InterviewStack.io LogoInterviewStack.io

Cloud Cost Optimization and Financial Operations Questions

Covers strategies and organizational practices for minimizing and managing cloud and infrastructure spend while balancing performance, reliability, and business priorities. Candidates should understand cloud cost drivers such as compute, storage, data transfer, and managed services; pricing models including on demand pricing, reserved capacity commitments, savings plans, and interruptible or spot offerings; and engineering techniques that reduce spend such as rightsizing, autoscaling, storage tiering, caching, and workload placement. This topic also includes financial operations practices for continuous cost management and governance: resource tagging and cost allocation, budgeting and forecasting, chargeback and showback models, anomaly detection and alerting, cost reporting and dashboards, and processes to gate changes that affect spend. Interviewees should be able to estimate recurring costs and total cost of ownership, identify and quantify optimization opportunities, weigh trade offs between cost and business objectives, and describe tools and metrics used to monitor and communicate cost to stakeholders.

MediumTechnical
0 practiced
Given a billing_events table (columns: event_date DATE, service STRING, amount_usd FLOAT), write a SQL query to flag any service that has spending for the current week greater than 150% of its 3-week moving average. Use standard SQL and be explicit about window functions or aggregates.
MediumTechnical
0 practiced
Your team runs many Spark ETL jobs on AWS EMR. Describe medium-term optimization techniques specific to EMR and Spark that reduce cost while preserving throughput: instance fleet choices, spot usage strategies, instance sizing, EMR auto-scaling rules, caching, and file formats. Give the most impactful levers and potential pitfalls.
MediumSystem Design
0 practiced
Design a cost-conscious streaming ingestion pipeline that must accept 100k events/sec, guarantee <1s end-to-end latency for 95% of events, retain raw events for 30 days, and keep monthly infrastructure cost under a specified budget. Describe architecture choices (e.g., managed streaming vs self-hosted Kafka), storage format, batching/windowing, and autoscaling strategy with cost trade-offs.
MediumTechnical
0 practiced
You manage a 50 TB data lake with most queries touching only recent partitions. Propose a lifecycle policy that moves older data to cheaper tiers, describe how you would compute the TCO impact (including retrieval costs), and explain how you would validate that analytics queries still meet SLA after the move.
MediumTechnical
0 practiced
Write a Python function (or clear pseudocode) that estimates the monthly cost of a recurring Spark job given these inputs: number_of_executors, executor_vcpu, executor_memory_gb, runtime_minutes_per_job, jobs_per_day, price_per_vcpu_hour, storage_gb_month, storage_price_per_gb_month, percent_spot_used. Include handling for spot discount and show the formula used.

Unlock Full Question Bank

Get access to hundreds of Cloud Cost Optimization and Financial Operations interview questions and detailed answers.

Sign in to Continue

Join thousands of developers preparing for their dream job.