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.
Python UnicodeEncodeError / UnicodeDecodeError: A Field Guide
Diagnose and fix Python Unicode encoding/decoding errors in production. Covers common causes, quick checks, and real-world fixes.
Python Generator Already Exhausted: What You're Actually Seeing
A direct engineering guide to diagnosing, fixing, and preventing the 'StopIteration' or silent empty-iteration caused by exhausted Python generators.
Pydantic V2 Migration Breaking Changes Debugging Guide
A practical debug guide for breaking changes when migrating from Pydantic V1 to V2, covering common errors and fixes.
Debugging Python boto3 AWS API Errors: A Field Guide
A practical guide to diagnosing and fixing boto3 API errors in Python, covering credential issues, throttling, and service-specific failures.
Debugging redis-py Connection Refused Errors
A step-by-step guide to debugging 'Connection refused' errors in redis-py, covering network checks, Redis config, and Python client troubleshooting.
gRPC Client-Server Error in Python: Connection Refused and Deadline Exceeded
A practical guide to debugging connection refused, deadline exceeded, and other communication errors in Python gRPC services.
Long-form thinking on debugging habits, observability, and the systems around the bug.
Debugging Production Issues Without a Debugger: Approaches That Work
Attaching an interactive debugger in production is usually impossible. Here’s how I gather signal, reproduce issues, and restore service using other techniques.
Writing Bug Reports That Developers Appreciate
A good bug report is more than a template. Learn which details actually move the needle, and which common 'best practices' waste developer time.
Assert Statements: Where They Help and Where They Hurt
Assert statements are a double-edged sword. Used correctly, they catch bugs early and document invariants. Used carelessly, they can mask failures and create security holes. Here's how to wield them effectively.
Defensive Logging: Patterns for Surviving Production Data Rot
Most logging advice stops at 'log more'. Here's how to log defensively—handling nulls, encoding, PII, and context propagation before they rot your observability pipeline.
Debuggers vs Console.log: Why I Stopped Using Print Statements for Debugging
Print statements are the duct tape of debugging. They work for trivial issues, but for race conditions, async flows, or deep call stacks, a debugger saves hours. Here's what I learned after years of using both.
Treating Bugs as Hypotheses: How the Scientific Method Fixes Debugging
Frustrated by flailing through logs? The scientific method turns debugging into a reproducible process. Here's how to formulate hypotheses, design experiments, and isolate root causes with confidence.