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 Read Error Messages: A Debugging Protocol
Most engineers skim error messages and miss the signal. Here's a repeatable protocol for extracting maximum information from stack traces, log lines, and crash dumps — with a real incident walkthrough.
When to Escalate a Bug: A Decision Framework for Junior and Mid-Level Engineers
A practical framework for junior and mid-level engineers to decide when to escalate a bug, with real-world examples and criteria beyond time spent.
Debugging vs. Firefighting: Why Treating Production Incidents as Debugging Sessions Fails
When production goes down, your brain wants to debug. That instinct costs you hours. Here's why firefighting requires a fundamentally different approach, and the specific process I use to switch modes.
Writing an Incident Runbook That Actually Gets Used in Production
A runbook isn't a document—it's a tool. Here's how to write one that reduces MTTR and doesn't embarrass you during the next PagerDuty alert.
Debugging a production incident with your boss on Slack: staying rational when everything is on fire
A personal account of debugging a cascading Redis failure while the VP of Engineering watched, and the mental models that kept the fix from turning into a rollback.
Reading Distributed Traces to Find Latency: A Field Guide
Tracing tools generate a firehose of data. Here's how to filter the signal from the noise and actually find the root cause of high latency.