Problem Solving and Structured Thinking Questions

Focuses on general problem solving strategies and structured thinking applicable to engineering, coding, and complex decision making. Core skills include clarifying the problem, breaking problems into subproblems, identifying patterns, selecting appropriate approaches and data structures, developing and testing incremental solutions, analyzing trade offs, reasoning about time and space complexity, handling edge cases, and communicating thought process clearly. Includes algorithmic patterns and design of systematic approaches to unfamiliar problems as well as frameworks for organizing thought under ambiguity.

MediumTechnical

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Design runbooks that support rapid incident mitigation while also capturing the rationale for decisions made during the incident. Provide a structured runbook template that includes checks, commands, decision trees, rollback steps, and post-incident actions. Explain how you'd keep runbooks up to date and discoverable for on-call engineers.

HardSystem Design

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Design an automated rollback system that triggers when canary deployments show regressions on key metrics (error rate increase, p95 latency increase). Specify which signals to monitor, how to perform canary analysis (baselines, statistical tests), how to trigger an automated rollback safely, and what safeguards prevent accidental rollbacks.

MediumTechnical

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Compare and evaluate caching strategies (LRU, LFU, TTL-based caches) for API response caching in a system where stale data is tolerated for 30 seconds but hit rate is critical. Propose a structured rubric to choose one strategy over another and how you'd benchmark the candidates in production-like conditions.

EasyTechnical

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You are given a high-level reliability objective: reduce p99 latency by 50% for a critical endpoint over the next quarter. Using structured thinking, break this high-level goal into measurable subproblems, concrete milestones, and sample tasks (monitoring, profiling, code changes, infra). Describe how you'd track progress and prioritize work.

HardTechnical

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Design and describe a concurrent LRU cache in Go that supports high concurrency and O(1) get/put operations. Provide the data structures you would use, show pseudocode for get and put, explain locking strategy or lock-free alternatives, and describe how you would test for race conditions and correctness.

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