Handling Problem Variations and Constraints Questions

This topic covers the ability to adapt an initial solution when interviewers introduce follow up questions, new constraints, alternative optimization goals, or larger input sizes. Candidates should quickly clarify the changed requirement, analyze how it affects correctness and complexity, and propose concrete modifications such as changing algorithms, selecting different data structures, adding caching, introducing parallelism, or using approximation and heuristics. They should articulate trade offs between time complexity, space usage, simplicity, and robustness, discuss edge case handling and testing strategies for the modified solution, and describe incremental steps and fallbacks if the primary approach becomes infeasible. Interviewers use this to assess adaptability, problem solving under evolving requirements, and clear explanation of design decisions.

EasyTechnical

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You proposed a single-region REST service backed by PostgreSQL. During a follow-up the client states: expected read traffic will increase 10× and 99th-percentile read latency must be <50ms. As a Solutions Architect, what clarifying questions would you ask and what immediate architecture changes would you consider to meet throughput and tail-latency targets?

HardTechnical

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A new regulation requires customer-managed keys (CMKs) and full audited read logs. Your managed DB currently uses provider-controlled keys. Describe concrete changes to support CMKs, envelope encryption, access controls, key rotation, backup handling, and the operational impact on latency and availability.

EasyTechnical

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Explain vertical scaling vs horizontal scaling in the context of cloud-hosted services. For each approach, list pros and cons with respect to cost, fault domains, operational complexity and downtime. Give an example scenario where vertical scaling is preferable and one where horizontal is preferable.

MediumSystem Design

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A synchronous OLTP database is being slowed by heavy analytic queries. Propose an architecture to isolate analytics from OLTP: options such as read-replicas, change-data-capture (CDC) to a data warehouse, or separate OLAP store. Discuss trade-offs in data freshness, cost and operational complexity.

MediumTechnical

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You introduced parallelism to a CPU-bound batch job with task dependencies. Describe how you'd model the task graph (DAG), partition work, schedule workers, handle synchronization and failures, and avoid common pitfalls like excessive synchronization or hot partitions.

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