Cloud Engineer Interview Help: AWS, Azure, and GCP Questions with AI Prep

The Cloud Interview Challenge

Cloud engineering interviews are uniquely broad. You might get asked about VPC networking, IAM policies, serverless architectures, cost optimization, security best practices, and multi-cloud strategy — all in one session. Each cloud provider has hundreds of services, and interviewers expect you to know the right one for each scenario.

The reality is that even experienced cloud engineers specialize. An AWS expert might not know Azure's networking model in detail. A GCP specialist might not remember AWS IAM intricacies. This breadth is where AI interview assistance becomes genuinely valuable.

Core Cloud Concepts (Asked Regardless of Provider)

1. Explain the shared responsibility model.

Cloud provider secures the infrastructure (physical, network, hypervisor). Customer secures everything they put on it (data, IAM, application code, OS patches for IaaS). The line shifts depending on the service type — more managed means less customer responsibility.

2. How do you design for high availability?

Multi-AZ/region deployment, load balancing, auto-scaling, health checks, database replication, CDN for static content, DNS failover. Design for failure — assume any component can fail.

3. What is the difference between vertical and horizontal scaling?

Vertical: bigger instances (limited by hardware). Horizontal: more instances (limited by architecture). Most cloud-native apps prefer horizontal for better fault tolerance and cost efficiency.

4. How do you handle disaster recovery in the cloud?

RPO/RTO definitions drive the strategy. Options range from backup/restore (cheapest, highest RTO) to pilot light, warm standby, and multi-region active-active (most expensive, lowest RTO).

5. Explain the concept of Infrastructure as Code.

Infrastructure defined in configuration files (Terraform, CloudFormation, Pulumi), version controlled, reviewed like application code, reproducible across environments.

AWS-Specific Questions

6. Compare EC2, ECS, EKS, Lambda, and Fargate — when do you use each?

EC2 for full control. ECS for simple container orchestration. EKS for Kubernetes-native teams. Lambda for event-driven, short-duration workloads. Fargate for serverless containers without managing nodes.

7. Design a serverless API on AWS.

API Gateway + Lambda + DynamoDB. Consider: cold starts, concurrency limits, API Gateway throttling, DynamoDB capacity modes (on-demand vs provisioned), CloudWatch for monitoring.

8. Explain VPC networking — subnets, route tables, security groups, NACLs.

VPC is your isolated network. Public subnets have internet gateway routes; private subnets use NAT gateway. Security groups are stateful (per-instance); NACLs are stateless (per-subnet). Route tables control traffic flow.

9. How do you implement least-privilege IAM?

Start with no permissions, add only what is needed. Use IAM roles over users, policies with specific resource ARNs, condition keys, permission boundaries. Use Access Analyzer to find unused permissions.

10. What is AWS Organizations and how do you use it?

Multi-account management. OUs for organizing accounts, SCPs for guardrails, consolidated billing, centralized CloudTrail and Config. Landing Zone or Control Tower for setup.

Azure-Specific Questions

11. Compare Azure App Service, AKS, Container Instances, and Functions.

App Service for managed web apps. AKS for Kubernetes workloads. Container Instances for simple, short-lived containers. Functions for event-driven serverless.

12. Explain Azure Resource Manager and ARM templates vs Bicep.

ARM is the management layer. ARM templates are JSON-based IaC (verbose). Bicep is a cleaner DSL that compiles to ARM templates. Terraform also works with Azure.

13. How does Azure Active Directory differ from traditional AD?

Azure AD is cloud-native identity. No domain controllers, no LDAP (uses REST APIs and OAuth/OIDC). Supports SSO, conditional access, B2B/B2C identity. Hybrid with AD Connect.

GCP-Specific Questions

14. What is Google Cloud's approach to networking?

Global VPC (unlike AWS regional VPCs), shared VPC for multi-project networking, Cloud Interconnect for hybrid, Cloud CDN, global load balancing with anycast IPs.

15. Compare Cloud Run, GKE, and Cloud Functions.

Cloud Run for containerized apps without cluster management. GKE for full Kubernetes control. Cloud Functions for lightweight event-driven code. Cloud Run is the sweet spot for most workloads.

16. Explain BigQuery architecture.

Serverless data warehouse. Separation of storage and compute. Columnar storage format (Capacitor). Dremel query engine for fast analytical queries. Slots for compute allocation.

Multi-Cloud and Architecture Questions

17. How do you approach multi-cloud?

Use cases: vendor lock-in mitigation, best-of-breed services, compliance requirements. Challenges: increased complexity, skill requirements, networking. Kubernetes and Terraform help with portability.

18. Design a microservices architecture in the cloud.

Service decomposition, API gateway, service mesh, event-driven communication (queues/topics), distributed tracing, circuit breakers, centralized logging, container orchestration.

19. How do you optimize cloud costs?

Right-sizing, reserved instances/committed use, spot/preemptible instances, auto-scaling, storage tiering, unused resource cleanup, cost allocation tags, FinOps practices.

20. Explain zero-trust networking in the cloud.

Never trust, always verify. Identity-based access, micro-segmentation, encryption in transit and at rest, continuous authentication, BeyondCorp model.

Using AI for Cloud Interview Preparation

Cloud interviews test an impossibly broad knowledge base. No one remembers every AWS service, every Azure resource type, and every GCP API. In your daily work, you use documentation constantly.

Craqly's AI assistant acts as that documentation during your interview. When asked about VPC networking, it reminds you of the key components. When asked to compare services across clouds, it provides the differentiators. You still need hands-on experience and genuine understanding — the AI handles the recall of specific details you might forget under pressure.

Start with a AI interview copilot focused on cloud topics to see how the real-time suggestions work for technical questions.