Quiz and Summary on Pipeline Monitoring, Maintenance and Auditing
The chapter outlines a comprehensive framework for monitoring, maintaining, and auditing AWS serverless data pipelines. It differentiates between application data logging and AWS service access logging, emphasizing the importance of structured JSON logging for actionable insights. Key components include metric filters for alarm triggering, performance tuning strategies for Glue and EMR, and audit trail configurations using CloudTrail. Advanced analysis tools like CloudWatch Logs Insights and Amazon EMR are highlighted for handling large volumes of logs and complex queries, ensuring efficient data management and compliance readiness.
Summary
This chapter established a complete observability and logging framework for AWS serverless data pipelines, progressing from foundational monitoring through performance optimization to audit-ready centralized logging and advanced analysis techniques.
Observability foundations
The observability stack begins with understanding two distinct logging categories. Application data logging captures custom events from ETL scripts, Lambda functions, and Glue jobs, while AWS service access logging records API-level activity through CloudTrail and S3 server access logs.
CloudWatch Logs organizes data using a two-level hierarchy in which log groups serve as containers that share retention and access settings, and log streams hold actual event data from individual sources. Structured JSON logging enables metric filters and Logs Insights queries to parse fields ...