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Capacity Planning and Forecasting Questions

Covers forecasting demand and planning infrastructure and platform capacity to meet expected business needs reliably and cost effectively. Candidates should be able to analyze historical usage and growth trends, build and validate capacity models, define capacity metrics and thresholds, estimate headroom and safety margins, and translate business growth scenarios into procurement or cloud provisioning plans and timelines. Includes storage and compute lifecycle planning such as archiving and retention strategies, upgrade and rollout planning to avoid disruption, and trade offs between overprovisioning and right sizing. Also addresses design for scale and redundancy, autoscaling and elasticity patterns, load balancing and failover planning, capacity testing and stress testing, monitoring and alerting for capacity signals, and techniques to measure and improve forecast accuracy. Finally it covers operational governance and decision making including cross team resource allocation, capacity reviews, cost optimization and budgeting, runbooks and change control, and alignment of capacity plans with service level objectives and business projections.

EasyTechnical
0 practiced
Given baseline storage of 12 TB and current observed storage of 15.6 TB six months later, compute the compound monthly growth rate and project storage in 12 months using simple exponential growth. Show the formula and discuss limitations of exponential projections for capacity planning.
MediumSystem Design
0 practiced
Design a cost-optimized storage tiering solution for event data across cloud object storage (e.g., S3: Standard/IA/Glacier). Include lifecycle rules, estimated cost tradeoffs, retrieval SLA for archives, and how to preserve efficient queryability for recent data.
MediumTechnical
0 practiced
How would you align the technical capacity plan with product roadmaps and business forecasts? Describe the data inputs you need (feature releases, marketing campaigns), cadence for updates, risk buffers, and how you would manage conflicting priorities across product teams.
MediumTechnical
0 practiced
Design a monitoring dashboard for capacity signals of a streaming ingestion system. Include key resource and business metrics, percentile latencies, queue/backpressure indicators, capacity headroom, and example alert thresholds. Explain how each metric maps to operational action.
HardTechnical
0 practiced
Describe a capacity governance framework for a large organization. Include allocation policies, quota enforcement, chargeback/showback mechanisms, exception handling, capacity review boards, and automated enforcement via IaC and policy-as-code (e.g., OPA).

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