Server Side Asynchronous Programming Questions

Asynchronous and concurrent programming as applied to backend systems, including event loop models, thread pools, futures and promises, asynchronous I O, streaming, and reactive frameworks. Covers Node dot js event loop and streaming APIs, Java threading models and reactive libraries such as Project Reactor or RxJava, Python asyncio and multiprocessing versus multithreading trade offs, handling blocking operations, backpressure and flow control, and patterns to structure scalable non blocking servers. Candidates should demonstrate the ability to reason about throughput, latency, resource contention, and appropriate concurrency models for server workloads.

EasyTechnical

34 practiced

Explain the trade-offs between Python's multiprocessing and multithreading for server-side concurrency. Include the Global Interpreter Lock (GIL) impact, IPC costs, memory duplication, start-up latency, and scenarios when you would prefer one approach over the other for CPU-bound vs I/O-bound workloads.

EasyTechnical

23 practiced

Compare futures, promises, and callbacks across Java (CompletableFuture), JavaScript (Promise), and Python (concurrent.futures.Future / asyncio.Future / Task). For each platform, show typical APIs for chaining asynchronous operations, handling exceptions, and cancelling or timing out a running operation. Focus on server-side patterns and where cancellation semantics differ.

EasyTechnical

16 practiced

Implement an asynchronous exponential backoff with full jitter algorithm in Node.js. Provide an async function backoff(attempt, baseMs, capMs) that returns a Promise resolving after a randomized delay. Include example outputs for attempt values 1..5 and explain why jitter reduces thundering-herd problems compared to fixed backoff.

HardTechnical

23 practiced

Implement a simple reactive pull-based iterator in Java that supports backpressure: define a Publisher interface with subscribe(Subscriber) where Subscriber can request(n) items and Publisher emits only when requested. Implement thread-safety, support cancellation, and avoid busy-waiting. Do not use existing Reactive Streams libraries; show how you handle concurrent requests and cancellations.

MediumTechnical

31 practiced

Implement a graceful shutdown pattern for an asyncio-based HTTP server in Python: stop accepting new connections, allow in-flight requests to complete with a configurable timeout, cancel long-running background tasks, flush metrics, and then exit. Provide function outlines for signal handling and describe race conditions to watch for.

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