Cloud Architecture Interview Questions for India 2026

Cloud architecture interviews test design thinking more than service memorisation. Core concepts: High availability vs fault tolerance: HA means minimising downtime (achieved through redundancy); fault tolerance means zero downtime even during failures (more expensive, usually reserved for critical systems). RPO and RTO: Recovery Point Objective (how much data loss is acceptable) and Recovery Time Objective (how long the system can be down). These drive disaster recovery design. Multi-region vs multi-AZ: multi-AZ handles data centre failures (availability zones within one region). Multi-region handles regional failures or global latency requirements. Circuit breaker pattern: prevents cascade failures in microservices: stops calls to a failing service and returns a fallback. CAP theorem: distributed systems can guarantee only two of Consistency, Availability, and Partition Tolerance.

Common AWS architecture design questions at Indian interviews: Design a highly available web application on AWS. Answer: Route 53 (DNS + health checks), CloudFront (CDN), Application Load Balancer, Auto Scaling Group of EC2 instances in multiple AZs, RDS Multi-AZ (PostgreSQL), ElastiCache Redis (session and cache), S3 (static assets), CloudWatch (monitoring). Design a real-time notification system. Answer: API Gateway + Lambda (ingestion), Kinesis Data Streams (real-time processing), Lambda consumers, DynamoDB (state storage), SNS/SQS (fan-out to email, push, SMS). Design a file processing pipeline. Answer: S3 (upload trigger), SQS queue (decoupled processing), Lambda or ECS tasks (processing workers), DynamoDB (job status tracking), S3 (output storage), CloudFront (download delivery).

Serverless (Lambda/Cloud Functions) vs containers (ECS/GKE): Serverless strengths: zero infrastructure management, automatic scaling, pay-per-execution (cost-efficient at low volume), fast deployment. Serverless limitations: cold start latency (critical for customer-facing, latency-sensitive APIs), maximum execution time (Lambda = 15 minutes), difficult to debug, stateless by design. Containers (ECS/EKS/GKE) strengths: predictable performance, long-running processes, stateful workloads, full control over environment. When to choose: event-driven, intermittent workloads: serverless. Consistent high-traffic APIs: containers. ECS vs EKS: ECS is AWS-native and simpler to manage for most use cases. EKS is Kubernetes: preferred when team already has k8s expertise or needs vendor-agnostic portability.

Cost optimisation is increasingly tested at senior cloud roles: Right-sizing: identify underutilised instances with CloudWatch metrics. EC2 instance types: On-Demand (full price, no commitment), Reserved Instances (1-3 year commitment, 30-60% discount), Spot Instances (spare capacity, 70-90% discount, can be interrupted: suitable for batch jobs, ML training). S3 storage tiers: Standard, Infrequent Access, Glacier: lifecycle policies to move data to cheaper tiers automatically. Data transfer costs: often overlooked: egress from AWS is charged, cross-AZ data transfer is also charged. Cloud security: IAM (principle of least privilege, role-based access, no long-lived access keys), VPC security groups vs NACLs, encryption at rest (KMS) and in transit (TLS), AWS Config and CloudTrail for compliance and audit.

Large Indian enterprises and IT services firms increasingly run multi-cloud environments spanning AWS, Azure, and Google Cloud. Interview questions at companies like Infosys, HCL, and Wipro often ask candidates to design workload distribution across clouds for regulatory and latency reasons. A common scenario is: "Design an architecture for an Indian bank that must keep customer data on Azure (due to existing Microsoft contract) while running ML workloads on AWS SageMaker." Interviewers expect you to address data egress costs, cross-cloud VPN or interconnect options, and compliance with RBI data localisation guidelines. Candidates with AWS Solutions Architect and Azure Administrator certifications are preferred at senior cloud roles starting from 25 LPA.

Indian organisations are acutely cost-sensitive with cloud spend, and interviewers test whether architects can balance reliability with rupee-denominated budgets. Common question formats include: "Our AWS bill is 1.2 crore per month: identify three architectural changes to reduce it by 30 percent." Expected answers cover Reserved Instance and Savings Plan commitments, right-sizing underutilised EC2 instances using AWS Compute Optimizer, moving cold data to S3 Glacier, and replacing always-on servers with Lambda for event-driven workloads. For Azure environments, mention Azure Hybrid Benefit for Windows Server licensing. Demonstrating familiarity with AWS Cost Explorer or Azure Cost Management dashboards during discussion signals hands-on experience that purely theoretical candidates lack.

Cloud architects interviewing at BFSI or healthcare companies in India must demonstrate understanding of regulatory compliance. The Reserve Bank of India mandates that payment system data remain within Indian borders, making AWS ap-south-1 (Mumbai) and Azure India Central the default regions for fintech workloads. Interviewers will test whether you know how to implement encryption at rest using AWS KMS or Azure Key Vault with customer-managed keys, and how to configure CloudTrail or Azure Monitor for audit logging. SEBI-regulated entities require six-year audit trail retention. Healthcare companies must align with DPDP Act 2023 data processing principles. Naming these regulators by name and citing specific controls demonstrates readiness for senior cloud architect roles at 30 to 50 LPA.