In the Data Pipeline architecture, the movement of data from Source (S3) -> Processing (Glue ETL) -> Analysis (Athena/Redshift) requires robust security and monitoring mechanisms. The objectives of this section aim to help learners:
Access Control Management (AWS IAM): Ensure the principle of least privilege. Precisely allocate the necessary Roles so that AWS Glue and Redshift can securely communicate with the S3 Data Lake.
Auditing and Logging (AWS CloudTrail): Track and record all operations (API Calls) that interact with the system, enabling quick tracing when misconfigurations or unauthorized access occur.
Pipeline Status Monitoring (Amazon CloudWatch / EventBridge): Capture the system status in real-time. Catch important event streams such as when a data processing job completes or fails.
Automated Alerting (Amazon SNS): Automate the distribution of notifications (via Email/SMS) to the Data Engineering/Admin team immediately when the Data Pipeline encounters an issue.