Designing Cloud Infrastructure for a Web Application

Here’s a simple high-level cloud infrastructure design for a web application. The main objective is to build a solution that is scalable, highly available, and simple to manage. By carefully selecting each component, I aimed to ensure that the architecture could handle fluctuating traffic while maintaining performance and reliability.


The Architecture Breakdown

The design consists of three key layers: Frontend, Backend, and Database. Each layer is supported by a load balancer to distribute traffic effectively. Additionally, horizontal scaling was prioritized to ensure the application could grow or shrink based on demand.


1. Frontend Layer: EC2 for Hosting

For the frontend, I chose an EC2 instance running a web server to serve the application. These instances are part of an Auto Scaling Group (ASG) to enable dynamic scaling based on traffic.

  • How it works:

    • Application Load Balancer (ALB): A public ALB distributes incoming requests from users to the EC2 instances hosting the frontend.

    • Scaling: The ASG automatically adjusts the number of frontend instances to handle spikes or dips in traffic.

  • Why I chose EC2:

    • Flexibility: EC2 allows complete control over the hosting environment.

    • Customizability: It supports deploying specific web servers or frameworks.


2. Backend Layer: Scalable Logic

The backend, like the frontend, is hosted on EC2 instances in an Auto Scaling Group (ASG) for horizontal scaling. These instances are spread across multiple Availability Zones (AZs) for fault tolerance and handle API requests and business logic.

  • How it works:

    • Internal ALB: An internal Application Load Balancer routes traffic from the frontend instances to the backend EC2 instances.

    • Auto Scaling: Scaling is triggered by metrics like CPU utilization or request count.

  • Why this setup works:

    • Reliability: Multi-AZ distribution ensures availability even if one AZ goes down.

    • Efficiency: Dynamic scaling minimizes costs while meeting demand.


3. Database Layer: Amazon DynamoDB

For the database, I chose Amazon DynamoDB, a fully managed NoSQL database that eliminates the need for redundant instances or manual scaling.

  • How it works:

    • DynamoDB provides a seamless way to handle both high and low traffic volumes by automatically scaling read and write capacity.
  • Why DynamoDB stood out:

    • Scalability: It scales elastically without needing explicit instance management.

    • High Availability: Data is replicated across multiple AZs, ensuring durability and low-latency access.


Traffic Flow: Connecting the Dots

  1. Users → Public ALB: External requests are routed through the public ALB to the frontend ASG (EC2 instances in public subnets).

  2. Frontend → Internal ALB: The frontend EC2 instances send API requests to the backend via an internal ALB.

  3. Backend → DynamoDB: Backend EC2 instances interact with DynamoDB to retrieve or store application data.

This setup ensures that each component operates independently but seamlessly integrates to deliver a smooth user experience.


Key Takeaways

  • Horizontal Scaling is Crucial: Allowing each layer to scale independently ensures the system remains responsive during traffic spikes.

  • Fault Tolerance is Non-Negotiable: Distributing resources across multiple AZs provides resilience against failures.


By combining EC2 instances, load balancers, and DynamoDB, this architecture achieves high availability, scalability, and performance. This project deepened my understanding of designing cloud infrastructure and reinforced the importance of choosing the right tools for each layer.

What are your thoughts on this design? Have you implemented something similar? I'd love to hear your insights!