---
title: Trace your Java Lambda functions with New Relic and OpenTelemetry
source: https://docs.newrelic.com/docs/serverless-function-monitoring/aws-lambda-monitoring/opentelemetry/lambda-opentelemetry-java
---

> #### 💡 PREVIEW
>
> AWS Lambda with OpenTelemetry for Java is still in development.
>
> We have similar documentation for [.NET](https://docs.newrelic.com/docs/serverless-function-monitoring/aws-lambda-monitoring/opentelemetry/lambda-opentelemetry-dotnet), but if  you're using Python, Go, JavaScript, Ruby, or PHP for AWS Lambda with OpenTelemetry, you can use our Java or .NET documentation as a general guide to the setup. For additional information, see [AWS Distro for OpenTelemetry](https://aws-otel.github.io/docs/introduction).

This guide will cover how you can use [OpenTelemetry Lambda](https://github.com/open-telemetry/opentelemetry-lambda) to trace your Java Lambda functions using AWS's managed [OpenTelemetry Lambda Layers](https://aws-otel.github.io/docs/getting-started/lambda/lambda-java-auto-instr). OpenTelemetry makes it easy to instrument your functions, including automatic instrumentation for many popular libraries.

## Prerequisites [#prerequisites]

This guide assumes you have the following:

-   A New Relic account. If you don't have one, [create one for free](https://newrelic.com/signup).
-   An AWS account. If you don't have one, [create one for free](https://aws.amazon.com/).
-   A Java Lambda Function running under either the `java8.al2` or `java11` runtimes. If you don't have one yet, [create one now](https://docs.aws.amazon.com/lambda/latest/dg/lambda-java.html).

### (Optional) Enable X-Ray [#xray]

Even though we're not using AWS X-Ray in this setup, we still need to enable X-Ray in the Lambda function to enable the tracing features built into AWS OpenDistro.

To enable X-Ray:

1.  Open your function in the [Lambda Console](https://console.aws.amazon.com/lambda).
2.  Choose **Configuration**, then **Monitoring Tools**.
3.  Choose **Edit**.
4.  Under **X-Ray**, enable **Active tracing**.

Alternatively, if you're using [SAM (Serverless Application Model)](https://aws.amazon.com/serverless/sam/) or [CloudFormation](https://aws.amazon.com/cloudformation/resources/templates/) templates, you can enable X-Ray by adding the following to your Lambda function's properties:

```yaml
yourFunctionHere:
  Type: AWS::Serverless::Function
  Properties:
    # ...
    Policies:
      - AWSLambdaBasicExecutionRole
      # ...
      - AWSXrayWriteOnlyAccess
    Tracing: Active
```

> #### ⚠️ IMPORTANT
>
> This option requires that you have `AWSLambdaBasicExecutionRole` or an equivalent policy attached to your function.

## Step 1: Install the layer [#install]

AWS publishes a managed layer that includes the [OpenTelemetry Lambda Collector](https://github.com/open-telemetry/opentelemetry-lambda), the [OpenTelemetry Java SDK](https://github.com/open-telemetry/opentelemetry-java-instrumentation), and the [ADOT auto instrumentation agent](https://github.com/aws-observability/aws-otel-java-instrumentation).

To install it:

1.  Open your function in the [Lambda Console](https://console.aws.amazon.com/lambda).
2.  Under **Layers** in the **Designer** section, choose **Add a layer**.
3.  Under **Specify an ARN**, paste one of the layer ARNs for your function's architecture form the list below. Replace `{region}`with your AWS region, such as `us-east-1`.
4.  Choose **Add**.

    -   AMD64 / X86_64: `arn:aws:lambda:{region}:901920570463:layer:aws-otel-java-agent-amd64-ver-1-11-1:1`
    -   ARM64: `arn:aws:lambda:{region}:901920570463:layer:aws-otel-java-agent-arm64-ver-1-11-1:1`

For SAM or CloudFormation templates, add this to your function's properties:

```yaml
yourFunctionHere:
  Type: AWS::Serverless::Function
  Properties:
    # ...
    Layers:
      # Use this if using x86_64 architecture
      - !Sub arn:${AWS::Partition}:lambda:${AWS::Region}:901920570463:layer:aws-otel-java-agent-amd64-ver-1-11-1:1
      # Use this if using arm64 architecture
      - !Sub arn:${AWS::Partition}:lambda:${AWS::Region}:901920570463:layer:aws-otel-java-agent-arm64-ver-1-11-1:1
```

> #### ⚠️ IMPORTANT
>
> Refer to the [latest ARNs published by AWS](https://aws-otel.github.io/docs/getting-started/lambda/lambda-java-auto-instr) to verify the layer ARNs above are up to date.

## Step 2: Configure the layer [#configure]

To configure the layer we need to configure an [exec wrapper](https://docs.aws.amazon.com/lambda/latest/dg/runtimes-modify.html#runtime-wrapper). The exec wrapper is a script that gets run during function initialization. In this case, the script configures OpenTelemetry.

1.  Open your function in the [Lambda Console](https://console.aws.amazon.com/lambda).
2.  Choose **Configuration** and then **Environment variables**.
3.  Under **Environment variables**, choose **Edit**.
4.  Choose **Add environment variable**.
5.  For the **Key** set it to `AWS_LAMBDA_EXEC_WRAPPER` and set the **Value** to one of the following options (depends on your handler type). Then choose **Save**.

    -   `/opt/otel-handler`: for wrapping regular handlers (implementing `RequestHandler`)
    -   `/opt/otel-proxy-handler`: for wrapping regular handlers (implementing `RequestHandler`) proxied through API Gateway, enabling HTTP context propagation
    -   `/opt/otel-stream-handler`: for wrapping streaming handlers (implementing `RequestStreamHandler`), enabling HTTP context propagation for HTTP requests

For SAM or CloudFormation templates, add this to your function's properties:

```yaml
yourFunctionHere:
  Type: AWS::Serverless::Function
  Properties:
    # ...
    Environment:
      Variables:
        AWS_LAMBDA_EXEC_WRAPPER: /opt/otel-handler
```

> #### ⚠️ IMPORTANT
>
> Replace `/opt/otel-handler` if your function handler implements one of the other handler types.

## Step 3: Add New Relic environment variables [#env-variables]

To send the OpenTelemetry data that this layer collects to New Relic, we need to configure the OpenTelemetry Lambda Collector that is packaged with the layer to export the telemetry it receives to the [New Relic OpenTelemetry Endpoint](https://docs.newrelic.com/docs/more-integrations/open-source-telemetry-integrations/opentelemetry/opentelemetry-quick-start). Before we do that, we first need to set some environment variables that it will depend upon.

1.  Generate and copy a New Relic license key from your New Relic account.
2.  Open up your function in the [Lambda Console](https://console.aws.amazon.com/lambda).
3.  Choose **Configuration** and then **Environment variables**.
4.  Under **Environment variables**, choose **Edit**.
5.  Choose **Add environment variable**.
6.  For the **Key** set it to `NEW_RELIC_LICENSE_KEY` and set the **Value** to the value of the license key you generated in step 1. Then choose **Save**.
7.  Choose **Add environment variable** again.
8.  For the **Key** set it to `NEW_RELIC_OPENTELEMETRY_ENDPOINT` and set the **Value** to one of the options below (depends on your New Relic region). Then choose **Save**.

    -   `otlp.nr-data.net:4317`: If your New Relic account is in the US region (default)
    -   `otlp.eu01.nr-data.net:4317`: If your New Relic account is in the EU region
    -   `otlp.jp.nr-data.net:4317`: If your New Relic account is in the JP region

For SAM and CloudFormation templates, add the following to your function's properties. Be sure to replace `your-license-key-here` with your license key and `otlp.nr-data.net:4317` with the New Relic OpenTelemetry Endpoint for your region.

```yaml
yourFunctionHere:
  Type: AWS::Serverless::Function
  Properties:
    # ...
    Environment:
      Variables:
        # ...
        NEW_RELIC_LICENSE_KEY: your-license-key-here
        NEW_RELIC_OPENTELEMETRY_ENDPOINT: otlp.nr-data.net:4317
```

> #### ⚠️ IMPORTANT
>
> Replace `your-license-key-here` with your New Relic license key, and `otlp.nr-data.net:4317` with the endpoint appropriate for your New Relic region. See the list above.

## Step 4: Configure the Collector [#collector]

Now we will override the OpenTelemetry Lambda Collector's default configuration with one that exports telemetry to the New Relic OpenTelemetry endpoint. To do this we must include a `collector.yaml` config file with our function.

Create a `collector.yaml` file in your function's root directory with the following contents:

```yaml
receivers:
  otlp:
    protocols:
      grpc:
      http:

exporters:
  otlp:
    endpoint: ${NEW_RELIC_OPENTELEMETRY_ENDPOINT}
    headers:
      api-key: ${NEW_RELIC_LICENSE_KEY}

service:
  pipelines:
    traces:
      receivers: [otlp]
      exporters: [otlp]
    metrics:
      receivers: [otlp]
      exporters: [otlp]
    logs:
      receivers: [otlp]
      exporters: [otlp]
```

Bundle this `collector.yaml` file in the root directory of your function's zip package and re-deploy.

1.  Open your function in the [Lambda Console](https://console.aws.amazon.com/lambda).
2.  Choose **Configuration** and then **Environment variables**.
3.  Under **Environment variables**, choose **Edit**.
4.  Choose **Add environment variable**.
5.  For the **Key** set `OPENTELEMETRY_COLLECTOR_CONFIG_FILE` and set the **Value** to `/var/task/collector.yaml`.
6.  Then choose **Save**.

For SAM and CloudFormation templates, add this to your function's properties:

```yaml
yourFunctionHere:
  Type: AWS::Serverless::Function
  Properties:
    # ...
    Environment:
      Variables:
        # ...
        OPENTELEMETRY_COLLECTOR_CONFIG_FILE: /var/task/collector.yaml
```

> #### ⚠️ IMPORTANT
>
> This assumes you bundled your `collector.yaml` in your function's root directory. If you bundled it somewhere else, replace `/var/task/collector.yaml` with the path to your `collector.yaml`.

## Step 5: View your data in the New Relic UI [view-data]

First you will want to [invoke your Lambda function](https://docs.aws.amazon.com/lambda/latest/dg/lambda-invocation.html) a few times to start generating telemetry. From there, head over to New Relic to find your [traces](https://one.newrelic.com/launcher/nr1-core.explorer?overlay=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), [metrics](https://one.newrelic.com/launcher/nr1-core.explorer?overlay=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), and [logs](https://one.newrelic.com/launcher/nr1-core.explorer?overlay=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).

Your telemetry will not appear under New Relic Serverless. Instead, you will find your telemetry data under the New Relic OpenTelemetry Nerdlets.

## Automatic instrumentation overhead [#auto-inst]

ADOT Lambda Layer for Java auto-instrumentation agent has a notable impact on startup
time on AWS Lambda, and you will generally need to use this along with [provisioned concurrency](https://docs.aws.amazon.com/lambda/latest/dg/provisioned-concurrency.html) to serve production requests without causing timeouts on initial requests while it initializes. We recommend testing this configuration in a non-production environment first to determine the appropriate settings for your use case.

Alternatively, you can use the following manual instrumentation method. By default, manual instrumentation requires fewer resources at function initialization. However, this
method requires a code change in most cases.

## Manual instrumentation [#manual-inst]

The manual instrumentation method is similar to the automatic instrumentation procedure in this document. The only difference is the Lambda Layer ARN you specify in [step 1](#install).

For manual instrumentation, instead of using the layer ARNs in [Step 2](#install), use one of the layer ARNs in the list below for your function's architecture:

-   AMD64 / X86_64: `arn:aws:lambda:{region}:901920570463:layer:aws-otel-java-wrapper-amd64-ver-1-11-1:1`
-   ARM64: `arn:aws:lambda:{region}:901920570463:layer:aws-otel-java-wrapper-arm64-ver-1-11-1:1`

Replace the `{region}` with your AWS region, such as `us-east-1`.

All other steps remain the same.

This alternative Lambda Layer will still wrap your Lambda function like the automatic method. It will also instrument the [AWS SDK](https://github.com/open-telemetry/opentelemetry-java-instrumentation/tree/main/instrumentation/aws-sdk/aws-sdk-2.2/library) automatically. But all other libraries you use will require you to include
the library's OpenTelemetry instrumentation library from the [OpenTelemetry instrumentation repository](https://github.com/open-telemetry/opentelemetry-java-instrumentation)
in your function's dependencies and modify your code to initialize it.

You can see an [example with OKHttp on GitHub](https://github.com/open-telemetry/opentelemetry-lambda/tree/main/java#sample-applications).

> #### ⚠️ IMPORTANT
>
> Refer to the [latest ARNs published by AWS](https://aws-otel.github.io/docs/getting-started/lambda/lambda-java) to verify the layer ARNs above are up to date.

## Distributed Tracing [#distributed-tracing]

In some cases you may see fragmented distributed traces within New Relic with this configuration. This occurs when a trace starts or involves a service that is outside the ADOT context (for example, a managed AWS service). Spans from that service are created by X-Ray, not OpenTelemetry, and ADOT does not forward them to New Relic. Although the traces appear fragmented, they still provide complete insight into performance within the Lambda function as well as other services whose spans were forwarded to New Relic.

## More information [#more-info]

For more information, check out the [New Relic OpenTelemetry quick start](https://docs.newrelic.com/docs/more-integrations/open-source-telemetry-integrations/opentelemetry/opentelemetry-quick-start).