Cloud Data Architecture and Tradeoffs Questions

Designing data architectures specifically for cloud environments and evaluating platform trade offs. Topics include when to use managed relational services, managed nonrelational services, cloud data warehouses, cloud object storage, lifecycle policies, cross region replication, data residency and compliance considerations, cost versus performance trade offs, managed service operational constraints, and strategies for high availability and disaster recovery in the cloud. Candidates should be able to compare cloud service options and justify choices based on reliability, cost, and compliance.

EasyTechnical

46 practiced

A client has hundreds of data assets and asks why a metadata catalog is important. Describe the benefits for data discovery, governance, lineage, and self-service analytics, and list three practical steps to onboard teams to a new data catalog.

MediumTechnical

45 practiced

For low-latency financial trade processing where end-to-end latency target is sub-millisecond, evaluate managed streaming services versus a self-managed streaming infrastructure. Consider determinism, latency, failover, compliance, and operational costs in your recommendation.

HardTechnical

53 practiced

Serverless data processing is appealing to reduce ops, but it has constraints like cold starts and concurrency limits. Propose architecture patterns to implement ELT pipelines using serverless compute while mitigating cold-starts, throughput limits, and resource throttling.

MediumSystem Design

47 practiced

Design a multi-tenant analytics platform for SaaS customers where tenants have isolated workloads, share base datasets, and the platform must prevent noisy neighbor effects. Describe tenancy models, resource isolation approaches, cost allocation, and how to support tenant-specific security policies.

HardSystem Design

48 practiced

Design a backup and restore strategy for a petabyte-scale data lake that must meet RPO of 1 hour and RTO of 4 hours. Cover cross-region replication, versioning, catalog consistency, restore orchestration, and the tradeoffs of retaining multiple recovery points.

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