FIFO Queues In .NET

FIFO Queues in .NET

• Definition: First-In, First-Out data structure where the earliest enqueued item is dequeued first.
• API Surface: Use Queue<T> for in-memory work, Channel<T> for async producers/consumers, and ConcurrentQueue<T> in multi-threaded scenarios.

var orders = new Queue<Order>();
orders.Enqueue(new Order("EURUSD", 1_000_000m));
orders.Enqueue(new Order("GBPUSD", 750_000m));

while (orders.TryDequeue(out var next))
{
    await _executionService.ExecuteAsync(next);
}

⚙️ Threading Tip: Prefer Channel<T> or System.Threading.Channels when you need async waiting rather than spin-checking a Queue<T>.

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Questions & Answers

Q: When should you use Queue<T> vs ConcurrentQueue<T>?

A: Use Queue<T> for single-threaded scenarios. Use ConcurrentQueue<T> when multiple threads enqueue/dequeue concurrently, but note it lacks blocking reads.

Q: Why choose Channel<T> over BlockingCollection<T>?

A: Channel<T> supports async producers/consumers, backpressure, and high performance without legacy BlockingCollection overhead. It integrates well with async/await.

Q: How do you implement backpressure with FIFO queues?

A: Use bounded Channel<T> so producers await when the queue is full, preventing memory blowups and throttling upstream systems.

Q: How do you ensure ordering when scaling consumers?

A: Single consumer preserves strict FIFO. If you scale out, partition by key (e.g., account ID) so each partition maintains order, or accept eventual ordering per partition only.

Q: How do you persist FIFO semantics across process restarts?

A: Use durable queues (RabbitMQ, Azure Service Bus) with FIFO support, or persist queue state in a database/outbox to resume processing after failure.

Q: What’s the cost of peeking?

A: Queue<T>.Peek() is O(1) and non-destructive. For channels, peeking isn’t supported; you’d need to buffer manually if you must inspect before processing.

Q: How do you avoid busy-wait loops with Queue<T>?

A: Use synchronization primitives (SemaphoreSlim, AutoResetEvent) or switch to Channel<T>/BlockingCollection<T> which provide blocking/async waits.

Q: How do FIFO queues interact with metrics?

A: Track enqueue/dequeue rates, queue length, and processing latency. Alert when queue length grows unexpectedly—indicates downstream slowness.

Q: How do you handle poison messages?

A: Implement retries with exponential backoff, move failures to a dead-letter queue, and avoid blocking the FIFO by skipping or quarantining bad entries.

Q: How do you throttle producers?

A: Combine bounded channels with SemaphoreSlim or token buckets. Producers await when the channel is full, smoothing load on downstream services.