Send Java logs and traces to Bronto via OpenTelemetry

This page covers instrumenting a Java application with the OpenTelemetry SDK to send logs and traces to Bronto over OTLP/HTTP via a local OTel Collector. Both signals are co-equal: logs are bridged via the Logback or Log4j2 appender — no log statement changes needed — and traces are emitted via a tracer provider.

If you don’t have a Collector and want to export directly from your application to Bronto, see Direct export to Bronto at the bottom of this page.

Prerequisites

Java 8 or later
Maven or Gradle
A running OTel Collector configured to forward logs and traces to Bronto — see Connect Open Telemetry to Bronto
OpenTelemetry Java SDK documentation

Install dependencies

Use the OpenTelemetry BOM to manage all SDK versions in one place and avoid version conflicts.

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>io.opentelemetry</groupId>
      <artifactId>opentelemetry-bom</artifactId>
      <!-- check https://mvnrepository.com/artifact/io.opentelemetry/opentelemetry-bom for latest -->
      <version>LATEST</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

<dependencies>
  <dependency>
    <groupId>io.opentelemetry</groupId>
    <artifactId>opentelemetry-api</artifactId>
  </dependency>
  <dependency>
    <groupId>io.opentelemetry</groupId>
    <artifactId>opentelemetry-sdk</artifactId>
  </dependency>
  <dependency>
    <groupId>io.opentelemetry</groupId>
    <artifactId>opentelemetry-exporter-otlp</artifactId>
  </dependency>
  <!-- check https://mvnrepository.com/artifact/io.opentelemetry.instrumentation/opentelemetry-logback-appender-1.0 for latest -->
  <dependency>
    <groupId>io.opentelemetry.instrumentation</groupId>
    <artifactId>opentelemetry-logback-appender-1.0</artifactId>
    <version>LATEST</version>
  </dependency>
</dependencies>

// check https://mvnrepository.com/artifact/io.opentelemetry/opentelemetry-bom for latest BOM version
implementation platform('io.opentelemetry:opentelemetry-bom:LATEST')

dependencies {
    implementation 'io.opentelemetry:opentelemetry-api'
    implementation 'io.opentelemetry:opentelemetry-sdk'
    implementation 'io.opentelemetry:opentelemetry-exporter-otlp'
    // check https://mvnrepository.com/artifact/io.opentelemetry.instrumentation/opentelemetry-logback-appender-1.0 for latest
    implementation 'io.opentelemetry.instrumentation:opentelemetry-logback-appender-1.0:LATEST'
}

Package	Purpose
`opentelemetry-api`	Core OTel API
`opentelemetry-sdk`	SDK — `SdkLoggerProvider`, processors
`opentelemetry-exporter-otlp`	OTLP/HTTP exporter
`opentelemetry-logback-appender-1.0`	Bridges Logback into OTel

Using Log4j2 instead of Logback? Replace the appender dependency with opentelemetry-log4j-appender-2.17 from io.opentelemetry.instrumentation.

Configure the log bridge

Add the OpenTelemetryAppender to your logback.xml. Every log record Logback handles will be forwarded to the OTel pipeline.

logback.xml

<configuration>
  <appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
    <encoder>
      <pattern>%d{HH:mm:ss} %-5level %logger{36} - %msg%n</pattern>
    </encoder>
  </appender>

  <appender name="OpenTelemetry"
            class="io.opentelemetry.instrumentation.logback.appender.v1_0.OpenTelemetryAppender">
    <captureExperimentalAttributes>true</captureExperimentalAttributes>
    <captureCodeAttributes>true</captureCodeAttributes>
  </appender>

  <root level="INFO">
    <appender-ref ref="CONSOLE" />
    <appender-ref ref="OpenTelemetry" />
  </root>
</configuration>

captureExperimentalAttributes includes thread name and logger name as OTel attributes. captureCodeAttributes includes the source file, class, method, and line number.

Configure the OTLP exporter

Create an OpenTelemetrySdk instance with a SdkLoggerProvider and install it as the global instance. Call OpenTelemetryAppender.install() to wire the Logback appender to the SDK.

OtelConfig.java

import io.opentelemetry.api.common.Attributes;
import io.opentelemetry.exporter.otlp.http.logs.OtlpHttpLogRecordExporter;
import io.opentelemetry.instrumentation.logback.appender.v1_0.OpenTelemetryAppender;
import io.opentelemetry.sdk.OpenTelemetrySdk;
import io.opentelemetry.sdk.logs.SdkLoggerProvider;
import io.opentelemetry.sdk.logs.export.BatchLogRecordProcessor;
import io.opentelemetry.sdk.resources.Resource;
import io.opentelemetry.semconv.ResourceAttributes;

public class OtelConfig {
    public static void configure() {
        OtlpHttpLogRecordExporter exporter = OtlpHttpLogRecordExporter.builder()
            .setEndpoint("http://localhost:4318/v1/logs")
            .build();

        Resource resource = Resource.getDefault().merge(
            Resource.create(Attributes.of(
                ResourceAttributes.SERVICE_NAME, "my-service",
                ResourceAttributes.SERVICE_NAMESPACE, "my-team",
                ResourceAttributes.DEPLOYMENT_ENVIRONMENT, "production"
            ))
        );

        SdkLoggerProvider loggerProvider = SdkLoggerProvider.builder()
            .setResource(resource)
            .addLogRecordProcessor(BatchLogRecordProcessor.builder(exporter).build())
            .build();

        OpenTelemetrySdk openTelemetry = OpenTelemetrySdk.builder()
            .setLoggerProvider(loggerProvider)
            .buildAndRegisterGlobal();

        OpenTelemetryAppender.install(openTelemetry);
    }
}

Call OtelConfig.configure() once at application startup, before the first log statement.

Set resource attributes

Resource attributes are attached to every log record exported from this process. Two attributes drive how Bronto organises incoming logs:

OTel attribute	Bronto concept	Description
`service.name`	Dataset	Groups logs from one service
`service.namespace`	Collection	Groups related services or a team’s services

These are set via Resource.create() in the SDK configuration above.

Complete example

Main.java

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class Main {
    private static final Logger logger = LoggerFactory.getLogger(Main.class);

    public static void main(String[] args) {
        OtelConfig.configure();

        logger.info("Application started");
        logger.warn("Low disk space, free_gb={}", 2.1);
        logger.error("Database connection failed", new RuntimeException("timeout"));
    }
}

Existing SLF4J / Logback log statements require no changes.

Verify delivery

After running your application, check both signals in Bronto:

Logs: open the Search page and filter by the dataset name you set in service.name — your log records should appear within a few seconds.
Traces: open the Explore Traces page and filter by the same service.name — your spans should appear within a few seconds.

If no logs appear, check:

The OTel Collector is running and reachable at the configured endpoint.
The Collector’s pipeline includes a logs pipeline with an otlp receiver and the Bronto exporter — see Connect Open Telemetry to Bronto.
OpenTelemetryAppender.install() is called before the first log statement.
BatchLogRecordProcessor exports on a background thread — for short-lived programs, add a shutdown hook: loggerProvider.shutdown().

Traces

The OpenTelemetry Java Agent provides zero-code auto-instrumentation for Spring, Hibernate, gRPC, Kafka, JDBC, and many more frameworks. Download the jar and attach it at startup with -javaagent:opentelemetry-javaagent.jar — no SDK code changes are needed. It is the recommended starting point for most Java applications.

Configure the tracer provider

No additional packages are needed — opentelemetry-sdk and opentelemetry-exporter-otlp already include tracing support. Create a SdkTracerProvider and combine it with the SdkLoggerProvider in the same OpenTelemetrySdk builder:

OtelConfig.java

import io.opentelemetry.exporter.otlp.http.trace.OtlpHttpSpanExporter;
import io.opentelemetry.sdk.trace.SdkTracerProvider;
import io.opentelemetry.sdk.trace.export.BatchSpanProcessor;

SdkTracerProvider tracerProvider = SdkTracerProvider.builder()
    .setResource(resource)
    .addSpanProcessor(BatchSpanProcessor.builder(
        OtlpHttpSpanExporter.builder()
            .setEndpoint("http://localhost:4318/v1/traces")
            .build()
    ).build())
    .build();

OpenTelemetrySdk openTelemetry = OpenTelemetrySdk.builder()
    .setLoggerProvider(loggerProvider)
    .setTracerProvider(tracerProvider)
    .buildAndRegisterGlobal();

OpenTelemetryAppender.install(openTelemetry);

The shared resource ensures service.name and service.namespace are identical on both logs and traces.

Creating spans

Get a tracer from the global instance and use it to create spans:

Tracer tracer = GlobalOpenTelemetry.getTracer("my-service");

Span span = tracer.spanBuilder("process-payment")
    .startSpan();
try (Scope scope = span.makeCurrent()) {
    span.setAttribute("payment.amount", 99.99);
    logger.info("Processing payment");  // trace_id and span_id injected automatically
} finally {
    span.end();
}

Any Logback or Log4j2 statement inside an active span will automatically have trace_id and span_id attached.

GenAI semantic conventions

If your application calls an LLM, OpenTelemetry defines GenAI semantic conventions for model, token usage, and prompt/response content.

This page was verified on July 17, 2026. GenAI libraries and semantic conventions are evolving rapidly, so package configuration and emitted attributes can change between releases. Keep your instrumentation current and verify the fields emitted by the version you deploy.

Auto-instrumentation

The OpenTelemetry Java Agent includes GenAI instrumentation for the OpenAI Java client and AWS SDK v2 Bedrock calls — no extra instrumentation dependency is needed. Model calls carry gen_ai.provider.name, gen_ai.request.model, and token-usage attributes instead of only a plain HTTP client span.

GenAI instrumentation coverage in the Java agent is newer and narrower than Python’s — check the agent’s supported libraries list for your provider/framework. If it isn’t covered, use manual spans below.

Experimental: capturing prompt and response content

For the Java agent’s OpenAI and AWS SDK instrumentations, content capture is off by default:

export OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true

Captured content may be emitted as OTel log events rather than span attributes, depending on the instrumented client and agent version. It then travels through the logs pipeline and is not queryable on the trace span itself.To make it searchable, also emit it as a structured log record correlated by trace_id, using the log bridge configured above. See LLM Observability for the recommended attribute names, a worked logging example, and Bronto search queries.

Manual spans

Where the agent doesn’t cover your provider or framework, set the gen_ai.* attributes yourself:

Tracer tracer = GlobalOpenTelemetry.getTracer("my-service");

Span span = tracer.spanBuilder("chat gpt-4o-mini").startSpan();
try (Scope scope = span.makeCurrent()) {
    span.setAttribute("gen_ai.provider.name", "openai");
    span.setAttribute("gen_ai.request.model", "gpt-4o-mini");
    span.setAttribute("gen_ai.usage.input_tokens", 33);
    span.setAttribute("gen_ai.usage.output_tokens", 74);
    span.setAttribute(
        io.opentelemetry.api.common.AttributeKey.stringArrayKey("gen_ai.response.finish_reasons"),
        java.util.List.of("stop")
    );
} finally {
    span.end();
}

See LLM Observability for the full recommended attribute set, including gen_ai.input.messages / gen_ai.output.messages, and how to search and aggregate GenAI fields in Bronto.

Direct export to Bronto

If you are not using an OTel Collector, export directly to Bronto by replacing the exporter configurations with the Bronto OTLP endpoints and your API key:

OtlpHttpLogRecordExporter logExporter = OtlpHttpLogRecordExporter.builder()
    .setEndpoint("https://ingestion.eu.bronto.io/v1/logs") // or ingestion.us.bronto.io
    .addHeader("x-bronto-api-key", "<YOUR_API_KEY>")
    .build();

OtlpHttpSpanExporter traceExporter = OtlpHttpSpanExporter.builder()
    .setEndpoint("https://ingestion.eu.bronto.io/v1/traces") // or ingestion.us.bronto.io
    .addHeader("x-bronto-api-key", "<YOUR_API_KEY>")
    .build();

Region	Logs endpoint	Traces endpoint
EU	`https://ingestion.eu.bronto.io/v1/logs`	`https://ingestion.eu.bronto.io/v1/traces`
US	`https://ingestion.us.bronto.io/v1/logs`	`https://ingestion.us.bronto.io/v1/traces`

See API Keys for how to create a key with ingestion permissions. No other changes to the rest of the setup are required.

Overview

Ingest with agents

Ingest from AWS

Ingest from Azure

Ingest from CDN and edge

Ingest from apps and platforms

Ingest from infrastructure and databases

Ingest OpenTelemetry data

Send Java logs and traces to Bronto via OpenTelemetry

Prerequisites

Install dependencies

Configure the log bridge

Configure the OTLP exporter

Set resource attributes

Complete example

Verify delivery

Traces

Configure the tracer provider

Creating spans

GenAI semantic conventions

Auto-instrumentation

Experimental: capturing prompt and response content

Manual spans

Direct export to Bronto

​Prerequisites

​Install dependencies

​Configure the log bridge

​Configure the OTLP exporter

​Set resource attributes

​Complete example

​Verify delivery

​Traces

​Configure the tracer provider

​Creating spans

​GenAI semantic conventions

​Auto-instrumentation

​Experimental: capturing prompt and response content

​Manual spans

​Direct export to Bronto

Prerequisites

Install dependencies

Configure the log bridge

Configure the OTLP exporter

Set resource attributes

Complete example

Verify delivery

Traces

Configure the tracer provider

Creating spans

GenAI semantic conventions

Auto-instrumentation

Experimental: capturing prompt and response content

Manual spans

Direct export to Bronto