System Design Interview Prep: AWS Edition

In a standard System Design interview, it is perfectly acceptable to use generic terms like "Load Balancer," "Blob Storage," and "Message Queue."

However, if you are interviewing at Amazon (AWS), or if you want to demonstrate deep production-level expertise at a startup, specifically naming and architecting with AWS services will significantly elevate your score.

Here is your cheat sheet for mapping generic System Design concepts to their enterprise AWS equivalents.

1. Compute and Load Balancing

When an interviewer asks you to scale the application servers, you must choose the right compute layer.

• Generic: Application Server

• AWS Standard: Amazon EC2 (Elastic Compute Cloud) inside an Auto Scaling Group.

• AWS Containerized: Amazon ECS (Elastic Container Service) or EKS (Kubernetes) with AWS Fargate for serverless compute.

• AWS Serverless: AWS Lambda. (Use this for event-driven architectures, like image resizing upon upload).

• Generic: Load Balancer

• AWS Equivalent: Application Load Balancer (ALB) for HTTP/HTTPS traffic (Layer 7). Network Load Balancer (NLB) for extreme performance TCP traffic (Layer 4).

2. Databases

Do not just say "I will use a database." You must specify SQL vs NoSQL, and choose the correct AWS engine.

• Generic: Relational Database (SQL)

• AWS Equivalent: Amazon RDS (PostgreSQL/MySQL) or Amazon Aurora (for massive, cloud-native scalability with read replicas).

• Use case: Financial transactions, user accounts, strict ACID compliance.

• Generic: Wide-Column / Key-Value (NoSQL)

• AWS Equivalent: Amazon DynamoDB.

• Use case: Massive read/write scale, shopping carts, session data.

• Generic: Caching Layer

• AWS Equivalent: Amazon ElastiCache (Redis or Memcached).

• Use case: Caching database queries to reduce latency and protect the primary database from read-spikes.

3. Storage and Content Delivery

• Generic: Blob / Object Storage

• AWS Equivalent: Amazon S3 (Simple Storage Service).

• Use case: Storing user-uploaded photos, videos, or static assets.

• Generic: Content Delivery Network (CDN)

• AWS Equivalent: Amazon CloudFront.

• Use case: Caching static assets at edge locations globally to reduce latency for international users.

4. Asynchronous Messaging

To prevent tight coupling between microservices, you need a message queue or a pub/sub system.

• Generic: Message Queue

• AWS Equivalent: Amazon SQS (Simple Queue Service).

• Use case: Decoupling heavy background jobs (like sending emails or processing video) from the main application thread.

• Generic: Pub/Sub (Publish-Subscribe)

• AWS Equivalent: Amazon SNS (Simple Notification Service) or Amazon MSK (Managed Streaming for Apache Kafka).

• Use case: Fan-out architectures (e.g., A user uploads a video, SNS triggers three different Lambdas: one for compression, one for thumbnail generation, and one for malware scanning).

[!TIP] Defend Your Choices: Interviewers don't care that you know the name "DynamoDB." They care why you chose it. Always follow up your component selection with the specific trade-offs (e.g., "I chose DynamoDB over RDS because we need single-digit millisecond latency at any scale, and we are willing to sacrifice complex JOIN operations to get it.")