Building a Cloud-Native Animation Platform - Architecture Decisions for Scale

Dec 20, 2024

Building a platform from scratch presents a unique opportunity: you can choose the right architecture from day one. When we worked on a cloud-native animation platform, we designed it to scale from the start.

The Vision

Create a platform that could handle complex animation workflows, integrate with AI services, and scale automatically based on demand—all while maintaining cost efficiency and developer productivity.

Architecture Decisions

Frontend: Angular with State Management

We chose Angular with NgRx for complex state management. This allowed us to build reactive user interfaces that could handle real-time updates and complex animations efficiently.

Backend: NestJS Microservices

NestJS provided the perfect foundation for building scalable microservices. Its modular architecture and TypeScript-first approach ensured type safety and maintainability across the entire backend.

Serverless Integrations

Leveraging AWS Lambda, we built serverless functions for:

  • Image processing and optimization
  • AI model integrations
  • Background job processing

This approach reduced operational overhead while maintaining scalability.

Cloud Infrastructure

We built on AWS:

  • Cognito for authentication and user management
  • S3 for scalable object storage
  • Neptune for graph database needs
  • CloudFront for global content delivery
  • Route53 for DNS management

Infrastructure as Code

All infrastructure was defined in Terraform, ensuring:

  • Version-controlled infrastructure changes
  • Reproducible environments
  • Cost visibility and optimization

CI/CD Excellence

GitHub Actions pipelines automated:

  • Testing (Jest for unit and integration tests)
  • Building and containerization
  • Deployment to multiple environments
  • Security scanning

Special Challenges

Media Processing

Working with video and animation files required efficient processing. We integrated FFMPEG for video manipulation and implemented streaming uploads to handle large files without timeouts.

AI Integration

Integrating OpenAI API and Azure ML Studio services required careful API design and error handling. We built resilient integration layers that could handle API rate limits and failures gracefully.

Results

The platform successfully:

  • Handles complex animation workflows at scale
  • Processes media files efficiently
  • Integrates seamlessly with AI services
  • Scales automatically based on demand
  • Maintains high developer velocity

Key Takeaways

Cloud-native architecture isn’t just about using cloud services—it’s about building systems that leverage the cloud’s strengths: scalability, managed services, and pay-as-you-go pricing.

By choosing the right technologies from the start and investing in infrastructure as code and CI/CD, we created a platform that could grow with the business without requiring constant refactoring.

Building a new platform? TechTrail helps you make the right architecture decisions from day one. Contact us to discuss your project.