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DCT Technology Pvt. Ltd.
DCT Technology Pvt. Ltd.

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Factory Pattern in Cloud Service Selection (AWS, GCP, Azure)

Choosing between AWS, GCP, and Azure can feel like picking a favorite child — and that’s a nightmare when you're building cloud-native applications.

But what if I told you there’s a design pattern that makes cloud service selection modular, testable, and flexible?

That’s the power of the Factory Design Pattern — and today, I’ll show you how it can make your cloud integrations smarter and your architecture cleaner. Whether you’re working on a multi-cloud setup or building platform-agnostic microservices, this pattern has your back.

Let’s dive in. 🛠️

🤔 The Problem: Hardcoding Cloud Providers

Many developers (and companies) fall into this trap:

if (provider === 'aws') {
  return new AWSStorageService();
} else if (provider === 'gcp') {
  return new GCPStorageService();
} else if (provider === 'azure') {
  return new AzureStorageService();
}
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This is fine… until it isn’t. What happens when:

  • A new provider gets added?
  • The constructor logic changes?
  • You want to write unit tests?

Your code becomes a maze of if-else or switch-case statements. That’s technical debt in disguise.


⚙️ The Solution: Abstract the Cloud Providers Using a Factory

Instead of hardcoding service creation, delegate it to a factory class that abstracts the logic. Here's a simple version in JavaScript:

class CloudServiceFactory {
  static getStorageService(provider) {
    switch (provider) {
      case 'aws':
        return new AWSStorageService();
      case 'gcp':
        return new GCPStorageService();
      case 'azure':
        return new AzureStorageService();
      default:
        throw new Error('Unsupported provider');
    }
  }
}
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Now you can just do:

const storage = CloudServiceFactory.getStorageService('gcp');
storage.uploadFile('my-file.txt');
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This is cleaner, more extensible, and makes testing a breeze.


🏗️ Real-World Use Case: Multi-Cloud File Upload Service

Imagine you’re building a platform that allows users to choose their cloud storage provider dynamically. Instead of duplicating logic, your architecture would look like this:

  1. User selects their preferred cloud provider.
  2. App calls the factory to get the appropriate service.
  3. Files are uploaded using the standard interface.

This approach ensures:

  • ✅ Better code maintainability
  • ✅ Easy unit testing with mocks/stubs
  • Extensibility for new providers like DigitalOcean, IBM Cloud, etc.

🧪 Bonus: Make It Testable

Because the implementation is decoupled, you can easily mock your cloud services during tests:

jest.mock('./AWSStorageService');
jest.mock('./GCPStorageService');

test('calls correct provider', () => {
  const service = CloudServiceFactory.getStorageService('aws');
  expect(service).toBeInstanceOf(AWSStorageService);
});
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This keeps your CI/CD pipeline fast and efficient — no need to actually connect to cloud APIs during tests.


🔍 Resources to Deepen Your Understanding


👨‍💻 Pro Tip: Combine with Strategy Pattern for Extra Power

Want to not only select cloud providers dynamically but also dynamically switch upload strategies like chunked uploads or encryption?

Use the Strategy Pattern with the Factory. Now you’re building systems like a software architect, not just a coder.


🔄 Final Thoughts

The Factory Pattern isn’t just for creating objects — it’s a blueprint for scalable decision-making in code.

When applied to cloud service selection, it:

  • Simplifies your architecture
  • Enables vendor flexibility
  • Reduces testing complexity
  • Future-proofs your application

💡 Don't hardcode cloud logic. Abstract it. Test it. Scale it.


👋 Like what you're reading?

👉 Follow [DCT Technology] for more dev patterns, cloud best practices, and real-world architecture tips.

Let’s build smarter, not harder. 💻🚀


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