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.
17 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.
NumPy Broadcasting Shape Mismatch: A Field Guide to Silent Failures and Runtime Errors
Diagnose and fix NumPy broadcasting shape mismatches with concrete steps, error patterns, and a real incident walkthrough.
SQLAlchemy N+1 Queries: Diagnosing Lazy Loading Performance Disasters
How to detect, diagnose, and fix the N+1 query problem in SQLAlchemy caused by lazy loading. Includes concrete commands, SQLAlchemy event hooks, and realistic war stories.
Pandas dtype Unexpected Conversion: A Debugging Guide
When pandas silently changes dtypes from int to float, object to category, or datetime to object, debugging requires understanding pandas' internal type inference and nullable integer arrays. This guide covers real-world causes and fixes.
Debugging Python Datetime Timezone-Awareness and Offset Errors
A concise guide to diagnosing and fixing Python datetime offset and timezone-awareness bugs, with real-world examples and concrete commands.
Celery Beat Periodic Task Not Running: A Field Guide
A production-tested guide to diagnosing why your Celery Beat periodic tasks silently fail to execute, covering scheduler locks, timezone mismatches, and worker routing.
Python Virtual Environment Package Not Found: Debugging Guide
A practical guide to debugging 'module not found' errors inside Python virtual environments, covering PATH issues, activation traps, and pip installation nuances.
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.