Data Engineering Certification Prep Series – Tip #31

Real-Time Monitoring for Complex Data Pipelines on AWS

Problem

A company runs a large data processing pipeline with dozens of steps, built using Amazon S3, AWS Lambda, and AWS Step Functions. The business requires real-time alerts whenever any step succeeds or fails, across the entire pipeline. The challenge for the data engineer is to design a centralized, scalable, and real-time monitoring solution—without adding unnecessary complexity or latency.

Options Considered

Option A: Step Functions → S3 → S3 Event Notifications

• Notifications are written only after execution completes
• S3 events are not designed for workflow state monitoring

Option B: Lambda → S3 → S3 Event Notifications

• Requires custom logic in every Lambda
• Creates tight coupling and higher maintenance

Option C: AWS CloudTrail → SNS

• CloudTrail tracks API calls, not execution outcomes
• Delayed and noisy for operational alerts

Option D: Amazon EventBridge → SNS

• Native integration with AWS Step Functions
• Triggers on execution state changes (SUCCEEDED, FAILED, TIMED_OUT)
• Fully event-driven and real-time

Solution

Configure Amazon EventBridge to monitor Step Functions execution status changes and publish alerts to an Amazon SNS topic

This approach:

• Provides real-time notifications
• Requires zero custom code
• Scales naturally as pipeline complexity grows
• Keeps monitoring decoupled from business logic

SNS can then fan out alerts to email, Slack, PagerDuty, or incident-management systems.

Key Takeaways

• Event-driven architectures are ideal for pipeline observability
• Use EventBridge for state changes, not storage or audit services
• Avoid embedding monitoring logic inside Lambda functions
• AWS-native integrations often provide the cleanest and least-effort solution