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.
AWS DynamoDB Throttling: Provisioned Throughput Exceeded Debugging Guide
A hands-on guide to diagnosing and fixing DynamoDB throttling errors caused by exceeded provisioned throughput, with real-world tactics and a war story.
AWS Step Functions State Machine Failed: Debugging Execution Failures
A practical guide to diagnosing and fixing AWS Step Functions execution failures, covering common causes, quick diagnosis steps, and real-world debugging patterns.
Debugging AWS AppSync Resolver Mapping Errors
A practical guide to diagnosing and fixing VTL and JavaScript mapping errors in AWS AppSync resolvers, covering common pitfalls and production debugging techniques.
Debugging GCP Cloud SQL Connection Limit Exceeded
Diagnose and resolve 'too many connections' errors in GCP Cloud SQL with actionable steps, root causes, and a real-world incident.
Azure AD Authentication Token Error — A Practical Debugging Guide
A hands-on guide to diagnosing and fixing Azure AD token errors like AADSTS700016, 500208, and 65001. Covers common causes, quick diagnosis steps, and real-world fix patterns.
Azure Functions Cold Start: Diagnosing and Fixing Slow First Requests
A targeted guide for identifying and eliminating cold start latency in Azure Functions, covering platform settings, code patterns, and runtime diagnostics.
Long-form thinking on debugging habits, observability, and the systems around the bug.
Tracking Down a 200 MB Leak with Python Memory Profilers
A production API was silently leaking 200 MB of RAM every hour. Here's how memory profilers found the culprit—a forgotten NumPy array reference—and how you can apply the same techniques.
Reading CPU Flame Graphs: What the Hot Colors Actually Tell You
Flame graphs are everywhere, but most engineers read them wrong. Here's how to identify real bottlenecks, avoid common misinterpretations, and turn profile data into actionable fixes.
When Logs Lie: The Gaps Between What You Log and What Actually Happened
Logs are the first thing we reach for during an incident. But they can be misleading, incomplete, or outright wrong. Here's when to trust them and when not to.
Adding Observability to a 500K-Line Monolith Without a Rewrite
Adding structured logging, distributed tracing, and metrics to a legacy monolith without a full rewrite. Real code examples and a war story from a 500K-line codebase.
Distributed Tracing: Following a Single Request Across Microservices
Distributed tracing lets you follow a request as it hops across services. I'll show you how trace context propagates, why sampling matters, and how tracing helped us debug a 5-second latency spike in production.
Structured Logging in JSON: Fields, Schemas, and Pitfalls from Production
A practical guide to designing JSON log schemas that are queryable, consistent, and actually useful in production — with field recommendations and a war story.