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 Read Error Messages: A Debugging Protocol
Most engineers skim error messages and miss the signal. Here's a repeatable protocol for extracting maximum information from stack traces, log lines, and crash dumps — with a real incident walkthrough.
When to Escalate a Bug: A Decision Framework for Junior and Mid-Level Engineers
A practical framework for junior and mid-level engineers to decide when to escalate a bug, with real-world examples and criteria beyond time spent.
Debugging vs. Firefighting: Why Treating Production Incidents as Debugging Sessions Fails
When production goes down, your brain wants to debug. That instinct costs you hours. Here's why firefighting requires a fundamentally different approach, and the specific process I use to switch modes.
Writing an Incident Runbook That Actually Gets Used in Production
A runbook isn't a document—it's a tool. Here's how to write one that reduces MTTR and doesn't embarrass you during the next PagerDuty alert.
Debugging a production incident with your boss on Slack: staying rational when everything is on fire
A personal account of debugging a cascading Redis failure while the VP of Engineering watched, and the mental models that kept the fix from turning into a rollback.
Reading Distributed Traces to Find Latency: A Field Guide
Tracing tools generate a firehose of data. Here's how to filter the signal from the noise and actually find the root cause of high latency.