Instrumenting Ruby Serverless Applications


The Datadog Forwarder Lambda function is required to ingest AWS Lambda traces, enhanced metrics, custom metrics, and logs.


  1. Install the Datadog Lambda Library

    The Datadog Lambda Library can be installed as a layer or a gem. For most functions, Datadog recommends installing the library as a layer. If your Lambda function is deployed as a container image, you must install the library as a gem.

    The minor version of the datadog-lambda gem always matches the layer version. For example, datadog-lambda v0.5.0 matches the content of layer version 5.

    • Option A: Configure the layers for your Lambda function using the ARN in the following format.

      # For regular regions
      # For us-gov regions

      Replace <AWS_REGION> with a valid AWS region, such as us-east-1.

    • Option B: If you cannot use the prebuilt Datadog Lambda layer, you can add the following to your Gemfile as an alternative:

      gem 'datadog-lambda'
      gem 'ddtrace'

      ddtrace contains native extensions that must be compiled for Amazon Linux to work with AWS Lambda. Datadog therefore recommends that you build and deploy your Lambda as a container image. If your function cannot be deployed as a container image and you would like to use Datadog APM, Datadog recommends installing the Lambda Library as a layer instead of as a gem.

      Install gcc, gmp-devel, and make prior to running bundle install in your function’s Dockerfile to ensure that the native extensions can be successfully compiled.

      FROM <base image>
      # assemble your container image
      RUN yum -y install gcc gmp-devel make
      RUN bundle config set path 'vendor/bundle'
      RUN bundle install
  2. Configure your Lambda functions

    Enable Datadog APM and wrap your Lambda handler function using the wrapper provided by the Datadog Lambda library.

    require 'datadog/lambda'
    Datadog::Lambda.configure_apm do |c|
    # Enable the instrumentation
    def handler(event:, context:)
        Datadog::Lambda.wrap(event, context) do
            return { statusCode: 200, body: 'Hello World' }
  3. Subscribe the Datadog Forwarder to log groups

    Subscribe the Datadog Forwarder Lambda function to each of your function’s log groups to send metrics, traces and logs to Datadog.

    1. Install the Datadog Forwarder if you haven’t.
    2. Subscribe the Datadog Forwarder to your function’s log groups.

What’s next?

  • You can now view metrics, logs, and traces on the Serverless Homepage.
  • See the sample code to monitor custom business logic
  • See the troubleshooting guide if you have trouble collecting the telemetry
  • See the advanced configurations to
    • connect your telemetry using tags
    • collect telemetry for AWS API Gateway, SQS, etc.
    • capture the Lambda request and response payloads
    • link errors of your Lambda functions to your source code
    • filter or scrub sensitive information from logs or traces

Monitor custom business logic

If you would like to submit a custom metric or span, see the sample code below:

require 'ddtrace'
require 'datadog/lambda'

Datadog::Lambda.configure_apm do |c|
# Enable the instrumentation

def handler(event:, context:)
    # Apply the Datadog wrapper
    Datadog::Lambda::wrap(event, context) do
        # Add custom tags to the lambda function span,
        # does NOT work when X-Ray tracing is enabled
        current_span = Datadog::Tracing.active_span
        current_span.set_tag('', '123456')


        Datadog::Tracing.trace('') do |span|
          puts "Hello, World!"

        # Submit a custom metric
          'coffee_house.order_value', # metric name
          12.45, # metric value
          time:, # optional, must be within last 20 mins
          "product":"latte", # tag
          "order":"online" # another tag

# Instrument the function
def some_operation()
    Datadog::Tracing.trace('some_operation') do |span|
        # Do something here

For more information on custom metric submission, see Serverless Custom Metrics. For additional details on custom instrumentation, see the Datadog APM documentation for custom instrumentation.

Further Reading