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

19 practiced

Explain how a thread pool works in server-side Java. Describe the behavioral differences between Executors.newCachedThreadPool, newFixedThreadPool, and newScheduledThreadPool. Given an I/O-bound web service and a CPU-bound image processing service, how would you choose pool sizes and why? Discuss queue choices and rejection policies for overload scenarios.

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.

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.

HardTechnical

22 practiced

A production reactive pipeline built with Reactor reports intermittent high end-to-end latency spikes. Describe your investigative plan: what metrics, logs and distributed traces to collect, where to add instrumentation, how to determine whether backpressure propagation or a slow downstream service is the cause, and what emergency mitigations you might apply to stabilize latency while investigating.

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.

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