Today’s Build: The Observability Command Center
You’re running a distributed log processing cluster across 50 Kubernetes pods. Your logs show processing slowdowns, but is it network congestion, CPU throttling, or disk I/O saturation? Without unified monitoring, you’re diagnosing in the dark.
Today we integrate infrastructure metrics with log analysis, creating a single pane of glass that reveals the complete health story of your system. By lesson’s end, you’ll correlate log patterns with resource usage and predict failures before they impact users.
What You’ll Build:
Unified metrics collector aggregating infrastructure + application data
Real-time dashboard correlating logs with CPU/memory/network metrics
Intelligent alerting that combines infrastructure signals with log anomalies
Integration with Day 152’s Kubernetes operator for cluster-wide monitoring
Historical analysis showing resource impact on log processing performance
Why Infrastructure + Log Monitoring Integration Matters
Netflix processes 500 billion events daily. When their recommendation engine slows, they need instant answers: Is Java heap exhausted? Are disks saturated? Is network latency spiking? Their unified monitoring correlates GC pauses with request latency and disk I/O with batch processing throughput.
