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.
Debugging Production Issues Without a Debugger: Approaches That Work
Attaching an interactive debugger in production is usually impossible. Here’s how I gather signal, reproduce issues, and restore service using other techniques.
Writing Bug Reports That Developers Appreciate
A good bug report is more than a template. Learn which details actually move the needle, and which common 'best practices' waste developer time.
Assert Statements: Where They Help and Where They Hurt
Assert statements are a double-edged sword. Used correctly, they catch bugs early and document invariants. Used carelessly, they can mask failures and create security holes. Here's how to wield them effectively.
Defensive Logging: Patterns for Surviving Production Data Rot
Most logging advice stops at 'log more'. Here's how to log defensively—handling nulls, encoding, PII, and context propagation before they rot your observability pipeline.
Debuggers vs Console.log: Why I Stopped Using Print Statements for Debugging
Print statements are the duct tape of debugging. They work for trivial issues, but for race conditions, async flows, or deep call stacks, a debugger saves hours. Here's what I learned after years of using both.
Treating Bugs as Hypotheses: How the Scientific Method Fixes Debugging
Frustrated by flailing through logs? The scientific method turns debugging into a reproducible process. Here's how to formulate hypotheses, design experiments, and isolate root causes with confidence.