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.
How to Reproduce a Flaky Test: From CI Logs to Reliable Failure
A practical guide to turning intermittent test failures into reliably reproducible bugs, with techniques ranging from loop testing to thread sanitizers.
Property-Based Testing: Finding the Off-by-One That Lived in Production for 18 Months
A concrete story of how switching from example-based tests to property-based tests caught a timing bug that had survived code review, QA, and 18 months of production traffic.
How We Reduced End-to-End Test Flakiness by 80% with Deterministic Seeding
After months of chasing intermittent failures in our CI pipeline, we implemented a three-part strategy — deterministic seeding, isolated state per test, and a structured retry budget — that cut flaky end-to-end test failures by 80%.
Snapshot Testing: The 5 Hidden Failure Modes That Will Break Your CI
Snapshot tests seem like a safety net, but they often hide real bugs, bloat diffs, and silently break your CI. Here are the five failure modes I've seen in production and how to fix them.
Testing Async Code: Avoiding Flakiness and False Positives in JavaScript
Async testing is full of traps: unhandled rejections, race conditions, and tests that pass when they shouldn't. Here's how to write reliable async tests in JavaScript.
Testing Error Handling Code Paths: A Practical Approach
Error handling code is often the least tested and most brittle. Here's how to cover those paths with fault injection, mocks, and chaos engineering.