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.
6 playbooks in Distributed Systems
Debugging Cache Stampedes
How to recognize and contain request spikes when cached data expires.
Debugging Stale Locks
Stale locks turn a previous failure into a new outage.
Debugging Tenant Cache Bugs
Tenant cache bugs are both correctness and security incidents.
Debugging Distributed Locks
A checklist for stale locks, duplicate workers, TTL drift, and clock-skew ownership bugs.
Debugging Queue Consumer Failures
How to debug missing retries, duplicate workers, and failed jobs that vanish from queues.
Debugging Performance Backpressure
How to diagnose resource exhaustion in streams, queues, and hot paths.
Structured investigations for the failure modes engineers meet in real systems.
Retry logic creating duplicate requests: how to debug it
Your retry logic fires a second request before the first one finishes. The server processes both. Now you have two charges, two emails, or two orders.
Webhook fires twice: how to debug duplicate webhook deliveries
Your webhook endpoint receives the same event twice. The provider retried because your endpoint did not acknowledge fast enough, or your handler is not idempotent.
Queue consumer not processing messages: how to debug it
Messages pile up in the queue but your consumer does nothing. The consumer might be crashed, stuck, or silently discarding messages.
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.
Duplicate emails sent by retry bug: how to debug it
Your email service retries a failed send, but the first send actually succeeded. Users get two, three, or ten copies of the same email.
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.
Long-form thinking on debugging habits, observability, and the systems around the bug.
When caches lie: debugging stale data in distributed systems
Cache invalidation is often cited as one of the two hard problems in CS, but the daily reality is subtler: partial staleness, clock drift, and silent evictions. This post walks through real debugging techniques for stale data in Redis, Memcached, and CDN layers.
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.
Timeouts Every Engineer Gets Wrong (and How to Fix Them)
Most timeout bugs aren't logic errors — they're configuration failures. Here's how to stop treating timeouts as magic numbers and start engineering them deliberately.
Backpressure in Streaming Systems: When Your Pipeline Fights Back
Backpressure is the system's way of saying 'slow down.' Ignore it and you get OOM crashes, silent data loss, or cascading failures. Here's how to design for it.