Day 53: Centralized Logging Strategy - Debugging StreamSocial at Scale
What We’re Building Today
Today we’re implementing a production-grade centralized logging system using the ELK stack to debug a critical viral content scenario at StreamSocial. When a post goes viral (think millions of views in minutes), your distributed system generates logs across dozens of producers, brokers, and consumers. Without centralized logging, debugging becomes hunting through hundreds of log files across different servers—impossible at scale.
High-Level Goals:
Deploy ELK stack (Elasticsearch, Logstash, Kibana) for Kafka log aggregation
Implement structured JSON logging across all Kafka components
Build real-time log correlation to trace requests through the entire pipeline
Debug a viral content bottleneck using centralized log analysis
Create monitoring dashboards showing log patterns and anomalies
