1. Enable all logging for your Step Function. In your AWS console, open your state machine. Click Edit and find the Logging section. There, set Log level to ALL and enable the Include execution data checkbox.

2. Ensure you have deployed the Datadog Lambda Forwarder, and that you are using v3.130.0 or later. As an alternative, you may also use Amazon Data Firehose, which can subscribe to Amazon CloudWatch log groups across multiple AWS regions. However, it requires that the Step Functions log group name begins with “/aws/vendedlogs/states/”.

3. Subscribe CloudWatch logs to the Datadog Lambda Forwarder. If the log group name for your Step Functions begins with “/aws/vendedlogs/states/”, you can also use the Serverless Framework or the Datadog CLI to configure the subscription.

   Automatic custom installation

   1. Ensure that you have set up the Datadog-AWS integration.
   2. In Datadog, open the AWS integration tile, and view the Configuration tab.
   3. On the left, select the AWS account where your Step Function is running. Open the Log Collection tab.
   4. In the Log Autosubscription section, under Autosubscribe Forwarder Lambda Functions, enter the ARN of your Datadog Lambda Forwarder, as noted previously. Click Add.
   5. Toggle on Step Functions CloudWatch Logs. Changes take 15 minutes to take effect.

   Note: Log Autosubscription requires your Lambda Forwarder and Step Function to be in the same region.

   Manual custom installation

   1. Open your AWS console and go to your Datadog Lambda Forwarder. In the Function overview section, click on Add trigger.
   2. Under Add trigger, in the Trigger configuration section, use the Select a source dropdown to select CloudWatch Logs.
   3. Under Log group, select the log group for your state machine. For example, /aws/vendedlogs/states/my-state-machine.
   4. Enter a filter name. You can choose to name it “empty filter” and leave the Filter pattern box blank.

4. Set up tags. Open your AWS console and go to your Step Functions state machine. Open the Tags section and add env:<ENV_NAME>, service:<SERVICE_NAME>, and version:<VERSION> tags. The env tag is required to see traces in Datadog, and it defaults to dev. The service tag defaults to the state machine’s name. The version tag defaults to 1.0.

5. To enable tracing, you have two options:

   • Per Step Function: Add the DD_TRACE_ENABLED tag to each Step Function and set the value to true.
   • At the Forwarder level: To enable tracing for all Step Functions connected to the Forwarder, you have two options:
     • When creating the CloudFormation stack for the forwarder, set the DdStepFunctionsTraceEnabled parameter to true.
     • After the forwarder is created, set the environment variable DD_STEP_FUNCTIONS_TRACE_ENABLED to true.

1. If you haven’t already, install the Datadog CLI v2.18.0+.

   npm install -g @datadog/datadog-ci
   

2. Ensure you have deployed the Datadog Lambda Forwarder, and that you are using v3.130.0 or later. As an alternative, you can also use Amazon Data Firehose, which can subscribe to Amazon CloudWatch log groups across multiple AWS regions. Your Step Functions log group name should use this format:

   /aws/vendedlogs/states/<STEP_FUNCTION_NAME>-Logs
   

   Optionally, you can add your environment to this log group name: /aws/vendedlogs/states/<STEP_FUNCTION_NAME>-Logs-<ENV>

   Take note of your Forwarder’s ARN.

3. Run:

   datadog-ci stepfunctions instrument \
    --step-function <STEP_FUNCTION_ARN> \
    --forwarder <FORWARDER_ARN> \
    --env <ENVIRONMENT> \
    --propagate-upstream-trace \
    --merge-step-function-and-lambda-traces
   

   • Replace <STEP_FUNCTION_ARN> with the ARN of your Step Function. Repeat the --step-function flag for each Step Function you wish to instrument.
   • Replace <FORWARDER_ARN> with the ARN of your Datadog Lambda Forwarder. This step configures the log stream subscription for the Forwarder.
   • Replace <ENVIRONMENT> with the environment tag you would like to apply to your Step Functions.

   For more information about the datadog-ci stepfunctions command, see the Datadog CLI documentation.

Note: The datadog-ci stepfunctions instrument command automatically enables tracing.

1. If you haven’t already, install the Datadog Serverless Framework Plugin v5.40.0+:

   serverless plugin install --name serverless-plugin-datadog
   

2. Ensure you have deployed the Datadog Lambda Forwarder, and that you are using v3.130.0 or later. As an alternative, you can also use Amazon Data Firehose, which can subscribe to Amazon CloudWatch log groups across multiple AWS regions. Your Step Functions log group name should use this format:

   /aws/vendedlogs/states/<STEP_FUNCTION_NAME>-Logs-<STAGE>
   

3. Add the following to your serverless.yml:

   custom:
     datadog:
       site: <DATADOG_SITE>
       apiKeySecretArn: <DATADOG_API_KEY_SECRET_ARN>
       forwarderArn: <FORWARDER_ARN>
       enableStepFunctionsTracing: true
       propagateUpstreamTrace: true
       mergeStepFunctionAndLambdaTraces: true
   

   • Replace <DATADOG_SITE> with (ensure the correct DATADOG SITE is selected on the right of this docs page).
   • 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 instead use apiKey and set the Datadog API key in plaintext.
   • Replace <FORWARDER_ARN> with the ARN of your Datadog Lambda Forwarder. This step configures the log stream subscription for the Forwarder.

   For additional settings, see Datadog Serverless Framework Plugin - Configuration parameters.

   Note: The enableStepFunctionsTracing: true line automatically enables tracing.

1. Ensure you have deployed the Datadog Lambda Forwarder, and that you are using v3.130.0 or later.

2. Install Datadog’s CDK Construct Library, which automatically sets up logging and subscribes the Forwarder to the log group.

Example

from aws_cdk import (
    aws_stepfunctions as sfn,
    aws_stepfunctions_tasks as tasks,
)
from datadog_cdk_constructs_v2 import DatadogStepFunctions, DatadogLambda

state_machine = sfn.StateMachine(...)
datadog_sfn = DatadogStepFunctions(
    self,
    "DatadogSfn",
    env="<ENV>", # e.g. "dev"
    service="<SERVICE>", # e.g. "my-cdk-service"
    version="<VERSION>", # e.g. "1.0.0"
    forwarderArn="<FORWARDER_ARN>", # e.g. "arn:test:forwarder:sa-east-1:12345678:1"
    tags=<TAGS>, # optional, e.g. "custom-tag-1:tag-value-1,custom-tag-2:tag-value-2"
)
datadog_sfn.add_state_machines([child_state_machine, parent_state_machine])

For sample stacks and additional code examples, see CDK Examples for Instrumenting AWS Step Functions.

Note: The Datadog Step Functions CDK construct automatically enables tracing.

1. Ensure you have deployed the Datadog Lambda Forwarder, and that you are using v3.130.0 or later.

2. Add the following to your template.yaml:

   Transform:
   - AWS::Serverless-2016-10-31
   - Name: DatadogServerless
      Parameters:
         stackName: !Ref "AWS::StackName"
         apiKey: "<DATADOG_API_KEY>"
         env: "<ENV>" # e.g. "dev"
         service: "<SERVICE>" # e.g. "my-sam-service"
         version: "<VERSION>" # e.g. "1.0.0"
         stepFunctionForwarderArn: "<FORWARDER_ARN>" # "arn:test:forwarder:sa-east-1:12345678:1"
         tags: "<TAGS>" # optional, e.g. "custom-tag-1:tag-value-1,custom-tag-2:tag-value-2"
   

For additional settings, see the documentation on GitHub.