Event-driven Data Preprocessing on AWS Lambda

Question

Pulumi · Accepted Answer

To set up an event-driven data preprocessing workflow with AWS Lambda, we'll create a Pulumi program that encompasses the following steps:

1. **Lambda Function**: Provision an AWS Lambda function that will contain the logic for data preprocessing. This function will be triggered by an event.
   
2. **CloudWatch Event Rule**: Define an AWS CloudWatch Event Rule that listens for a specific event pattern or schedule to trigger the Lambda function.

3. **Event Target**: Configure the event target for the CloudWatch Event Rule, pointing to the AWS Lambda function.

4. **IAM Role**: Create an IAM role with the necessary permissions for the Lambda function to run and for CloudWatch to invoke it.

5. **Permissions**: Assign invocation permissions for the CloudWatch Event Rule to execute the Lambda function.

Below is the detailed Pulumi program written in Python that creates this event-driven data preprocessing system on AWS:

```python
import pulumi
import pulumi_aws as aws

# Define the IAM role that will allow Lambda function to run and log its activity
lambda_role = aws.iam.Role("lambdaRole",
    assume_role_policy="""{
        "Version": "2012-10-17",
        "Statement": [{
            "Action": "sts:AssumeRole",
            "Principal": {
                "Service": "lambda.amazonaws.com"
            },
            "Effect": "Allow",
            "Sid": ""
        }]
    }""")

# Attach the AWS managed LambdaBasicExecutionRole policy to the role
lambda_exec_policy_attachment = aws.iam.RolePolicyAttachment("lambdaExecPolicyAttachment",
    role=lambda_role.name,
    policy_arn="arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole")

# Define the Lambda function
lambda_function = aws.lambda_.Function("dataPreprocessingFunction",
    runtime="python3.8",  # Example runtime, choose what's appropriate
    code=pulumi.FileArchive("./data_preprocessing.zip"),  # The path to the ZIP file containing your Lambda function code
    handler="data_preprocessing.handler",  # The handler method (entry point) within your Lambda code
    role=lambda_role.arn,
    timeout=180)  # Example timeout setting, adjust according to your needs

# Create a CloudWatch Event Rule to trigger the Lambda function
# This rule could be based on a schedule (e.g., run every hour) or a specific event pattern
event_rule = aws.cloudwatch.EventRule("dataPreprocessingTriggerRule",
    schedule_expression="rate(1 hour)",  # Example schedule every 1 hour
    # You could also specify an `event_pattern` instead of `schedule_expression` if needed
    description="Triggers the data preprocessing Lambda function every 1 hour")

# Target for the CloudWatch Event Rule that points to the Lambda function
event_target = aws.cloudwatch.EventTarget("dataPreprocessingTarget",
    rule=event_rule.name,
    arn=lambda_function.arn)

# Give CloudWatch Events permission to invoke the Lambda function
lambda_permission = aws.lambda_.Permission("lambdaPermission",
    action="lambda:InvokeFunction",
    principal="events.amazonaws.com",
    source_arn=event_rule.arn,
    function=lambda_function.name)

# Export the Lambda function ARN and name, so it can be easily referenced or invoked
pulumi.export('lambda_function_arn', lambda_function.arn)
pulumi.export('lambda_function_name', lambda_function.name)
```

Let's go through the program:

- We create an IAM role `lambdaRole` that the AWS Lambda function will assume to get the necessary permissions. This role has a trust relationship with the Lambda service.

- We attach the `AWSLambdaBasicExecutionRole` managed policy to our IAM role so that our Lambda function can write logs to Amazon CloudWatch.

- The `dataPreprocessingFunction` is our AWS Lambda function, using Python 3.8 runtime, with the code zipped and located in the local directory. The handler specifies the function that Lambda calls when your function is invoked.

- A CloudWatch Event Rule `dataPreprocessingTriggerRule` is created to trigger on a defined schedule (every 1 hour in this example). This rule can also be setup to trigger using event patterns, say when an object is uploaded to an S3 bucket or any other event that AWS Lambda can respond to.

- `dataPreprocessingTarget` is the event target that tells CloudWatch where to send the events, in this case, our Lambda function.

- `lambdaPermission` gives the necessary invocation permission for the CloudWatch Event to call the Lambda function.

Finally, we export the ARN and name of the Lambda function so you can easily locate or reference it in AWS or other Pulumi stacks.

As for the Lambda function code (`data_preprocessing.handler`), you would need to package your Python code into a ZIP file (`data_preprocessing.zip`). The handler function inside the Lambda code is what will be executed upon the event trigger. Please make sure you have this zipfile ready and that it contains all the necessary dependencies.

Remember to replace the `runtime`, `code`, and `handler` properties of the `dataPreprocessingFunction` based on your Lambda function specifics. Similarly, if you are triggering the Lambda on a different event, adjust the `schedule_expression` or use an `event_pattern` in the CloudWatch Event Rule.