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.
Debugging LCP: Largest Contentful Paint Too Slow
A practical guide to diagnosing and fixing slow Largest Contentful Paint in real-world web applications, with specific commands, metrics, and war stories.
Debugging Cumulative Layout Shift (CLS): A Production Engineer's Guide
This guide provides concrete steps to diagnose and fix CLS issues in production, with real commands and specific tools.
JavaScript Long Task Blocking Main Thread: Diagnosis and Fixes
A practical guide to identifying and fixing JavaScript long tasks that block the browser's main thread, causing jank and poor user experience.
Debugging High Interaction to Next Paint (INP) Scores
A practical guide to diagnosing and fixing poor Interaction to Next Paint (INP) scores, covering event handler delays, rendering bottlenecks, and real-user monitoring.
Debugging JavaScript Garbage Collection Pauses That Kill Responsiveness
Learn how to identify and fix long GC pauses in Node.js and browser JavaScript using Chrome DevTools, Node --trace-gc, and heap snapshots.
OpenTelemetry Traces Not Appearing: Debugging Missing Spans in Production
A debugging guide for when OpenTelemetry traces are not appearing in your observability backend. Covers common and non-obvious causes like sampling misconfiguration, exporter timeouts, and context propagation failures.
Long-form thinking on debugging habits, observability, and the systems around the bug.
Why Your Production Logs Are Lying to You
Logs tell you what the code reported. They almost never tell you what actually happened. Here is the gap, and how to close it.
Debugging Production Issues Without a Debugger: Approaches That Work
Attaching an interactive debugger in production is usually impossible. Here’s how I gather signal, reproduce issues, and restore service using other techniques.
Defensive Logging: Patterns for Surviving Production Data Rot
Most logging advice stops at 'log more'. Here's how to log defensively—handling nulls, encoding, PII, and context propagation before they rot your observability pipeline.
Tracking Down a 200 MB Leak with Python Memory Profilers
A production API was silently leaking 200 MB of RAM every hour. Here's how memory profilers found the culprit—a forgotten NumPy array reference—and how you can apply the same techniques.
Reading CPU Flame Graphs: What the Hot Colors Actually Tell You
Flame graphs are everywhere, but most engineers read them wrong. Here's how to identify real bottlenecks, avoid common misinterpretations, and turn profile data into actionable fixes.
When Logs Lie: The Gaps Between What You Log and What Actually Happened
Logs are the first thing we reach for during an incident. But they can be misleading, incomplete, or outright wrong. Here's when to trust them and when not to.