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Cost Optimization at Scale Questions

Addresses cost conscious design and operational practices for systems operating at large scale and high volume. Candidates should discuss measuring and improving unit economics such as cost per request or cost per customer, multi tier storage strategies and lifecycle management, caching, batching and request consolidation to reduce resource use, data and model compression, optimizing network and input output patterns, and minimizing egress and transfer charges. Senior discussions include product level trade offs, prioritization of cost reductions versus feature velocity, instrumentation and observability for ongoing cost measurement, automation and runbook approaches to enforce cost controls, and organizational practices to continuously identify, quantify, and implement savings without compromising critical service level objectives. The topic emphasizes measurement, benchmarking, risk assessment, and communicating expected savings and operational impacts to stakeholders.

HardTechnical
0 practiced
Design a benchmarking framework to measure cost per 1000 requests for a given workload across multiple cloud providers. Describe test harness, reproducibility controls, load-profile generation, variance analysis, cost normalization factors, and how you would present the results to procurement and engineering stakeholders.
MediumTechnical
0 practiced
Explain the interplay between data retention policies and regulatory/compliance constraints. How would you design lifecycle policies that balance cost reduction with legal and audit requirements, and what approval and validation steps would you include in a production rollout?
EasyTechnical
0 practiced
List and compare common cloud pricing models (on-demand, reserved, committed-use, spot/preemptible, savings plans). For each, explain the trade-offs a Solutions Architect should communicate to customers during a sales process and an example workload where that model is ideal.
MediumSystem Design
0 practiced
Design a multi-region replication strategy for a read-heavy service that must keep read latency <100ms for 95% of global traffic and minimize cross-region egress charges. Provide options (active-active, active-passive, caching, geo-routing), their expected egress implications, and when each is appropriate.
MediumTechnical
0 practiced
You're preparing a cost estimate to migrate an on-prem Hadoop data warehouse to the cloud. Outline the approach you'd take as a Solutions Architect to estimate TCO: inventory, equivalent cloud services, storage/compute trade-offs, egress assumptions, conversion factors, and sensitivity analysis. Provide a list of required inputs from the customer.

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