5 Fundamental Architectures You Should Know for Cloud Interviews
Hey, it’s Lefteris 👋 I’m the voice behind the weekly newsletter “The Cloud Engineers.”
If you want to break into a cloud role (Cloud Engineer, Cloud Developer, Software Engineer, DevOps, SRE, Solutions Architect, etc.) and you have an interview coming up, understanding cloud architecture is non-negotiable if you want to stand out in interviews.
Most candidates focus on certifications or memorising AWS services, but interviews are designed to test something deeper: how you think about building scalable, reliable, and resilient systems.
In this article, we’ll look at 5 fundamental architectures you should know. Master them, understand the trade-offs behind them, and you’ll stand out for the right reasons.
If you want hands-on practice with these 5 architectures, grab my free PDF, 5 AWS Projects To Get You Hired., featuring 5 real-world AWS projects with architecture diagrams and step-by-step implementation guides.
1. 3-Tier Architecture
This is the foundation. Frontend, backend, database: three distinct layers, each with a clear responsibility. Simple in concept, but interviewers expect you to go far beyond drawing three boxes on a whiteboard.
Key AWS Services: CloudFront + S3 (frontend), ALB + EC2/ECS with Auto Scaling (backend), RDS Multi-AZ or Aurora (database).
What interviewers expect you to know:
How to scale each tier independently: stateless backends behind a load balancer, read replicas for database read-heavy workloads.
Failure scenarios: what happens when an AZ goes down? How does Multi-AZ RDS failover work?
Caching strategies: ElastiCache between backend and database to reduce latency and DB load.
The difference between horizontal and vertical scaling, and why horizontal wins at scale.
When discussing this architecture, show that you understand the why behind each layer’s separation, not just the what.
2. Microservices
Breaking a monolith into smaller, independent services sounds clean on paper. In practice, it introduces a whole new category of challenges.
Key AWS Services: ECS or EKS, Lambda.
What interviewers expect you to know:
Trade-offs vs. monoliths: when the operational overhead isn’t worth it (small teams, early-stage products).
Data ownership: each service owns its data store. No shared databases.
How you handle failures across service boundaries: circuit breakers, retries with exponential backoff, timeouts.
Observability: how do you trace a request that flows through 5 services?
The key insight interviewers look for: you chose microservices because the problem demanded it, not because it was trendy.
3. Serverless
No servers to patch, no infrastructure to manage. You can build entire applications without provisioning a single instance.
Key AWS Services: Lambda, API Gateway.
What interviewers expect you to know:
Cold starts: what causes them, how to mitigate
Cost model: pay-per-invocation is cheap at low scale but can surprise you with high-throughput workloads. Know the break-even point vs. containers.
When NOT to use serverless: long-running processes, workloads needing persistent connections, or latency-critical paths where cold starts are unacceptable.
The interview-winning move is demonstrating that you can evaluate when serverless is the right tool and when it introduces more problems than it solves.
4. Event-Driven Architecture
This is where modern cloud design becomes powerful. Instead of services calling each other directly, they produce and consume events asynchronously. The result: loose coupling, high scalability, and systems that are naturally resilient to spikes in traffic.
Key AWS Services: EventBridge, SNS, SQS.
What interviewers expect you to know:
The difference between queuing (SQS one consumer) and pub/sub (SNS fan-out to many consumers).
Eventual consistency: data won’t be immediately up to date across services. You need to explain how your system handles this.
Idempotency: events can be delivered more than once. Your consumers must handle duplicates gracefully.
Dead-letter queues: what happens when an event fails processing repeatedly? How do you monitor and replay?
A real scenario: an order is placed → event fires → inventory, notifications, and analytics services react independently without knowing about each other.
The challenge is showing you can design systems where components don’t need to know about each other but still behave correctly as a whole.
5. Containers
Containers give you consistency across environments and fine-grained control over your runtime. They sit between the full control of EC2 and the abstraction of serverless.
Key AWS Services: ECS, EKS, ECR.
What interviewers expect you to know:
When containers beat serverless: long-running processes, specific runtime needs, workloads needing persistent connections, or apps being migrated from on-premises.
When serverless beats containers: short-lived, event-triggered functions with variable traffic.
Health checks, rolling deployments, and blue/green strategies for zero-downtime updates.
You don’t need to be a Kubernetes expert. But you should understand pods, services, and why teams choose (or avoid) K8s.
Conclusion
These five architectures cover the vast majority of what you’ll face in cloud interviews. You don’t need to memorise every AWS service. You need to understand patterns, trade-offs, and when to apply each one.
The candidates who stand out are the ones who can explain why they chose an architecture, not just draw it on a board. Show your reasoning. Discuss trade-offs. Acknowledge limitations.
Cloud interviews are rarely about knowing the “correct” AWS service. They’re about proving you can make good engineering decisions under constraints.
If you want hands-on practice with these 5 architectures, grab my free PDF, 5 AWS Projects To Get You Hired., featuring 5 real-world AWS projects with architecture diagrams and step-by-step implementation guides.