Build vs. Buy vs. Cloud vs. On Premise Trade Offs Questions
Understanding key trade-offs in technology decision-making: (1) Build vs. Buy - custom development flexibility vs. packaged software speed/cost, (2) Cloud vs. On-Premise - operational burden, control, scalability, security, cost, (3) SaaS vs. Licensed - flexibility, upgrade frequency, customization options. Understanding implications for cost, time-to-value, flexibility, control, and ongoing support.
MediumTechnical
0 practiced
Implement a Python function estimate_monthly_cost(compute_hours, storage_gb, egress_gb, rates) that returns a dictionary with 'cloud' and 'onprem' estimated costs. Rates is a dict like {'cloud': {'cpu': 0.05, 'storage_per_gb': 0.025, 'egress_per_gb': 0.09}, 'onprem': {...}}. Apply a 10% storage discount for volumes > 10,000 GB. Include basic unit tests for zero usage and a large-scale case.
HardTechnical
0 practiced
You must guarantee end-to-end correctness for financial transaction streams. Compare using a managed streaming product that advertises exactly-once semantics across producers/processors/sinks versus self-hosted Kafka with idempotent producers and idempotent sinks (resulting in at-least-once). Discuss implementation complexity, latency, performance, cost, and operational risk for both options.
HardTechnical
0 practiced
Design a benchmarking plan to compare Trino/Presto on-premise against cloud-native query engines (e.g., BigQuery/Snowflake) operating on comparable datasets stored in HDFS vs cloud object storage. Include dataset characteristics, workload mix, concurrency testing, warm vs cold cache, metrics to collect, and how to ensure a fair comparison.
MediumSystem Design
0 practiced
You must select a data warehouse for this workload: 200 concurrent BI users, 5 TB compressed active data, monthly 200 TB scanned by queries, unpredictable month-end peaks. Compare cloud-managed warehouses (Snowflake, BigQuery) versus an on-prem MPP (Greenplum/Vertica), focusing on cost, concurrency, elasticity, maintenance, and vendor support—then recommend one approach and justify your choice.
HardTechnical
0 practiced
Your cloud bill shows heavy spikes from 100 TB egress/month at $0.09/GB and repeated scans of hot storage. Propose a prioritized set of optimizations (caching, query rewrite, regionalization, reserved capacity, negotiated egress discounts). Provide estimated monthly savings given the 100 TB egress baseline for each optimization you propose.
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