Introduction
In this tutorial, we will build an automated data pipeline using AWS Glue, Athena, Lambda, EventBridge, and Step Functions. This pipeline will automate ETL jobs, making data processing seamless and efficient.
AWS ETL Workflow Orchestration
Overview of the Data Pipeline
We will create a Glue ETL job that reads data from an S3 data lake cataloged in AWS Glue. The job will be orchestrated using EventBridge, Lambda, and AWS Step Functions to ensure automated execution.
Understanding AWS Glue, EventBridge, and Step Functions
AWS Glue: A fully managed ETL service that helps prepare and transform data.
AWS EventBridge: A serverless event bus that connects applications using events.
AWS Step Functions: A visual workflow service that automates and coordinates AWS services.
Creating a Lambda Function to Trigger Glue ETL
Search for AWS Lambda in the AWS Console.
Click on "Create Function."
Provide a function name:
Futurex_Invoke_Glue_ETL.Select the runtime: Python 3.8.
Click "Create Function."
Modify the source code using Python and Boto3 SDK. This code will:
Create an instance of the Glue client.
Specify the Glue job name.
Trigger the Glue ETL job.
Assigning Permissions to Lambda
Before testing the Lambda function, we must ensure it has access to trigger the Glue job.
Go to AWS IAM.
Search for "Roles."
Find the role created for Lambda (
Futurex_Invoke_Glue_ETL_Role).Click on the role and attach the "AWSGlueServiceRole" policy.
Save the changes.
Testing the Lambda Function
Click "Test."
Provide a dummy event name.
Run the function and check the Glue interface to confirm the job execution.
Triggering Glue ETL Using Step Functions
Navigate to AWS Step Functions.
Create a new state machine using the visual editor.
Select "Start Job Run - AWS Glue."
Specify the Glue job name.
Click "Create" and execute the Step Function.
Confirming the Job Execution
Monitor the Step Function execution logs.
Check the Glue ETL job logs to confirm the execution.
Chaining Lambda Function with Step Functions
Instead of directly triggering a Glue job, Step Functions can trigger Lambda, which in turn triggers the ETL job.
Create a new Step Function with a blank template.
Select "Lambda Function" instead of "Glue Job" in the workflow.
Specify the Lambda function (
Futurex_Invoke_Glue_ETL).Click "Create" and execute the workflow.
Automating the Pipeline with AWS EventBridge
Create an EventBridge rule named
Futurex_ETL_S3.Set the event source as "S3 Object Created."
Specify the S3 bucket (
Futurex_Skills).Choose Step Functions as the target.
Select the previously created Step Function.
Click "Create Rule."
Testing End-to-End Automation
Upload a new file to the S3 bucket.
Check if the EventBridge rule triggers the Step Function.
Verify the Glue ETL job execution.
Conclusion
By integrating AWS Glue, Lambda, EventBridge, and Step Functions, we have successfully built an automated data pipeline. This approach ensures efficient and event-driven ETL job execution, enhancing data processing capabilities in AWS environments.
