20/05/2026
Free Book Practical DevOps AI Release Chapter 14
[Chapter 13: Multi-Source Log Integration]
- Understanding the challenge: Moving from single log files to real infrastructure.
- Building API clients: Connect to Elasticsearch, Kubernetes, and AWS CloudWatch.
- Authentication and security: Handle API keys, IAM roles, and service accounts properly.
- Query optimization: Fetch logs efficiently without overwhelming your systems.
- Error handling: Deal with API rate limits, timeouts, and service unavailability.
- Log format normalization: Create a unified structure from different log formats.
- Testing each connector: Verify each integration works before combining them.
[Chapter 14: Cross-System Correlation and Analysis]
- The power of correlation: Understanding how events connect across systems.
- Building the aggregation pipeline: Combine logs from multiple sources into a unified view.
- Teaching correlation: Write prompts that instruct the AI to link related events.
- Time-based correlation: Match events that happened around the same time across different systems.
- Contextual analysis: Build narratives like "service crashed because database hit connection limits after deployment changed timeout settings."
- Implementing the full analysis loop: Pull logs, aggregate, correlate, analyze, and report.
- Testing correlation logic: Verify the agent correctly identifies related events.