Title

AWS re:Invent 2023 - Scaling on AWS for the first 10 million users (ARC206)

Summary

• Skye Hart, a manager for solutions architecture at AWS, and Chris Munns, a startup lead and tech advisor, present best practices for scaling applications on AWS.
• The talk covers the importance of building applications with the intention to scale, focusing on customer satisfaction, resilience, and future-proofing.
• Key concepts include decoupling front-end and back-end, leveraging serverless technologies, and the importance of laying a strong foundation.
• AWS Amplify is highlighted for front-end hosting, offering ease of deployment and global distribution through CloudFront.
• For the back-end, a range of compute options are discussed, including EC2, containers (ECS, EKS, Fargate), and serverless (Lambda).
• The presenters recommend starting with SQL databases, specifically Amazon Aurora, for its scalability and managed services.
• As applications scale and potentially face issues, AWS CloudWatch and AWS X-Ray are recommended for monitoring and observability.
• Amazon DevOps Guru and Amazon CodeGuru are introduced as tools that use machine learning to provide insights and recommendations for infrastructure and code.
• The talk concludes with strategies for scaling beyond 10 million users, including database federation, caching, and breaking down monolithic applications into microservices.

Insights

• AWS emphasizes the importance of building applications with scalability in mind from the start, but acknowledges that no architecture is designed for high scalability on day one.
• Serverless technologies are increasingly important for rapid scaling and reducing the management of underlying infrastructure, allowing developers to focus on innovation.
• AWS Amplify is positioned as a simple and powerful technology for front-end hosting, with serverless benefits and built-in features for atomic deployments and feature branch deployments.
• The presenters advocate for starting with SQL databases due to their popularity, support, and alignment with many application data structures, but also recognize the use cases for NoSQL databases.
• Monitoring and observability tools like AWS CloudWatch and AWS X-Ray are critical for proactive management and understanding of application performance.
• Machine learning tools like Amazon DevOps Guru and Amazon CodeGuru can provide valuable insights and recommendations, leveraging AWS's experience and data models.
• As applications grow, strategies such as database federation, caching, and microservices architecture become necessary to continue scaling effectively.
• The talk suggests that while serverless is the most expensive way to buy compute on AWS, it offers a trade-off in terms of total cost of ownership and management simplicity that can be beneficial for a long time.
• The presenters highlight that AWS is constantly evolving, and what was considered advanced scaling techniques a decade ago may now be standard practice, emphasizing the need to stay updated with the latest AWS offerings and best practices.