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.
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.
Writing Bug Reports That Developers Appreciate
A good bug report is more than a template. Learn which details actually move the needle, and which common 'best practices' waste developer time.
Assert Statements: Where They Help and Where They Hurt
Assert statements are a double-edged sword. Used correctly, they catch bugs early and document invariants. Used carelessly, they can mask failures and create security holes. Here's how to wield them effectively.
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.
Debuggers vs Console.log: Why I Stopped Using Print Statements for Debugging
Print statements are the duct tape of debugging. They work for trivial issues, but for race conditions, async flows, or deep call stacks, a debugger saves hours. Here's what I learned after years of using both.
Treating Bugs as Hypotheses: How the Scientific Method Fixes Debugging
Frustrated by flailing through logs? The scientific method turns debugging into a reproducible process. Here's how to formulate hypotheses, design experiments, and isolate root causes with confidence.