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.
Python Memory Leak Profiling: Diagnosing Unbounded Growth in Production
A practical guide to identifying and fixing Python memory leaks using tracemalloc, objgraph, and heapy, with production-tested strategies.
Python logging not showing output: Why your log messages vanish
A practical guide to diagnosing silent loggers in Python, covering root logger, handler levels, propagation, and common misconfigurations that cause output to disappear.
Go pprof CPU & Memory Profiling: Real-World Debugging Tactics
A hands-on debugging guide for Go pprof CPU and memory profiling with real commands, root causes, and a war story.
Diagnosing and Fixing Java OutOfMemoryError: Java Heap Space
A practical guide to diagnosing Java heap OutOfMemoryError in production, covering non-obvious causes like GC overhead, native memory leaks, and permgen/metaspace issues.
Custom Metrics Not Appearing in AWS CloudWatch: A Debugging Guide
Diagnose why your custom CloudWatch metrics are not showing up. Covers common causes like namespace mismatch, timestamp issues, and IAM permissions.
HTTP Connection Timeout: Debugging Network Stalls and Misconfigured Timeouts
A practical guide to diagnosing HTTP connection timeouts caused by network latency, firewall drops, TCP backlog exhaustion, and misconfigured timeout stack.
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.