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.
Stale lock bug: how locks that are never refreshed cause outages
A lock is acquired, the operation succeeds, but the lock is never released or refreshed. Other processes wait until the lock TTL expires, causing delays or outages.
Tenant cache leak: how to debug cross-tenant data exposure through caching
A user from Tenant A sees data from Tenant B because the cache key does not include the tenant identifier. The cache is leaking data across tenants.
Observability missing logs: how to debug gaps in logging and monitoring
A critical error happened in production but there are no logs for it. The log level is too high, logs are dropped under load, or the log pipeline has a silent failure.
Log says success but the user still fails: how to debug misleading logs
Your application logs 'Operation completed successfully' but the user sees an error or gets no result. The log is lying — it is logging intent, not outcome.
Background job stuck: how to debug jobs that never complete
A background job enters the queue, a worker picks it up, and then nothing. The job never completes, never fails, and never retries. It is stuck in limbo.
Race condition in payment flow: how to debug concurrent payment issues
Two requests hit the payment endpoint at the same time. Both check the balance, both see enough funds, and both deduct. The user is charged twice.
Long-form thinking on debugging habits, observability, and the systems around the bug.
The Art of the Minimal Reproducible Example: A Debugging Superpower
A minimal reproducible example (MRE) is more than just a snippet — it's a tool that isolates the bug, saves time, and gets you faster answers. Here's how to build one that works, with a real-world war story.
Retry Storms: When Retries Make a Cascading Failure Worse
Retries seem like a safety net, but in a distributed system under load they can turn a small hiccup into a full outage. Here's how retry storms form and what to do about them.
Caching Bugs Are the Worst: A Postmortem on Stale Data Disasters
A deep dive into the most insidious caching bugs, with real postmortems and practical patterns to avoid stale-data disasters.
Observability vs. Monitoring: Why Your On-Call Rotation Still Wakes You Up at 3 AM
Monitoring tells you something is broken. Observability lets you figure out why—without guessing, without SSH, without restarting the pod.
Debugging Flaky Tests for Good: A Systematic Approach to Root Cause Analysis
Flaky tests waste time and erode trust. Here's how to find and fix the actual root cause instead of just rerunning.
Idempotency Keys: The Safety Net Your Payment API Needs
How idempotency keys prevent double charges, lost refunds, and data corruption in payment APIs. With real-world examples and edge cases you haven't considered.