Concurrency

EF Core’s default optimistic concurrency model is a great starting point, but it’s not a silver bullet. When write contention heats up, its limitations can lead to performance bottlenecks and data integrity challenges. Understanding the trade-offs between optimistic and pessimistic concurrency is crucial for building robust, scalable applications. This article explores the conceptual costs and benefits of each strategy, helping you decide when to stick with the default and when to reach for explicit locking. ...

TL;DR: A deadlock happens when threads block each other, waiting for resources that never become available. Most deadlocks in C# are caused by inconsistent lock ordering or mixing sync and async code. Recognize deadlocks by symptoms like app hangs, high thread count, or timeout exceptions. Prevent deadlocks by always acquiring locks in a consistent order, minimizing lock duration, and using lock timeouts. Prefer higher-level synchronization tools like SemaphoreSlim or concurrent collections to reduce risk. In async code, avoid blocking calls like .Wait() or .Result - use await all the way. Use debugging tools and thread dumps to detect and analyze deadlocks in production. Design your multithreaded code with prevention in mind; fixing deadlocks after deployment is much harder. A deadlock is one of the hardest bugs to solve in a multithreaded C# application. It doesn’t cause a crash or an obvious exception; it just brings your application to a silent, grinding halt. If you’ve ever seen a service become completely unresponsive under load for no apparent reason, a deadlock might be the culprit. ...