Instrumenting Ruby Applications

Instrumenting Ruby Applications

Required setup

If not already configured:

After you have installed the AWS integration and the Datadog Forwarder, follow these steps to instrument your application to send metrics, logs, and traces to Datadog.



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. E.g., datadog-lambda v0.5.0 matches the content of layer version 5.

Using the layer

Configure the layers for your Lambda function using the ARN in the following format.

# For regular regions

# For us-gov regions

The available RUNTIME options are Ruby2-5 and Ruby2-7. For VERSION, see the latest release. For example:


If your Lambda function is configured to use code signing, you must add Datadog’s Signing Profile ARN (arn:aws:signer:us-east-1:464622532012:/signing-profiles/DatadogLambdaSigningProfile/9vMI9ZAGLc) to your function’s Code Signing Configuration before you can add the Datadog Lambda library as a layer.

Using the gem

Add the following to your Gemfile:

gem 'datadog-lambda'

To use Datadog APM, you must also add ddtrace as a second dependency in your Gemfile.

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

Configure the function

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' }


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.


Although it’s optional, Datadog highly recommends tagging you serverless applications with the env, service, and version tags following the unified service tagging documentation.


After configuring your function following the steps above, view your metrics, logs, and traces on the Serverless homepage.

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.tracer.active_span
        current_span.set_tag('', '123456')


        Datadog.tracer.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.tracer.trace('some_operation') do |span|
        # Do something here

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

Further Reading