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.

HardSystem Design

46 practiced

Design an automated policy enforcement system using Infrastructure-as-Code (IaC) and CI that prevents new deployments from increasing monthly cloud spend above a team-specific budget. Include how you would detect potential budget violations during code review, block merges, and auto-remediate if an over-budget change reaches production.

MediumTechnical

53 practiced

Compare pruning, quantization, and distillation as model compression techniques for reducing inference cost. For each technique list expected compression range, recommended use-cases, and one operational challenge when applying it at scale.

HardSystem Design

38 practiced

Design a cost-optimized inference platform for a 70B-parameter LLM that must serve 1M requests/day with a 200ms P95 SLO and a target cost of under $0.50 per 1k requests. Discuss model serving strategy (sharding, tensor-slicing, quantization), caching, autoscaling, and hardware selection. Provide estimated trade-offs.

EasyTechnical

46 practiced

Given the following simplified schema, write a SQL query to compute monthly cost per active customer:

transactions(transaction_id, customer_id, service, cost_usd, occurred_at timestamp)

Requirements: compute total cost and cost per customer for month 2025-06, exclude zero-cost test transactions, and order by highest cost per customer. Use standard SQL.

MediumSystem Design

48 practiced

Design a multi-tier storage plan for a 5 PB ML dataset used for training and analytics. Requirements: keep last 90 days hot for training, older data accessible within 6 hours for retraining, cost target 50% lower than keeping all on SSD, and minimal operational overhead. List components, lifecycle policies, and expected trade-offs.

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