Async Programming & Concurrency

Master async/await patterns, avoid common pitfalls, and build highly concurrent .NET applications that scale efficiently.

55 min•By Priygop Team•Last updated: Feb 2026

Async/Await Best Practices

Always use async all the way: Never use .Result or .Wait() — it can cause deadlocks in ASP.NET Core and blocks thread pool threads
Use ConfigureAwait(false) in library code: Avoids capturing the synchronization context — library code shouldn't assume a specific context
Prefer ValueTask for hot paths: When a method often completes synchronously (cache hits), ValueTask avoids Task allocation overhead
Use CancellationToken everywhere: Pass CancellationToken through async chains — allows graceful cancellation of long-running operations
Avoid async void: Only use for event handlers. Async void methods can't be awaited, exceptions crash the process. Always return Task or ValueTask
Use Task.WhenAll for parallel operations: await Task.WhenAll(task1, task2, task3) runs concurrently — much faster than sequential await
Limit concurrency: Use SemaphoreSlim or Channel<T> to limit concurrent operations — prevent overwhelming databases or external APIs

Producer-Consumer: Use Channel<T> for high-performance producer-consumer — bounded channels provide backpressure when consumer can't keep up
Parallel Processing: Parallel.ForEachAsync for CPU-bound work across collections — automatically manages thread count based on available cores
Background Services: IHostedService and BackgroundService for long-running tasks — queue processing, scheduled jobs, health monitoring
Actor Pattern: Use frameworks like Akka.NET or Microsoft Orleans for actor-based concurrency — each actor processes messages sequentially, no shared state
Immutable Collections: Use ImmutableList<T>, ImmutableDictionary<T> for thread-safe data sharing — no locking needed when data doesn't change
Lock-Free Programming: Use Interlocked operations and ConcurrentDictionary for high-contention scenarios — avoids lock overhead