Multi Cloud Interview Q&A

Q: When would you choose this platform?

Choose based on: existing vendor relationships, team expertise, compliance requirements, pricing for your specific workload mix, and regional availability.

Q: What are the core shared services across clouds?

Compute (EC2/VM/GCE), Object Storage (S3/Blob/GCS), Managed K8s (EKS/AKS/GKE), IAM (IAM/AAD/IAM), Serverless (Lambda/Functions/Cloud Functions), Database (RDS/Azure SQL/Cloud SQL).

Q: How do you manage costs in this cloud?

Use reserved/committed use for baseline workloads (40-60% savings). Spot/preemptible for batch/fault-tolerant. Right-size instances (use monitoring data). Storage tiering. Auto-scaling to match actual demand.

Quick Reference — Multi Cloud

Key Points for Revision

•Review the overview section for core architecture and fundamentals

•Practice commands/configurations from the cheatsheet section

•Use interview Q&A for active recall before exams or interviews

•Cross-reference with related tools in the cloud academy

Practice Approach

1.Read the overview to understand what and why

2.Work through fundamentals for how

3.Attempt hands-on labs or configurations

4.Test yourself with interview questions

5.Keep cheatsheet accessible for quick reference during work

Further Learning

Connect this topic to the broader cloud ecosystem.

Each tool in this academy is designed to work with others —

understanding the integration points is what separates intermediate from senior practitioners.

Multi-Cloud Interview Q&A

Q: What are the main drivers for multi-cloud adoption?

Avoid vendor lock-in, regulatory requirements (data sovereignty across regions), best-of-breed services (AWS ML + GCP BigQuery), M&A (acquiring companies with different clouds), disaster recovery across providers, negotiating leverage. Reality: most multi-cloud is accidental (from M&A) rather than planned.

Q: What are the main challenges of multi-cloud?

Complexity: different APIs, tooling, IAM models, networking primitives. Skills: team needs expertise in multiple platforms. Cost: harder to optimize reservations/committed use across providers. Networking: cross-cloud traffic incurs egress costs and latency. Security: inconsistent policy enforcement across providers.

Q: How does Terraform enable multi-cloud?

Single HCL codebase with multiple provider blocks. Different state backends per cloud. Module abstraction: common interfaces with cloud-specific implementations. Terraform Cloud/Enterprise manages workspaces per cloud. Limitation: abstractions are leaky — still need to understand each cloud's primitives.

Q: What is a cloud-agnostic architecture?

Design that avoids provider-specific services (prefer open standards): Kubernetes over managed container services, PostgreSQL over Aurora/Cloud SQL, Kafka over managed messaging, S3-compatible storage API. Trade-off: lose provider-specific features and managed service benefits. Only worth it if actual portability is required.

Q: How do you handle identity across multiple clouds?

Federate identity: use a central IdP (Okta, Azure AD/Entra, Google Workspace) and federate to each cloud via OIDC/SAML. AWS: identity federation with AssumeRoleWithWebIdentity. Azure: external identity federation via Entra ID. GCP: Workload Identity Federation. Avoids managing separate IAM users per cloud.

This section is part of the SynfraCore learning platform. Use the sidebar to navigate to Overview, Fundamentals, Advanced, and Cheatsheet sections for comprehensive coverage of this topic.

Multi-Cloud Strategy — Interview Q&A