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.
How to Reproduce a Flaky Test: From CI Logs to Reliable Failure
A practical guide to turning intermittent test failures into reliably reproducible bugs, with techniques ranging from loop testing to thread sanitizers.
Property-Based Testing: Finding the Off-by-One That Lived in Production for 18 Months
A concrete story of how switching from example-based tests to property-based tests caught a timing bug that had survived code review, QA, and 18 months of production traffic.
How We Reduced End-to-End Test Flakiness by 80% with Deterministic Seeding
After months of chasing intermittent failures in our CI pipeline, we implemented a three-part strategy — deterministic seeding, isolated state per test, and a structured retry budget — that cut flaky end-to-end test failures by 80%.
Snapshot Testing: The 5 Hidden Failure Modes That Will Break Your CI
Snapshot tests seem like a safety net, but they often hide real bugs, bloat diffs, and silently break your CI. Here are the five failure modes I've seen in production and how to fix them.
Testing Async Code: Avoiding Flakiness and False Positives in JavaScript
Async testing is full of traps: unhandled rejections, race conditions, and tests that pass when they shouldn't. Here's how to write reliable async tests in JavaScript.
Testing Error Handling Code Paths: A Practical Approach
Error handling code is often the least tested and most brittle. Here's how to cover those paths with fault injection, mocks, and chaos engineering.