Buglyst Blog
Learn to debug under pressure.
Playbooks for fast pattern recognition, guides for the full investigation, and articles for the engineering judgment around the edges.
17 playbooks · 509 guides · 95 articles · 12 linked practice labs ·skip to practice
Fast pattern recognition for the production failures engineers see most often.
1 playbook in Observability & Performance
Structured investigations for the failure modes engineers meet in real systems.
Slow API response: how to debug latency issues
An API endpoint that used to return in 50ms now takes 3 seconds. Find the bottleneck before your users notice.
Observability missing logs: how to debug gaps in logging and monitoring
A critical error happened in production but there are no logs for it. The log level is too high, logs are dropped under load, or the log pipeline has a silent failure.
Log says success but the user still fails: how to debug misleading logs
Your application logs 'Operation completed successfully' but the user sees an error or gets no result. The log is lying — it is logging intent, not outcome.
Diagnosing Hidden Performance Bottlenecks in React Apps
Cut through noise and pinpoint real React performance issues. This guide details actionable profiling, interpretation, and advanced optimization techniques.
Diagnosing Node.js Event Loop Lag and High Latency in Production
An advanced guide to investigating and resolving unexpected event loop lag and high request latency in live Node.js applications.
Node.js Heap Snapshot Analysis: Finding the Leak That Survived GC
A practical guide to analyzing Node.js heap snapshots to find memory leaks that survive garbage collection. Covers snapshot comparison, retaining paths, and hidden class instances.
Long-form thinking on debugging habits, observability, and the systems around the bug.
Adding Observability to a 500K-Line Monolith Without a Rewrite
Adding structured logging, distributed tracing, and metrics to a legacy monolith without a full rewrite. Real code examples and a war story from a 500K-line codebase.
Distributed Tracing: Following a Single Request Across Microservices
Distributed tracing lets you follow a request as it hops across services. I'll show you how trace context propagates, why sampling matters, and how tracing helped us debug a 5-second latency spike in production.
Structured Logging in JSON: Fields, Schemas, and Pitfalls from Production
A practical guide to designing JSON log schemas that are queryable, consistent, and actually useful in production — with field recommendations and a war story.
Sentry Error Monitoring: A Practical Setup Guide from a Production Outage
A step-by-step setup guide for Sentry error monitoring, covering source maps, release tracking, grouping rules, and alerting — with a real story of a production outage that taught us the hard way.
Reading Prometheus Alert Rules: A Practical Reference for Debugging Firing Alerts
Alert rules look straightforward until you're staring at a firing alert at 3 AM. This post covers the structure, common traps, and how to extract actionable intent from any rule.
Profiling SQL Queries: Finding and Fixing the Slow 5%
Profiling SQL queries is more than running EXPLAIN. This guide covers practical techniques to find the slowest queries, interpret execution plans, and fix them — with real examples from PostgreSQL and MySQL.