The Datadog Serverless Framework plugin can be used to automatically configure and deploy your lambda with ASM.

To install and configure the Datadog Serverless Framework plugin:

1. Install the Datadog Serverless Framework plugin:

   serverless plugin install --name serverless-plugin-datadog
   

2. Enable ASM by updating your serverless.yml with the enableASM configuration parameter:

   custom:
     datadog:
       enableASM: true
   

   Overall, your new serverless.yml file should contain at least:

   custom:
     datadog:
       apiKeySecretArn: "{Datadog_API_Key_Secret_ARN}" # or apiKey
       enableDDTracing: true
       enableASM: true
   

   See also the complete list of plugin parameters to further configure your lambda settings.

3. Redeploy the function and invoke it. After a few minutes, it appears in ASM views.

The Datadog CLI modifies existing Lambda function configurations to enable instrumentation without requiring a new deployment. It is the quickest way to get started with Datadog’s serverless monitoring.

If you are configuring initial tracing for your functions, perform the following steps:

1. Install the Datadog CLI client:

   npm install -g @datadog/datadog-ci
   

2. If you are new to Datadog serverless monitoring, launch the Datadog CLI in interactive mode to guide your first installation for a quick start, and you can ignore the remaining steps. To permanently install Datadog for your production applications, skip this step and follow the remaining ones to run the Datadog CLI command in your CI/CD pipelines after your normal deployment.

   datadog-ci lambda instrument -i --appsec
   

3. Configure the AWS credentials:

   Datadog CLI requires access to the AWS Lambda service, and depends on the AWS JavaScript SDK to resolve the credentials. Ensure your AWS credentials are configured using the same method you would use when invoking the AWS CLI.

4. Configure the Datadog site:

   export DATADOG_SITE="<DATADOG_SITE>"
   

   Replace <DATADOG_SITE> with (ensure the correct Datadog site is selected on the right-hand side of this page).

5. Configure the Datadog API key:

   Datadog recommends saving the Datadog API key in AWS Secrets Manager for security. The key needs to be stored as a plaintext string (not a JSON blob). Ensure your Lambda functions have the required secretsmanager:GetSecretValue IAM permission.

   export DATADOG_API_KEY_SECRET_ARN="<DATADOG_API_KEY_SECRET_ARN>"
   

   For testing purposes, you can also set the Datadog API key in plaintext:

   export DATADOG_API_KEY="<DATADOG_API_KEY>"
   

6. Instrument your Lambda functions:

   To instrument your Lambda functions, run the following command.

   datadog-ci lambda instrument --appsec -f <functionname> -f <another_functionname> -r <aws_region> -v 100 -e 65
   

   To fill in the placeholders:

   • Replace <functionname> and <another_functionname> with your Lambda function names.
   • Alternatively, you can use --functions-regex to automatically instrument multiple functions whose names match the given regular expression.
   • Replace <aws_region> with the AWS region name.

   Note: Instrument your Lambda functions in a development or staging environment first. If the instrumentation result is unsatisfactory, run uninstrument with the same arguments to revert the changes.

   Additional parameters can be found in the CLI documentation.

The Datadog CDK Construct automatically installs Datadog on your functions using Lambda Layers, and configures your functions to send metrics, traces, and logs to Datadog through the Datadog Lambda Extension.

1. Install the Datadog CDK constructs library:

   # For AWS CDK v1
   pip install datadog-cdk-constructs
   
   # For AWS CDK v2
   pip install datadog-cdk-constructs-v2
   

2. Instrument your Lambda functions

   # For AWS CDK v1
   from datadog_cdk_constructs import Datadog
   # NOT SUPPORTED IN V1
   
   # For AWS CDK v2
   from datadog_cdk_constructs_v2 import Datadog
   
   datadog = Datadog(self, "Datadog",
       python_layer_version=100,
       extension_layer_version=65,
       site="<DATADOG_SITE>",
       api_key_secret_arn="<DATADOG_API_KEY_SECRET_ARN>", // or api_key
       enable_asm=True,
     )
   datadog.add_lambda_functions([<LAMBDA_FUNCTIONS>])
   

   To fill in the placeholders:

   • Replace <DATADOG_SITE> with (ensure the correct SITE is selected on the right).
   • Replace <DATADOG_API_KEY_SECRET_ARN> with the ARN of the AWS secret where your Datadog API key is securely stored. The key needs to be stored as a plaintext string (not a JSON blob). The secretsmanager:GetSecretValue permission is required. For quick testing, you can use apiKey instead and set the Datadog API key in plaintext.

   More information and additional parameters can be found on the Datadog CDK documentation.

3. Enable ASM by adding the following environment variables on your function deployment:

   environment:
     AWS_LAMBDA_EXEC_WRAPPER: /opt/datadog_wrapper
     DD_SERVERLESS_APPSEC_ENABLED: true
   

4. For Node and Python functions only, double-check that the function’s handler is set correctly:

   • Node: Set your function’s handler to /opt/nodejs/node_modules/datadog-lambda-js/handler.handler.
     • Also, set the environment variable DD_LAMBDA_HANDLER to your original handler, for example, myfunc.handler.
   • Python: Set your function’s handler to datadog_lambda.handler.handler.
     • Also, set the environment variable DD_LAMBDA_HANDLER to your original handler, for example, myfunc.handler.

5. Redeploy the function and invoke it. After a few minutes, it appears in ASM views.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN npm install --prefix /dd_tracer/node dd-trace --save
ENV DD_SERVICE=datadog-demo-run-nodejs
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["/nodejs/bin/node", "/path/to/your/app.js"]

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Copy the Datadog Node.JS tracer into your Docker image.

   RUN npm install --prefix /dd_tracer/node dd-trace --save
   

   If you install the Datadog tracer library directly in your application, as outlined in the manual tracer instrumentation instructions, omit this step.

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-nodejs
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   ENV DD_APPSEC_ENABLED=1
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your binary application wrapped in the entrypoint. Adapt this line to your needs.

   CMD ["/nodejs/bin/node", "/path/to/your/app.js"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN npm install --prefix /dd_tracer/node dd-trace --save
ENV DD_SERVICE=datadog-demo-run-nodejs
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
CMD ["/app/datadog-init", "/nodejs/bin/node", "/path/to/your/app.js"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN npm install --prefix /dd_tracer/node dd-trace --save
ENV DD_SERVICE=datadog-demo-run-nodejs
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["/your_entrypoint.sh", "/nodejs/bin/node", "/path/to/your/app.js"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN pip install --target /dd_tracer/python/ ddtrace
ENV DD_SERVICE=datadog-demo-run-python
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["/dd_tracer/python/bin/ddtrace-run", "python", "app.py"]

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Install the Datadog Python tracer.

   RUN pip install --target /dd_tracer/python/ ddtrace
   

   If you install the Datadog tracer library directly in your application, as outlined in the manual tracer instrumentation instructions, omit this step.

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-python
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   ENV DD_APPSEC_ENABLED=1
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your binary application wrapped in the entrypoint, launched by the Datadog trace library. Adapt this line to your needs.

   CMD ["/dd_tracer/python/bin/ddtrace-run", "python", "app.py"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN pip install --target /dd_tracer/python/ ddtrace
ENV DD_SERVICE=datadog-demo-run-python
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
CMD ["/app/datadog-init", "/dd_tracer/python/bin/ddtrace-run", "python", "app.py"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
RUN pip install --target /dd_tracer/python/ ddtrace
ENV DD_SERVICE=datadog-demo-run-python
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["your_entrypoint.sh", "/dd_tracer/python/bin/ddtrace-run", "python", "app.py"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD 'https://dtdg.co/latest-java-tracer' /dd_tracer/java/dd-java-agent.jar
ENV DD_SERVICE=datadog-demo-run-java
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["./mvnw", "spring-boot:run"]

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Add the Datadog Java tracer to your Docker image.

   ADD 'https://dtdg.co/latest-java-tracer' /dd_tracer/java/dd-java-agent.jar
   

   If you install the Datadog tracer library directly in your application, as outlined in the manual tracer instrumentation instructions, omit this step.

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-java
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   ENV DD_APPSEC_ENABLED=1
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your binary application wrapped in the entrypoint. Adapt this line to your needs.

   CMD ["./mvnw", "spring-boot:run"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD 'https://dtdg.co/latest-java-tracer' /dd_tracer/java/dd-java-agent.jar
ENV DD_SERVICE=datadog-demo-run-java
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
CMD ["/app/datadog-init", "./mvnw", "spring-boot:run"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD 'https://dtdg.co/latest-java-tracer' /dd_tracer/java/dd-java-agent.jar
ENV DD_SERVICE=datadog-demo-run-java
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["your_entrypoint.sh", "./mvnw", "spring-boot:run"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Manually install the Go tracer before you deploy your application. Compile your go binary with the “appsec” tag enabled (go build --tags "appsec" ...). Add the following instructions and arguments to your Dockerfile:

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENTRYPOINT ["/app/datadog-init"]
ENV DD_SERVICE=datadog-demo-run-go
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-go
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   ENV DD_APPSEC_ENABLED=1
   

4. Execute your binary application wrapped in the entrypoint. Adapt this line to your needs.

   CMD ["/path/to/your-go-binary"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENV DD_SERVICE=datadog-demo-run-go
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
CMD ["/app/datadog-init", "/path/to/your-go-binary"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENV DD_SERVICE=datadog-demo-run-go
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["your_entrypoint.sh", "/path/to/your-go-binary"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
# For arm64 use datadog-dotnet-apm-2.57.0.arm64.tar.gz
# For alpine use datadog-dotnet-apm-2.57.0-musl.tar.gz
ARG TRACER_VERSION
ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v${TRACER_VERSION}/datadog-dotnet-apm-${TRACER_VERSION}.tar.gz /tmp/datadog-dotnet-apm.tar.gz
RUN mkdir -p /dd_tracer/dotnet/ && tar -xzvf /tmp/datadog-dotnet-apm.tar.gz -C /dd_tracer/dotnet/ && rm /tmp/datadog-dotnet-apm.tar.gz
ENV DD_SERVICE=datadog-demo-run-dotnet
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["dotnet", "helloworld.dll"]

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Copy the Datadog .NET tracer into your Docker image.

   # For arm64 use datadog-dotnet-apm-2.57.0.arm64.tar.gz
   # For alpine use datadog-dotnet-apm-2.57.0-musl.tar.gz
   ARG TRACER_VERSION
   ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v${TRACER_VERSION}/datadog-dotnet-apm-${TRACER_VERSION}.tar.gz /tmp/datadog-dotnet-apm.tar.gz
   
   RUN mkdir -p /dd_tracer/dotnet/ && tar -xzvf /tmp/datadog-dotnet-apm.tar.gz -C /dd_tracer/dotnet/ && rm /tmp/datadog-dotnet-apm.tar.gz
   

   If you install the Datadog tracer library directly in your application, as outlined in the manual tracer instrumentation instructions, omit this step.

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-dotnet
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   ENV DD_APPSEC_ENABLED=1
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your binary application wrapped in the entrypoint. Adapt this line to your needs.

   CMD ["dotnet", "helloworld.dll"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
# For arm64 use datadog-dotnet-apm-2.57.0.arm64.tar.gz
# For alpine use datadog-dotnet-apm-2.57.0-musl.tar.gz
ARG TRACER_VERSION
ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v${TRACER_VERSION}/datadog-dotnet-apm-${TRACER_VERSION}.tar.gz /tmp/datadog-dotnet-apm.tar.gz
RUN mkdir -p /dd_tracer/dotnet/ && tar -xzvf /tmp/datadog-dotnet-apm.tar.gz -C /dd_tracer/dotnet/ && rm /tmp/datadog-dotnet-apm.tar.gz
ENV DD_SERVICE=datadog-demo-run-dotnet
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
CMD ["/app/datadog-init", "dotnet", "helloworld.dll"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
# For arm64 use datadog-dotnet-apm-2.57.0.arm64.tar.gz
# For alpine use datadog-dotnet-apm-2.57.0-musl.tar.gz
ARG TRACER_VERSION
ADD https://github.com/DataDog/dd-trace-dotnet/releases/download/v${TRACER_VERSION}/datadog-dotnet-apm-${TRACER_VERSION}.tar.gz /tmp/datadog-dotnet-apm.tar.gz
RUN mkdir -p /dd_tracer/dotnet/ && tar -xzvf /tmp/datadog-dotnet-apm.tar.gz -C /dd_tracer/dotnet/ && rm /tmp/datadog-dotnet-apm.tar.gz
ENV DD_SERVICE=datadog-demo-run-dotnet
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENTRYPOINT ["/app/datadog-init"]
CMD ["your_entrypoint.sh", "dotnet", "helloworld.dll"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Manually install the Ruby tracer before you deploy your application. See the example application.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENV DD_SERVICE=datadog-demo-run-ruby
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENV DD_TRACE_PROPAGATION_STYLE=datadog
ENTRYPOINT ["/app/datadog-init"]
CMD ["rails", "server", "-b", "0.0.0.0"]

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. (Optional) add Datadog tags

   ENV DD_SERVICE=datadog-demo-run-ruby
   ENV DD_ENV=datadog-demo
   ENV DD_APPSEC_ENABLED=1
   ENV DD_VERSION=1
   

3. This environment variable is needed for trace propagation to work properly in Cloud Run. Ensure that you set this variable for all Datadog-instrumented downstream services.

   ENV DD_TRACE_PROPAGATION_STYLE=datadog
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your binary application wrapped in the entrypoint. Adapt this line to your needs.

   CMD ["rails", "server", "-b", "0.0.0.0"]
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENV DD_SERVICE=datadog-demo-run-ruby
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENV DD_TRACE_PROPAGATION_STYLE=datadog
CMD ["/app/datadog-init", "rails", "server", "-b", "0.0.0.0"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ENV DD_SERVICE=datadog-demo-run-ruby
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENV DD_APPSEC_ENABLED=1
ENV DD_TRACE_PROPAGATION_STYLE=datadog
ENTRYPOINT ["/app/datadog-init"]
CMD ["your_entrypoint.sh", "rails", "server", "-b", "0.0.0.0"]

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Add the following instructions and arguments to your Dockerfile.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD https://github.com/DataDog/dd-trace-php/releases/latest/download/datadog-setup.php /datadog-setup.php
RUN php /datadog-setup.php --php-bin=all
ENV DD_SERVICE=datadog-demo-run-php
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENTRYPOINT ["/app/datadog-init"]

# use the following for an Apache and mod_php based image
RUN sed -i "s/Listen 80/Listen 8080/" /etc/apache2/ports.conf
EXPOSE 8080
CMD ["apache2-foreground"]

# use the following for an Nginx and php-fpm based image
RUN ln -sf /dev/stdout /var/log/nginx/access.log && ln -sf /dev/stderr /var/log/nginx/error.log
EXPOSE 8080
CMD php-fpm; nginx -g daemon off;

Note: The datadog-init entrypoint wraps your process and collects logs from it. To get logs working properly, ensure that your Apache, Nginx, or PHP processes are writing output to stdout.

Explanation

1. Copy the Datadog serverless-init into your Docker image.

   COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
   

2. Copy and install the Datadog PHP tracer.

   ADD https://github.com/DataDog/dd-trace-php/releases/latest/download/datadog-setup.php /datadog-setup.php
   RUN php /datadog-setup.php --php-bin=all
   

   If you install the Datadog tracer library directly in your application, as outlined in the manual tracer instrumentation instructions, omit this step.

3. (Optional) Add Datadog tags.

   ENV DD_SERVICE=datadog-demo-run-php
   ENV DD_ENV=datadog-demo
   ENV DD_VERSION=1
   

4. Change the entrypoint to wrap your application in the Datadog serverless-init process. Note: If you already have an entrypoint defined inside your Dockerfile, see the alternative configuration.

   ENTRYPOINT ["/app/datadog-init"]
   

5. Execute your application.

   Use the following for an Apache and mod_php based image:

   RUN sed -i "s/Listen 80/Listen 8080/" /etc/apache2/ports.conf
   EXPOSE 8080
   CMD ["apache2-foreground"]
   

   Use the following for an Nginx and php-fpm based image:

   RUN ln -sf /dev/stdout /var/log/nginx/access.log && ln -sf /dev/stderr /var/log/nginx/error.log
   EXPOSE 8080
   CMD php-fpm; nginx -g daemon off;
   

Alternative configuration

If you already have an entrypoint defined inside your Dockerfile, and you are using an Apache and mod_php based image, you can instead modify the CMD argument.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD https://github.com/DataDog/dd-trace-php/releases/latest/download/datadog-setup.php /datadog-setup.php
RUN php /datadog-setup.php --php-bin=all
ENV DD_SERVICE=datadog-demo-run-php
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
RUN sed -i "s/Listen 80/Listen 8080/" /etc/apache2/ports.conf
EXPOSE 8080
CMD ["/app/datadog-init", "apache2-foreground"]

If you require your entrypoint to be instrumented as well, you can swap your entrypoint and CMD arguments instead. For more information, see How serverless-init works.

COPY --from=datadog/serverless-init:1 /datadog-init /app/datadog-init
ADD https://github.com/DataDog/dd-trace-php/releases/latest/download/datadog-setup.php /datadog-setup.php
RUN php /datadog-setup.php --php-bin=all
ENV DD_SERVICE=datadog-demo-run-php
ENV DD_ENV=datadog-demo
ENV DD_VERSION=1
ENTRYPOINT ["/app/datadog-init"]

# use the following for an Apache and mod_php based image
RUN sed -i "s/Listen 80/Listen 8080/" /etc/apache2/ports.conf
EXPOSE 8080
CMD ["your_entrypoint.sh", "apache2-foreground"]

# use the following for an Nginx and php-fpm based image
RUN ln -sf /dev/stdout /var/log/nginx/access.log && ln -sf /dev/stderr /var/log/nginx/error.log
EXPOSE 8080
CMD your_entrypoint.sh php-fpm; your_entrypoint.sh nginx -g daemon off;

As long as your command to run is passed as an argument to datadog-init, you will receive full instrumentation.

Go to General settings and add the following to the Startup Command field:

curl -s https://raw.githubusercontent.com/DataDog/datadog-aas-linux/v1.4.0/datadog_wrapper | bash

Download the datadog_wrapper file from the releases and upload it to your application with the Azure CLI command:

  az webapp deploy --resource-group <group-name> --name <app-name> --src-path <path-to-datadog-wrapper> --type=startup