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Practice cloud architecture questions covering multi-region deployments, disaster recovery, cost optimization, and well-architected framework principles.
Answer a real Cloud Architecture interview question before you browse the list. No signup needed.
A content management application runs on EC2 instances in an Auto Scaling group across three Availability Zones. Every instance must read and write the same set of user-uploaded files through a standard file system interface (POSIX), and files must remain available if an AZ fails. Which storage solution should a solutions architect choose?
Practice in a session
10 questions from Cloud Architecture, one after another, then your score and streak.
Cloud architecture interviews assess your ability to design scalable, reliable, and cost-effective systems. Topics include multi-region deployments, disaster recovery (RPO/RTO), high availability patterns, security architecture, cost optimization, and applying well-architected framework principles.
Cloud architecture focuses specifically on leveraging cloud services and patterns, while system design is broader. Cloud architecture interviews expect you to name specific services, understand pricing models, and design for cloud-native patterns like serverless, managed services, and auto-scaling.
RPO (Recovery Point Objective) is the maximum acceptable data loss measured in time - how much data you can afford to lose. RTO (Recovery Time Objective) is the maximum acceptable downtime. A lower RPO requires more frequent backups, and a lower RTO requires faster failover infrastructure.
Use active-active or active-passive configurations. Active-active serves traffic from all regions simultaneously for lower latency. Active-passive keeps a standby region for failover. Consider data replication strategy, DNS routing, and eventual consistency challenges. Global load balancers route users to the nearest healthy region.
Use reserved instances or savings plans for predictable workloads. Right-size instances based on actual usage. Use spot/preemptible instances for fault-tolerant workloads. Implement auto-scaling. Delete unused resources. Use storage lifecycle policies to tier cold data. Tag resources for cost allocation and accountability.
Serverless (Lambda, Cloud Functions) abstracts all infrastructure - you pay per invocation and scale automatically to zero. Containers (ECS, GKE) give you more control over the runtime, support long-running processes, and are better for consistent high-traffic workloads. Serverless has cold start latency while containers have more predictable performance.