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.
18 playbooks · 509 guides · 96 articles · 13 linked practice labs ·skip to practice
Fast pattern recognition for the production failures engineers see most often.
7 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.
Background job stuck: how to debug jobs that never complete
A background job enters the queue, a worker picks it up, and then nothing. The job never completes, never fails, and never retries. It is stuck in limbo.
Race condition in payment flow: how to debug concurrent payment issues
Two requests hit the payment endpoint at the same time. Both check the balance, both see enough funds, and both deduct. The user is charged twice.
Kafka Consumer Lag Growing: Why Offsets Stall and How to Fix It
A practical guide to diagnosing and resolving Kafka consumer lag growth, covering configuration pitfalls, broker throttling, and rebalance storms.
Kafka Consumer Group Rebalance Storm Debugging
A practical guide to diagnosing and fixing Kafka consumer group rebalance storms—when frequent rebalances cause processing stalls and lag spikes.
RabbitMQ Messages Stuck Unacked: A Production Debugging Guide
A production-proven guide to diagnosing why RabbitMQ messages pile up as unacknowledged, from consumer stalls to prefetch traps.
Debugging SQS Messages Going to DLQ: Root Causes and Fixes
Troubleshoot why SQS messages are routed to dead-letter queues. Covers redrive policy misconfig, consumer timeouts, payload issues, and IAM pitfalls with concrete debugging steps.
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.
Spacemail Is Down: What the August 2026 Outage Teaches About Provider Failures
A concise status snapshot of the current Spacemail incident, followed by a practical engineering guide to provider-wide outages, regional failover, degraded modes, and safe recovery.