Advanced Real World Problem Solving Questions

Evaluate the candidates ability to solve complex multi layered technical and design problems by making reasonable assumptions, articulating trade offs, and handling edge cases. Candidates should show how to decompose problems that span networking caching persistence and performance optimization, select architectures and algorithms with explicit trade off analysis such as speed versus simplicity and functionality versus performance, and consider failure modes including network failures device limitations and concurrent access patterns. Strong responses include clear assumption statements, alternative approaches, complexity and cost considerations, testing and validation strategies, and plans to monitor and mitigate operational risks.

EasySystem Design

0 practiced

Design a simple REST API for fetching pre-aggregated metrics for dashboards with a freshness constraint of up to 1 minute and expected load of 1,000 RPS. Describe endpoints, caching strategy, TTLs, and how you would support queries for multiple time windows (e.g., last 1m, 1h, 24h). State assumptions about metric precomputation frequency.

EasyTechnical

0 practiced

Describe backpressure in distributed systems and give three mechanisms a data pipeline can use to apply backpressure to upstream producers: buffering with bounded queues, explicit signaling (e.g., HTTP 429), and flow-control protocols. For each mechanism describe failure modes and how you would protect memory and CPU during sustained overload.

HardTechnical

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Provide a capacity planning and cost-optimization plan for a distributed data service with daily traffic spikes (10x baseline). Include autoscaling policies, warm pools, spot vs on-demand instances, pre-warming caches, and graceful degradation strategies to meet SLOs while reducing cost.

MediumTechnical

0 practiced

Compare gRPC and REST for internal data services that require streaming responses and low-latency RPCs. Discuss performance, developer productivity, backward/forward compatibility, observability, and operational concerns like proxies and load-balancers.

EasyTechnical

0 practiced

For monitoring a distributed ETL service, explain the distinct roles of logs, metrics, and traces. Provide concrete examples of what each should capture for an ingestion job that processes per-file transforms (e.g., file received, parsing errors, duration, per-record failures) and how you would use them to investigate a spike in error rate.

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