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.
Flaky tests in CI: how to debug and fix intermittent test failures
A test passes nine times out of ten but randomly fails in CI with no code changes. Flaky tests destroy trust in the test suite — here is how to find and fix them.
Stale cache key bug: how to debug cache key collisions
Your cache returns data belonging to a different user, tenant, or request. The cache key is not unique enough — it is missing a dimension.
Distributed lock not releasing: how to debug stuck locks
Your distributed lock is acquired but never released. The lock holder crashed, the TTL expired but the key lingers, or the unlock logic has a bug.
Idempotency key not preventing duplicate payment: how to debug it
Your payment API accepts an idempotency key but still processes the same charge twice. The key is not being checked, stored, or matched correctly.
Slow API response: how to debug latency issues
An API endpoint that used to return in 50ms now takes 3 seconds. Find the bottleneck before your users notice.
N+1 query slowing down your API: how to find and fix it
Your API makes one query to get a list, then one more query for every item in the list. That is the N+1 pattern — it turns 1 query into 101 and kills performance.
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.