Building Scalable Applications: Lessons from Nexaloom and Rareboots

Scalability is the magic word every developer and startup founder talks about but often struggle to achieve. The process of building scalable applications requires making the right architectural and technological decisions from the outset. In my journey building Nexaloom and Rareboots Marketplace, I’ve had my fair share of learning experiences—both successes and challenges. In this article, I’ll walk you through key lessons learned in building scalable applications, covering architectural decisions, tech choices, and practical steps to ensure your application can handle growth.

Lesson 1: Start with the Right Tech Stack

When you're setting out to build a scalable application, the choice of tech stack can make or break your project’s ability to handle future growth.

Choosing Node.js for Nexaloom

For Nexaloom, an appointment scheduling and business management software, the need for rapid development and scalability was obvious from the start. I decided to go with Node.js for the backend, primarily because of its non-blocking, event-driven architecture. Node.js has a reputation for handling a high number of concurrent connections, which is exactly what Nexaloom needed as it scaled to serve multiple businesses and users simultaneously.

Another win for Node.js is the JavaScript ecosystem. With JavaScript running on both the front-end and back-end, it allowed for a unified development process, reducing context switching between languages. This also meant that I could easily onboard new developers, as JavaScript remains a common denominator among web developers.

Choosing Medusa.js for Rareboots

On the other hand, when building Rareboots Marketplace, I had a different set of challenges. Rareboots needed a robust e-commerce platform that could handle multiple sellers, extensive product listings, and high traffic. Instead of building everything from scratch, I chose to use Medusa.js, an open-source e-commerce framework built on Node.js.

Medusa provided a solid foundation for the marketplace with built-in support for core features like cart management, order handling, and even Stripe integration. But here’s the important part: it was extensible. Medusa allowed me to extend functionality, particularly in areas like custom product filtering, handling marketplace-specific logic, and advanced payment flows. This saved a lot of time in development while still keeping the codebase lean and modular.

Lesson 2: Database Architecture Matters

It’s tempting to throw everything into a single database and call it a day, but that’s a surefire way to run into scaling issues later. For both Nexaloom and Rareboots, I had to carefully consider how data was stored and accessed.

Choosing PostgreSQL for Structured Data

In both applications, I chose PostgreSQL as the primary database. PostgreSQL shines when it comes to handling relational data at scale. It’s also highly versatile, allowing for complex queries, transactions, and data integrity, which was critical for both Nexaloom’s appointment data and Rareboots’ marketplace transactions.

In Nexaloom, for example, we deal with a lot of user-generated data—appointment schedules, client profiles, and payments. The data relationships are clear, so relational databases made the most sense. Moreover, PostgreSQL’s ability to handle large datasets with proper indexing ensured that as the platform grew, the performance didn’t degrade.

Caching with Redis

Scaling isn't just about the database itself but how data is accessed. For frequently accessed data, caching can significantly reduce load on the database. In Rareboots, where certain product searches and recommendations were repeatedly requested, I implemented Redis for caching. This made a huge difference in reducing latency and improving user experience as the marketplace scaled up.

Lesson 3: Modular, Microservice-Based Architecture

Monolith vs. Microservices

When Nexaloom first started, the application was monolithic—a single codebase handling everything from user authentication to appointment scheduling. This was fine for the initial stages, but as we grew, it became clear that managing this single large application was going to be a nightmare.

Enter microservices.

Moving to a microservices architecture allowed us to decouple features and services into independent modules. For example, we separated the appointment scheduling logic from user management. This approach not only improved scalability but also made it easier to deploy updates independently without affecting other parts of the system.

In Rareboots, I adopted a hybrid approach. Some core services, like the checkout and payment processes, were split into microservices, while the core product listing and management were kept together in a more modular monolithic style. This allowed for flexibility without overcomplicating things too early.

Communication Between Services

One important lesson in microservices is that you need an efficient way for services to communicate. For both Nexaloom and Rareboots, I used message queues for inter-service communication, specifically RabbitMQ. This ensures that as traffic scales and services need to communicate asynchronously (e.g., handling payment confirmation or sending out email notifications), the system can handle the load without bottlenecking.

Lesson 4: Scaling the Frontend

Component-Based UI Development with React

Both Nexaloom and Rareboots needed responsive, scalable UIs. React was my go-to choice because of its component-based structure. Components are reusable, easy to maintain, and can be rendered dynamically based on the data flowing in from the backend.

For Nexaloom, this meant creating reusable components for things like the appointment calendar and client profile forms. As the platform grew and more features were added, React’s component reusability allowed for quick iterations and updates without rewriting the entire UI.

Server-Side Rendering for Performance

For Rareboots, scalability was not just about handling traffic but also about performance. As an e-commerce platform, every second counts when it comes to load time, and a slow experience can mean lost sales. To ensure optimal performance, I implemented server-side rendering (SSR) using Next.js. SSR allowed us to serve pre-rendered pages to users, reducing the initial load time and improving SEO, both crucial for marketplace success.

Lesson 5: Don’t Ignore DevOps and CI/CD

When you’re building an application that needs to scale, having a solid DevOps pipeline in place is crucial.

Automating Deployments

Both Nexaloom and Rareboots required frequent updates, and manual deployments simply weren’t feasible. By setting up a CI/CD pipeline with Jenkins and GitLab CI, we were able to automate builds, run tests, and deploy code to production with minimal downtime. This allowed us to push updates faster without breaking the application or creating unnecessary bottlenecks.

Monitoring and Scaling with Kubernetes

As both applications started handling more traffic, I introduced Kubernetes to manage containerized services. Kubernetes allowed us to scale individual services up or down based on demand, making sure we never over-provision resources. It also helped in managing deployment rollbacks in case any issues arose in production.

Final Thoughts

Building scalable applications requires careful planning, the right tech stack, and a deep understanding of how your application will grow. With Nexaloom, I learned the importance of modular architecture, and with Rareboots, I gained firsthand experience in building marketplace features at scale.

Here’s the takeaway: Start small, but design your application with growth in mind. Whether it’s choosing the right database, splitting your services into manageable parts, or caching frequently accessed data, every decision you make early on will impact your ability to scale later. Keep learning, keep iterating, and don’t be afraid to make adjustments as you go.