Architecture and Technical Trade Offs Questions

Centers on system and solution design decisions and the trade offs inherent in architecture choices. Candidates should be able to identify alternatives, clarify constraints such as scale cost and team capability, and articulate trade offs like consistency versus availability, latency versus throughput, simplicity versus extensibility, monolith versus microservices, synchronous versus asynchronous patterns, database selection, caching strategies, and operational complexity. This topic covers methods for quantifying or qualitatively evaluating impacts, prototyping and measuring performance, planning incremental migrations, documenting decisions, and proposing mitigation and monitoring plans to manage risk and maintainability.

EasyTechnical

33 practiced

Metrics to evaluate latency vs throughput trade-offs: As a Sales Engineer preparing a benchmark, list the eight most useful metrics you would collect during load testing to help quantify the trade-off and briefly explain why each one matters for business and engineering stakeholders.

HardTechnical

32 practiced

Performance diagnosis demo: A customer claims our product becomes CPU-bound under heavy load. Design an instrumentation and experiment plan to prove whether the bottleneck is CPU, network, or I/O. Specify which metrics to collect, minimal code or configuration changes to isolate the issue, and how you'd present the evidence to the customer.

MediumTechnical

28 practiced

Resilience patterns: Explain to a technical buyer how circuit breakers, retries with exponential backoff, and bulkheads help maintain system availability. For each pattern include one scenario where misapplying it could worsen system behavior and how you would tune or guard against that.

HardTechnical

37 practiced

Batch vs streaming for analytics: A large retailer needs near real-time personalization based on user events at 100k events/sec. Compare a batch micro-batch architecture versus a streaming architecture. For each option discuss latency, operational complexity, cost, correctness guarantees, and outline an incremental rollout plan that reduces customer risk.

HardTechnical

38 practiced

Serverless vs containerized services: You're presenting options to a CTO about running customer workloads using serverless functions (e.g., AWS Lambda) versus containers on managed Kubernetes. Compare cold-start behavior, scaling characteristics, operational complexity, cost for bursty vs steady workloads, vendor lock-in, and propose a measurable decision framework the CTO can use.

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