Scaling on AWS for the first 10 million users (ARC201)

Here is the summary of the video transcription in detail, formatted in Markdown with sections for better readability and single-level bullet points:

Key Takeaways

  • Building a scalable application requires a continuous cycle of building, measuring, and learning.
  • Start with a decoupled, managed architecture that can handle initial growth, then iterate and refactor as needed.
  • Leverage managed services and purpose-built tools to reduce operational overhead and focus on application development.
  • Observability and monitoring are crucial for understanding application performance and identifying bottlenecks.
  • Scale vertically, horizontally, and through caching to handle increasing user and data demands.
  • Eventually, transition to a microservices architecture and leverage event-driven communication patterns to support further growth.

Initial Architecture

  • Build a three-tier web application with a decoupled front-end and back-end.
  • Use Amplify Hosting for the front-end to leverage a serverless, managed service.
  • Utilize Amazon ECS with Fargate for the back-end to manage containers without worrying about infrastructure.
  • Choose Amazon Aurora Serverless v2 for the database, which can scale compute and storage independently.

Scaling to 10,000 Users

  • Implement observability and monitoring tools like CloudWatch and X-Ray to gain visibility into application performance.
  • Scale the database vertically by increasing the Aurora node size and horizontally by adding read replicas.
  • Use an RDS Proxy to manage the growing number of database connections.
  • Leverage Amazon ElastiCache to cache frequently accessed data and reduce load on the database.
  • Optimize the back-end by reducing slow database queries, profiling code, and leveraging caching.

Scaling to 1 Million Users

  • Continue scaling the database with more read replicas and leverage the database federation capabilities of Aurora.
  • Shift functionality to purpose-built databases like DynamoDB or time-series databases for specialized workloads.
  • Decouple the application into microservices based on data domains or business functions.
  • Introduce asynchronous communication patterns using services like Amazon SNS, SQS, EventBridge, and Kinesis.

Scaling to 10 Million Users

  • The architecture becomes highly customized and unique to the specific business requirements.
  • Continuously analyze and optimize the entire stack, focusing on performance and identifying areas for improvement.
  • Transition to self-managed compute services like Amazon EKS as the application complexity grows.
  • Implement extensive caching across all tiers of the application.

Conclusion

  1. The scalability capabilities of AWS services have improved significantly over the years, making it easier to build and scale applications.
  2. Leveraging managed services and reducing operational overhead are key to focusing on application development and innovation.
  3. Constant monitoring, observability, and a cycle of building, measuring, and learning are crucial for iterating and optimizing the architecture over time.

Your Digital Journey deserves a great story.

Build one with us.

Cookies Icon

These cookies are used to collect information about how you interact with this website and allow us to remember you. We use this information to improve and customize your browsing experience, as well as for analytics.

If you decline, your information won’t be tracked when you visit this website. A single cookie will be used in your browser to remember your preference.

Talk to us