanEventMapper)
  .build();

Kotlin Extensions

Running a lambda within a Span

To monitor the performance of a given lambda, you can use the withinSpan() method. By default, a scope will be created for the span, but you can disable this behavior by setting the activate parameter to false.

import com.datadog.android.trace.withinSpan
import com.datadog.android.trace.api.span.DatadogSpan

withinSpan("<SPAN_NAME>", parentSpan, activate) {
  // Your code here
}

Tracing SQLite transaction

If you are using SQLiteDatabase to persist data locally, you can trace the database transaction using the following method:

import com.datadog.android.trace.sqlite.transactionTraced
import android.database.sqlite.SQLiteDatabase

sqliteDatabase.transactionTraced("<SPAN_NAME>", isExclusive) { database ->
  // Your queries here
  database.insert("<TABLE_NAME>", null, contentValues)

  // Decorate the Span
  setTag("<TAG_KEY>", "<TAG_VALUE>")
}

It behaves like the SQLiteDatabase.transaction method provided in the core-ktx AndroidX package and only requires a span operation name.

Integrations

In addition to manual tracing, the Datadog SDK provides the following integrations.

OkHttp

If you want to trace your OkHttp requests, you can add the provided Interceptor (which can be found in the dd-sdk-android-okhttp library) as follows:

1. Add the Gradle dependency to the dd-sdk-android-okhttp library in the module-level build.gradle file:

dependencies {
    implementation "com.datadoghq:dd-sdk-android-okhttp:x.x.x"
}

2. Add DatadogInterceptor to your OkHttpClient:

val tracedHosts = listOf("example.com", "example.eu")
val okHttpClient = OkHttpClient.Builder()
  .addInterceptor(
    DatadogInterceptor.Builder(tracedHosts)
      .setTraceSampler(RateBasedSampler(20f))
      .build()
  )
  .build()

List<String> tracedHosts = Arrays.asList("example.com", "example.eu");
OkHttpClient okHttpClient = new OkHttpClient.Builder()
  .addInterceptor(
    new DatadogInterceptor.Builder(tracedHosts)
      .setTraceSampler(new RateBasedSampler(20f))
      .build()
  )
  .build();

This creates a span around each request processed by the OkHttpClient (matching the provided hosts), with all the relevant information automatically filled (URL, method, status code, error), and propagates the tracing information to your backend to get a unified trace within Datadog.

Network traces are sampled with an adjustable sampling rate. A sampling of 100% is applied by default.

The interceptor tracks requests at the application level. You can also add a TracingInterceptor at the network level to get more details, for example when following redirections.

val tracedHosts = listOf("example.com", "example.eu")
val okHttpClient = OkHttpClient.Builder()
  .addInterceptor(
    DatadogInterceptor.Builder(tracedHosts)
      .setTraceSampler(RateBasedSampler(20f))
      .build()
  )
  .addNetworkInterceptor(
    TracingInterceptor.Builder(tracedHosts)
      .setTraceSampler(RateBasedSampler(100f))
      .build()
  )
  .build()

List<String> tracedHosts = Arrays.asList("example.com", "example.eu");
OkHttpClient okHttpClient = new OkHttpClient.Builder()
  .addInterceptor(
    new DatadogInterceptor.Builder(tracedHosts)
      .setTraceSampler(new RateBasedSampler(20f))
      .build()
  )
  .addNetworkInterceptor(
    new TracingInterceptor.Builder(tracedHosts)
      .setTraceSampler(new RateBasedSampler(20f))
      .build()
  )
  .build();

In this case trace sampling decision made by the upstream interceptor for a particular request will be respected by the downstream interceptor.

Because the way the OkHttp Request is executed (using a Thread pool), the request span won’t be automatically linked with the span that triggered the request. You can manually provide a parent span in the OkHttp Request.Builder as follows by using Request.Builder.parentSpan extension method:

val request = Request.Builder()
  .url(requestUrl)
  .parentSpan(parentSpan)
  .build()

Request.Builder requestBuilder = new Request.Builder()
  .url(requestUrl)
Request request = OkHttpRequestExtKt
  .parentSpan(requestBuilder, parentSpan)
  .build();

Note:

• If you use multiple Interceptors, this one must be called first.
• If you define custom tracing header types in the Datadog configuration and are using a tracer registered with GlobalDatadogTracer, make sure the same tracing header types are set for the tracer in use.

Batch collection

All the spans are first stored on the local device in batches. Each batch follows the intake specification. They are sent as soon as 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 being offline, no data will be lost.

The data on disk will automatically be discarded if it gets too old to ensure the SDK doesn’t use too much disk space.

Initialization

The following methods in DatadogTracerBuilder can be used when initializing the DatadogTracer:

Further Reading

추가 유용한 문서, 링크 및 기사:

dd-sdk-android Source codeSOURCE CODE Explore your services, resources, and tracesDOCUMENTATION