Startup Ground to Cloud: Lifting a 3-Layer Monolith Into the Cloud

Introduction

Welcome back to our "Ground to Cloud" series, where we unravel the journey of migrating different architectural patterns to cloud infrastructure. Today, we're focusing on the 3-layer monolith—a classic architecture pattern that's particularly advantageous for startups poised to swiftly launch their MVPs and scale with precision. The 3-layer architecture is one of the most common patterns used by companies, largely because it mirrors the typical structure of development teams, divided into UI designers, backend developers, and database administrators. Despite the emergence of new patterns aimed at addressing the issues of layered monoliths, the 3-layer approach remains arguably one of the fastest and easiest way to build MVPs and maintain applications for startups in their early phases. With this context in mind, let's explore how to adapt this architecture for the cloud, utilizing a common stack to build a scalable 3-Layer Monolith.

The Startup Conundrum: Quick Launch vs. Scalable Architecture

For startups, the challenge lies in launching a scalable, maintainable product quickly without getting ensnared by the complexities of advanced software architectures. The 3-layer architecture, consisting of a presentation layer (UI), a logic layer (backend API), and a data layer (database), aligns neatly with common development team structures and offers a straightforward path to development and maintenance.

Migrating to the Cloud: A Strategic Overview

Front-End Layer

Keeping user interfaces responsive and engaging is crucial for startups. The choice between JavaScript and TypeScript often depends on the team's preference and the project's requirements. Also, there are three major frameworks dominate the landscape: React, Vue, and Angular. Each framework has its own set of advantages, ecosystem, and use cases, making the choice between them crucial for startups looking to optimize their user interface development.

Cloud Solution: AWS Amplify is a comprehensive service that supports the deployment of both JavaScript and TypeScript applications (as well as React, Angular, Vue, and other UI Frameworks), offering scalable hosting solutions that integrate seamlessly with other AWS services. This flexibility ensures that startups can develop and deploy front-end applications that are both dynamic and scalable, meeting the needs of a growing user base.

Backend Layer

The backend serves as the backbone of your application, processing requests, handling business logic, and interacting with the database. Django Rest Framework for Python and NestJS are among the most popular choices for developing robust APIs, thanks to their extensive community support, scalability, and ease of use. The choice here usually heavily relies on team expertise, both can work on wide range of use cases so as long as you do your research then it should all be fine. Besides these two, there are other ones like Flask, FastAPI, Plain NodeKS + Express, and more to choose from depending on your needs and team skills.

Cloud Solution: Containerizing the backend with Docker and deploying it on AWS ECS Fargate allows startups to manage their backend services without the hassle of server maintenance. This serverless approach ensures that resources are automatically scaled according to the application's needs, providing a cost-effective solution for startups looking to optimize their backend operations. With this approach, any framework you choose will work as long as you properly containerize it.

Database Layer: Open-Source vs. Proprietary Databases

A reliable database is essential for storing, retrieving, and managing application data efficiently. Open-source databases like MySQL and PostgreSQL are favored for their flexibility, robustness, and cost-effectiveness. However, some startups may opt for proprietary databases such as Microsoft SQL Server or Oracle, depending on specific requirements or existing infrastructure.

Cloud Solution: AWS RDS supports a wide range of database engines, including MySQL, PostgreSQL, Microsoft SQL Server, and Oracle. This managed database service simplifies operations such as provisioning, scaling, backups, and recovery, allowing startups to focus on their core product development without worrying about database management.

Add On: Optimizing with Asynchronous Processing

In developing responsive web applications, particularly with the 3-layer architecture, it's crucial to address potential responsiveness bottlenecks. These often arise from long-running tasks that do not need to be immediately reflected in the API response, such as image processing, cache updates, third-party synchronizations, and indexing operations. Integrating asynchronous processing mechanisms is a strategic move to enhance application performance without compromising the user experience.

Queue-Based Task Management: The nature of N-layered monoliths, with their comprehensive codebases and predefined routines, simplifies the process of transitioning long-running tasks into a queued system. By offloading these tasks to a queue, they can be processed independently of the main application flow, allowing the API to respond to requests more swiftly. This setup involves the use of queue workers, which are responsible for executing tasks as they are received, ensuring that resource-intensive processes do not block the main thread.

Choosing the Right Queue System: AWS offers two primary solutions for implementing queue-based asynchronous processing:

• AWS SQS (Simple Queue Service): For those seeking a fully managed message queuing service, AWS SQS provides a secure, scalable, and straightforward solution. It enables the decoupling of microservices, distributed systems, and serverless applications, facilitating reliable message processing and transmission without the need for a third-party messaging system.

• AWS Elastic Cache (for Redis): For teams already utilizing Redis for caching purposes, AWS Elastic Cache presents an efficient way to incorporate queue management without introducing additional systems. Redis, known for its high performance, supports various data structures such as strings, hashes, lists, and queues, making it versatile for handling asynchronous tasks.

By adopting a queue-based architecture for handling long-running tasks, startups can significantly improve the responsiveness of their 3-layer monoliths. Whether opting for AWS SQS for its simplicity and reliability or leveraging AWS Elastic Cache to utilize existing Redis setups, the key is to choose a system that aligns with the application's architectural needs and operational preferences. The integration of asynchronous processing, combined with the advantages of containerization, sets the stage for building resilient, high-performing applications capable of scaling alongside the startup's growth.

Wrapping Up: From Ground to Cloud with Confidence

Migrating a 3-layer monolith to the cloud is a strategic step for startups aiming for scalability and efficiency. This installment of the "Ground to Cloud" series demonstrates how cloud technologies like AWS Amplify, ECS Fargate, and RDS can transform the traditional 3-layer architecture into a dynamic, scalable solution ready for the demands of modern users. As we continue exploring architectural migrations in this series, remember that adopting cloud infrastructure is not just about leveraging new technologies—it's about empowering your startup to grow and adapt in an ever-changing digital landscape.

Stay tuned for more insights as we navigate the cloud together, ensuring your architecture is not just ready for today but built for tomorrow's challenges.