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.

MediumTechnical

0 practiced

You run a real-time metrics stream that normally has ~1K consumers but suddenly spikes to 50K; producers continue sending but downstream consumers are slow. Describe immediate mitigations to avoid exhaustion and data loss, and long-term architecture changes (fanout, tiered caching, backpressure-aware proxies) to handle such consumer spikes while preserving data integrity.

MediumTechnical

0 practiced

Explain the concept of backpressure in streaming and reactive systems. Provide concrete examples of how backpressure is implemented in Node.js streams, Reactive Streams (Project Reactor/RxJava), and RxJS. When should you choose automatic backpressure (built into framework) versus manual flow-control strategies in a backend pipeline?

HardTechnical

0 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

0 practiced

Describe approaches to unit and integration testing for asynchronous server code across Node.js (async/await), Python asyncio, and Java CompletableFuture/Reactive. Include strategies to make tests deterministic, mocking timers and I/O, simulating backpressure, and reducing flakiness due to concurrency. Provide example test patterns for asserting ordering and timing behavior.

MediumTechnical

0 practiced

You receive urgent alerts: a Node.js API's 95th percentile latency spiked and many requests are timing out. Process CPU is low, but event-loop lag (measured by event-loop-delay metric) is high. Describe a step-by-step incident-response plan: what metrics and traces you inspect, quick mitigations to restore service, and how to find the blocking code causing event-loop starvation.

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