Capacity Planning and Resource Optimization Questions

Covers forecasting, provisioning, and operating compute, memory, storage, and network resources efficiently to meet demand and service level objectives. Key skills include monitoring resource utilization metrics such as central processing unit usage, memory consumption, storage input and output and network throughput; analyzing historical trends and workload patterns to predict future demand; and planning capacity additions, safety margins, and buffer sizing. Candidates should understand vertical versus horizontal scaling, autoscaling policy design and cooldowns, right sizing instances or containers, workload placement and isolation, load balancing algorithms, and use of spot or preemptible capacity for interruptible workloads. Practical topics include storage planning and archival strategies, database memory tuning and buffer sizing, batching and off peak processing, model compression and inference optimization for machine learning workloads, alerts and dashboards, stress and validation testing of planned changes, and methods to measure that capacity decisions meet both performance and cost objectives.

EasyTechnical

0 practiced

Explain what spot/preemptible instances are and name three best-practice use-cases where they provide cost benefits without jeopardizing availability. For each use-case explain the interruption handling strategy you would recommend.

EasyTechnical

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Outline a basic 3-month capacity planning timeline for a new product launch expecting 1,000 concurrent users at launch. Describe the buffers (safety margins) you'd recommend, what validation activities you'd run pre-launch, and which stakeholders you would align with.

EasyTechnical

0 practiced

List common load-balancing algorithms (round-robin, least-connections, IP-hash/consistent-hash, weighted least-response-time). For each algorithm describe a workload pattern where it performs well and one pattern where it may cause suboptimal behavior.

MediumSystem Design

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Design a storage plan for a social media app that stores user images (hot), metadata (database), and compliance logs (cold). Provide capacity estimates based on growth assumptions, IO patterns for each store, backup/archival cadence, and cost vs performance tradeoffs.

EasyTechnical

0 practiced

Define SLO, SLI, and SLA, and explain how capacity planning can cause violations of these constructs. Provide a concrete example where an aggressive cost-cutting capacity change caused an SLO breach and how you would prevent that in future planning.

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