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Cloud Platform Fundamentals Questions

Comprehensive understanding of core public cloud services and the primary trade offs when selecting among them across major providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Candidates should know compute options including virtual machines, managed compute, containers and serverless functions; storage types including object, block and file storage and lifecycle and archival strategies; managed database offerings for relational, non relational, and data warehouse workloads; networking fundamentals including virtual private networks, subnets, routing, load balancing, content delivery networks, and private connectivity; messaging and integration services such as message queues and event streaming; identity and access management and secrets management; monitoring, logging, and observability; autoscaling, elasticity, high availability, and basic disaster recovery patterns; and cost and pricing considerations. The topic also covers the trade offs between managed services and self managed infrastructure in terms of consistency, latency, cost, operational overhead, and durability, and the ability to map common workload requirements to the right service categories.

MediumTechnical
44 practiced
Describe VPC connectivity options for cross-account and on-prem networks: VPC peering, Transit Gateway/Hub, VPN, and Direct Connect/Interconnect. For a data-engineering use case that transfers large nightly datasets between accounts and to on-prem, which would you choose and why?
HardSystem Design
43 practiced
You're architecting cross-account data access for analysts that must query multiple data warehouses across accounts. Propose a secure architecture that minimizes data copying, addresses authentication and auditability, and considers query performance.
HardTechnical
40 practiced
Write pseudocode or describe in detail an approach to achieve exactly-once processing semantics for a streaming ETL pipeline using Kafka (or a cloud pub/sub) and Spark Structured Streaming or similar. Cover ingestion, idempotency, checkpointing, and sink semantics.
HardTechnical
42 practiced
Describe how you would lead a cross-functional migration from VM-based ETL jobs to a serverless architecture (e.g., managed serverless functions and managed dataflow). Include stakeholder engagement, rollout plan, risk mitigation, indicators of success, and training for the team.
EasyTechnical
39 practiced
Explain differences and typical use cases for a relational managed database (e.g., RDS, Cloud SQL), a NoSQL/document store (e.g., DynamoDB, Firestore), and a cloud data warehouse (e.g., Redshift, BigQuery). Give examples of data-engineering tasks suited to each.

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