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.
Flutter setState Not Rebuilding Widget – Debugging Stale UI
Diagnose why setState doesn't trigger a rebuild in Flutter: missing context, wrong state class, or identity issues. Includes concrete commands and fixes.
Flutter FutureBuilder Rebuilds Infinitely: The Real Causes and Fixes
A practical guide to stopping FutureBuilder from rebuilding endlessly in Flutter, with root causes, diagnosis steps, and real war stories.
React Native FlatList Performance: Why Your List Jitters at 200+ Items
A hands-on guide to diagnosing and fixing FlatList jank, dropped frames, and blank cells in React Native apps, with real profiling commands.
PyTorch CUDA Out of Memory: Diagnosis and Recovery
A practical guide to diagnosing and fixing CUDA out-of-memory errors in PyTorch, covering memory fragmentation, gradient accumulation, and monitoring with nvidia-smi.
Debugging PyTorch Tensor Shape Mismatch Runtime Errors
A practical guide to diagnosing and resolving shape mismatch errors in PyTorch, covering common causes, debugging commands, and fixes.
PyTorch Gradient Explosion Producing NaN Loss
Diagnose and fix NaN losses caused by gradient explosion in PyTorch models. Covers gradient clipping, weight initialization, and data normalization.
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.