Deployment Options
Understand AWS Lambda deployment options and common design patterns for serverless applications. Learn key misconceptions about Lambda functions and how to organize your code effectively. This lesson equips you with practical insights into managing Lambda functions, optimizing resource use, and structuring applications around discrete jobs rather than solely functions.
We'll cover the following...
In the final chapter of this course, you’ll learn about common ways of structuring applications with Lambda functions.
Serverless architectures are still a relatively novel way of deploying applications, and it’s too early to talk about generally applicable design patterns or best practices. The community is still discovering how best to use this type of deployment architecture, and the platform is still frequently changing. There are, however, some good design practices worth considering when you are thinking about structuring applications with Lambda functions. As closing remarks for the course, I’d like to offer some ideas that helped us build and maintain MindMup efficiently. Hopefully, they will help you start thinking about organising your applications around Lambda functions in an effective way.
Think about jobs, not functions #
AWS Lambda quietly appeared on the scene in 2014, several years before ‘serverless’ became a buzzword. Back then, the DevOps community was trying to figure out the right relationship between applications, virtual machines and containers. Tool vendors were competing on how many times they could cram ‘micro-services’ into their ads. ‘Monolith’ became a dirty word. AWS product managers decided to introduce a new term and called their deployment units ‘functions’. It’s possible that they did this on purpose to signal a ...