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.
18 playbooks · 509 guides · 96 articles · 13 linked practice labs ·skip to practice
Fast pattern recognition for the production failures engineers see most often.
18 playbooks
Debugging Env Var Issues
A concise checklist for incidents where local works but CI, staging, or production changes behavior.
Debugging Cache Stampedes
How to recognize and contain request spikes when cached data expires.
Debugging CORS Origin Bugs
A practical way to inspect origin parsing, credentials, and header behavior.
Debugging Retry Bugs
Retry issues often hide the first failure and create duplicate work.
Debugging Timezone Bugs
Time bugs usually live at day boundaries, DST changes, and unit conversions.
Debugging Pagination Bugs
Pagination bugs hide in boundary math, cursor reuse, and new records arriving between pages.
Structured investigations for the failure modes engineers meet in real systems.
Jest Fake Timers Not Working: A Debugging Guide
A practical guide to debugging when Jest's fake timers (jest.useFakeTimers) don't behave as expected—covering async race conditions, timer scope, and common pitfalls.
Thread Pool Starvation Deadlock: How to Detect, Diagnose, and Fix It
Learn how to identify and resolve thread pool starvation deadlocks where waiting tasks block worker threads, causing cascading failures.
GC Thrashing Causes High CPU — How to Diagnose and Stop It
A practical guide to identifying and resolving garbage collection thrashing that spikes CPU usage in JVM and .NET applications.
Debugging Pandas Merge Producing Duplicate Rows
A targeted guide for diagnosing and fixing unexpected row explosions when merging DataFrames, covering key mismatches, duplicate keys, and index bleed.
Pandas SettingWithCopyWarning: How to Find and Fix the Real Source
A practical guide to eliminating SettingWithCopyWarning in pandas by understanding chain indexing, copy vs. view semantics, and using .loc and .copy() correctly.
RabbitMQ Connection Churn Spiking CPU: Debugging Guide
When clients rapidly open/close connections, RabbitMQ's Erlang VM burns CPU managing channel and process overhead. This guide covers the real causes, from client misconfigurations to rogue heartbeat timeouts.
Long-form thinking on debugging habits, observability, and the systems around the bug.
How to Read Error Messages: A Debugging Protocol
Most engineers skim error messages and miss the signal. Here's a repeatable protocol for extracting maximum information from stack traces, log lines, and crash dumps — with a real incident walkthrough.
When to Escalate a Bug: A Decision Framework for Junior and Mid-Level Engineers
A practical framework for junior and mid-level engineers to decide when to escalate a bug, with real-world examples and criteria beyond time spent.
Debugging vs. Firefighting: Why Treating Production Incidents as Debugging Sessions Fails
When production goes down, your brain wants to debug. That instinct costs you hours. Here's why firefighting requires a fundamentally different approach, and the specific process I use to switch modes.
Writing an Incident Runbook That Actually Gets Used in Production
A runbook isn't a document—it's a tool. Here's how to write one that reduces MTTR and doesn't embarrass you during the next PagerDuty alert.
Debugging a production incident with your boss on Slack: staying rational when everything is on fire
A personal account of debugging a cascading Redis failure while the VP of Engineering watched, and the mental models that kept the fix from turning into a rollback.
Reading Distributed Traces to Find Latency: A Field Guide
Tracing tools generate a firehose of data. Here's how to filter the signal from the noise and actually find the root cause of high latency.