So Your Startup Is Growing, Now What?

As your startup begins to gain traction and grow, the software that once served you well during your early stages now needs to evolve. This case study examines the journey of a startup facing the realities of scaling up. To respect confidentiality, we won’t name the company, but we’ll dive into their challenges and explore how they can transition their Ruby on Rails application to handle increased demand and complexity.

The Startup’s Initial Success

Think of your application like a car. When you were a student, you could get by with a small car that barely started but managed to take you where you needed to go. It was simple, functional, and got the job done. But as you grow up, start a family, and need to travel longer distances, you require something more secure and reliable, spacious enough to accommodate family members and luggage, and capable of taking you safely on longer trips. Similarly, the startup’s product, initially built using Ruby on Rails, was perfect for quickly developing an MVP (Minimum Viable Product) and gaining early market traction.

However, now that the startup is growing up, the application needs to grow up as well. It must handle more traffic, be more reliable to reduce support calls, and be easier to enhance with new features while keeping complexity and technical debt manageable. The initial simplicity that served the company well must evolve into a more sophisticated and scalable architecture.

Example of the Initial Code

Here’s a more complex example of what their initial code might look like, focusing on a PaymentsController that handles payment processing, database updates, success notifications, and subscription status updates:

class PaymentsController < ApplicationController
  def create
    @user = User.find(params[:user_id])
    @subscription = Subscription.find(params[:subscription_id])

    if process_payment
      @subscription.update(status: 'active', paid_at: Time.now)
      @user.notify_success("Your payment was successful and your subscription is now active.")
      render json: { message: 'Payment successful' }, status: :ok
    else
      render json: { error: 'Payment failed' }, status: :unprocessable_entity
    end
  end

  private

  def process_payment
    # Simulated payment processing logic
    payment_gateway.charge(@user, @subscription.amount)
  end

  def payment_gateway
    PaymentGateway.new(api_key: 'secret')
  end
end

In this example, the PaymentsController handles everything from processing payments to updating the subscription status and notifying the user of success. Unit tests for this controller would have been very complex due to the intertwined logic and dependencies, but (ironically) luckily, this problem hadn’t been tackled much throughout the codebase.

The Growing Pains

As the startup’s user base expanded, several issues began to surface:

1. Performance Bottlenecks:

• The monolithic structure struggled to handle increasing traffic, leading to slow response times and occasional downtime.

1. Scalability Issues:

• The tightly coupled code made it difficult to scale individual components. Scaling the entire application meant scaling everything, which was neither efficient nor cost-effective.

1. Maintainability Challenges:

• The heavy use of controllers for business logic made the codebase hard to maintain and prone to bugs. Each change risked breaking existing functionality.

1. Flexibility Limitations:

• Adding new features or modifying existing ones was cumbersome. The lack of modularity meant that even small changes could have wide-reaching impacts.

The Desired Future State

The company realized that to continue growing and meet their users’ demands, their software needed to evolve. They desired a system that was:

• More Stable: Capable of handling high traffic without frequent downtimes.
• Scalable: Able to scale specific components based on demand.
• Maintainable: Easier to manage and modify, reducing the risk of bugs.
• Flexible: Adaptable to new features and changes without extensive rewrites.

However, moving straight to a modular monolith wasn’t a likely approach. The company knew they wanted to eventually get there, but they also realized they had to reach this point in incremental steps to prevent service disruption. The first step would involve moving the logic to a service-like structure, where they had to think a lot about proper naming and namespacing of concepts. As a joke often shared among developers goes: “In computing, there are only two hard problems: invalidating cache and naming things.”

Transitioning to a Service-Oriented Structure

To begin the transition, the company started by refactoring their tightly coupled controllers into service objects. This step required careful consideration of naming and boundaries, akin to laying the foundation bricks before building a house.

Refactoring the Code

Here’s an example of how the PaymentsController can be refactored using service objects:

Initial Setup:

# app/controllers/payments_controller.rb
class PaymentsController < ApplicationController
  def create
    result = Payments::ProcessPayment.new(user_id: params[:user_id], subscription_id: params[:subscription_id]).call
    if result.success?
      render json: { message: 'Payment successful' }, status: :ok
    else
      render json: { error: 'Payment failed' }, status: :unprocessable_entity
    end
  end
end

Service Objects:

# app/services/payments/process_payment.rb
module Payments
  class ProcessPayment
    def initialize(user_id:, subscription_id:)
      @user = User.find(user_id)
      @subscription = Subscription.find(subscription_id)
    end

    def call
      if process_payment
        update_subscription
        notify_user
        OpenStruct.new(success?: true)
      else
        OpenStruct.new(success?: false)
      end
    end

    private

    def process_payment
      payment_gateway.charge(@user, @subscription.amount)
    end

    def payment_gateway
      PaymentGateway.new(api_key: 'secret')
    end

    def update_subscription
      @subscription.update(status: 'active', paid_at: Time.now)
    end

    def notify_user
      @user.notify_success("Your payment was successful and your subscription is now active.")
    end
  end
end

Future-Proofing with Microservices

Looking ahead, the startup aims to transition further into a microservices architecture. This approach will allow each module to evolve independently and scale according to its specific needs.

Benefits of Microservices:

• Independent Scaling: Scale services individually based on demand.
• Fault Isolation: Failures in one service do not affect others.
• Technology Diversity: Use different technologies best suited for each service.
• Faster Deployment: Deploy services independently, speeding up development cycles.

Steps to Transition:

1. Identify Microservice Candidates:

• Start with modules that have the highest impact or face the most issues.

1. Set Up Communication:

• Use APIs and messaging queues for communication between services.

1. Database Decoupling:

• Each microservice should manage its own data to avoid tight coupling.

1. Incremental Transition:

• Gradually transition modules to microservices, starting with less critical ones to minimize risk.

Conclusion

The journey from a monolithic MVP to a scalable microservices architecture is challenging but essential for growing startups. By first transitioning to a service-oriented structure, the company can improve maintainability and performance, setting a solid foundation for future growth. As the user base continues to expand, moving to microservices will provide the scalability, flexibility, and resilience needed to support long-term success.

This case study highlights the importance of evolving software architecture in tandem with business growth, ensuring that your startup is not only ready to handle current demands but is also prepared for future challenges. By taking incremental steps and focusing on proper design principles, you can build a robust, scalable system that supports your startup’s growth and success.