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.
Documenting Bugs: A Postmortem-Driven Approach That Cut Recurrence by 60%
Most bug write-ups are useless. Here's a structured, postmortem-driven approach that reduced bug recurrence by 60% in our team — with templates and a real incident walkthrough.
Debugging Inside Docker Containers: Tools, Techniques, and a War Story
Practical techniques for debugging inside Docker containers: exec, nsenter, strace, and a real incident that made me rethink debug images.
kubectl logs: Debugging Pods with Logs, Timestamps, and Previous Instances
Beyond `kubectl logs pod-name` — using timestamps, previous instances, and multi-container patterns to diagnose real failures.
Debugging Serverless Functions Locally: A Practical Approach
Local debugging of serverless functions requires different tools and mindset than traditional apps. Here's how I approach it with real examples.
Debugging Terraform and CloudFormation Errors: A Field Guide to the 3 AM Page
Infrastructure-as-code errors are inevitable. Here's how to systematically debug Terraform and CloudFormation failures without losing your mind.
Debugging as Hypothesis Testing: A Mental Model for Systematic Root Cause Analysis
Most debugging is frantic guessing dressed up as experience. Here's a mental model that treats debugging as a scientific process — form hypotheses, design experiments, and isolate root causes systematically.