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.
MediumSystem Design
0 practiced
Your analytics users are distributed across EU and APAC and require low-latency dashboards plus EU-only residency for some customer data. Compare multi-region single-cloud, multi-cloud, and single-cloud with on-prem edge nodes. Discuss replication, consistency, operational complexity, cost, and compliance trade-offs.
HardSystem Design
0 practiced
A major cloud region is down for 7 days. Your pipelines run on managed cloud services in that region. Design an architecture and operational plan to continue critical ingestion and analytics during extended regional outages while balancing cost. Discuss cross-region replication, warm-standby, multi-cloud failover, and pre-seeding data for quick recovery.
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.
MediumTechnical
0 practiced
Compare using a managed Kafka service (Confluent Cloud/MSK) versus running self-hosted Kafka for a company that ingests 100 TB/month of events. Discuss operational cost, latency, feature completeness (schema-registry, connectors), security, and vendor lock-in. Recommend an approach for a platform team of two engineers.
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.
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