Real Engineering Stories
Lessons from Production Systems
Learn from real-world production incidents, failures, scaling challenges, and architectural decisions. Story-driven, deeply technical documentation that teaches how real software systems behave in production—not theory or textbook examples.
Stories are ordered as a learning flow—from context and fundamentals to advanced distributed systems concepts.
The On-Call Fatigue That Led to a Critical Bug
A production incident where on-call fatigue caused an engineer to make a critical mistake during an incident response, making the outage worse. Learn about on-call practices, incident response, and team health.
The SSL Certificate That Expired at Midnight
A production outage caused by an expired SSL certificate that nobody noticed until users started reporting connection errors. Learn about certificate lifecycle management, automation, and why 'we'll remember to renew' is never a valid strategy.
The N+1 Query Problem That Slowed Down Our API
A production incident where an N+1 query problem in a user feed endpoint caused database load to spike, slowing down the entire API. Learn about N+1 queries, eager loading, and query optimization.
The Misconfigured Load Balancer That Created a Single Point of Failure
A production incident where a misconfigured load balancer sent all traffic to a single backend server, causing it to crash and take down the service. Learn about load balancer configuration, health checks, and redundancy.
The DNS Change That Pointed Production at Staging
A DNS configuration mistake during a migration pointed production traffic to the staging database, causing data corruption scares and a frantic 2-hour rollback. Learn about DNS propagation, change management, and environment isolation.
The Memory Leak That Caused Gradual Degradation
A production incident where a memory leak in notification processing code caused gradual memory increase over 21 days, eventually leading to pod OOM kills and service degradation. Learn about memory leak detection, bounded data structures, and monitoring memory trends.
The Cache Stampede That Took Down Our API
A production incident where an accidental cache flush caused a cache stampede, overwhelming the database connection pool and taking down the API. Learn about cache stampedes, connection pool exhaustion, and how to prevent them.
The Message Queue Lag That Overwhelmed Our Order Processing
A Kafka consumer fell behind during a flash sale, causing 6 hours of message lag. When the consumer caught up, it overwhelmed the database with a burst of writes. Learn about backpressure, consumer lag monitoring, and graceful degradation.
The Race Condition That Only Happened in Production
A production bug where a race condition in inventory management caused items to be oversold. The bug was impossible to reproduce in testing but happened frequently in production. Learn about race conditions, distributed locks, and debugging production-only bugs.
The Hot Partition That Overwhelmed Our Database
A production incident where a hot partition in a sharded database caused one shard to handle 90% of traffic, overwhelming it and causing service degradation. Learn about database sharding, partition keys, and load balancing.
The Circuit Breaker That Didn't Break
A production incident where a misconfigured circuit breaker allowed cascading failures to propagate, taking down multiple services. Learn about circuit breaker patterns, failure isolation, and resilience.
The Database Failover That Didn't Fail Over
When the primary database crashed, the automatic failover to the replica failed—the replica had drifted out of sync and wasn't actually ready. Learn about replication lag, failover testing, and why HA systems need constant validation.
The Deadlock That Froze Our Payment System
A database deadlock in payment processing caused 200 transactions to hang for 8 minutes during peak checkout. Users saw 'payment processing' indefinitely. Learn about deadlocks, lock ordering, transaction design, and debugging production concurrency issues.
The Monolith to Microservices Migration That Almost Failed
A production incident during a monolith to microservices migration where service dependencies and data consistency issues caused cascading failures. Learn about migration strategies, service boundaries, and data consistency in distributed systems.
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