serverless-application-model VS sst

The complete solution with SAM is available here.

There are many options to deploy Serverless Applications in AWS and one of them is SAM, the Serverless Application Model. I chose to use it here, because it doesn't add too many layers of abstraction between what's being deployed and the code we write and our infrastructure is quite simple.

The solution uses AWS SAM with the global configuration for Lambda functions and the public API you can use to access Apache Zeppelin. The stack deployment provides the URL as an output value.

When you combine this with the AWS Serverless Application Model you can also very easily include your dependencies. Or use a compiled language like golang for your Lambda functions. You simply run sam build before you run the aws cloudformation package and aws cloudformation deploy commands. SAM will build the binary and update the template to point to the newly built binary. Package will then upload it to S3 and replace the local reference to the S3 location. Deploy can then create or update the stack or you can use the CloudFormation integration in CodePipeline.

I'm a big fan of using an Infrastructure as Code (IaC) approach for any project. My go to tools for this are the Servlerless Application Model (SAM) and it's associated CLI (SAM CLI). For more official use cases and for cross platform apps I typically use Terraform.

AWS SAM

Kicking off the tour and not starting a war, but I'm going to be using the Serverless Application Model.

The diagram here is super simple. I'm going to write something a little later that shows how this code could fit into a bigger workflow, but for now, I'm keeping it basic. And yes, that's the SAM Squirrel in there.

Interestingly, AWS CDK and SAM are both explicitly mentioned. While CDK broadly addresses Infrastructure as Code, SAM is highlighted for its role in developing serverless data pipelines - a hugely underrated concept.

Naturally, there are several options available to declare your cloud resources. The options with the most popularity are the CDK, AWS CloudFormation, SST, Serverless framework, Terraform, and AWS SAM. There are others, but when talking about Infrastructure as Code (IaC), these are the ones you hear about most often.

We see some great results from using these in conjunction with frameworks such as SST or Serverless, and also some real spaghetti from people who organically proliferate 100’s of functions over time and lose track of how they relate to each other or how to update them safely across time and service. Buyer beware!

> But if you have a sufficiently large enough API surface, doing one lambda per endpoint comes with a lot of pain as well. Packaging and deploying all of those artifacts can be very time consuming, especially if you have a naive approach that does a full rebuild/redeploy every time the pipeline runs.

Yeah, thankfully SST [0] does the heavy lifting for me. I've tried most of the solutions out there and SST was where I was the happiest. Right now I do 1 functions per endpoint. I structure my code like url paths mostly, 1 stack per final folder, so that the "users" folder maps to "/users/*" and inside I have get/getAll/create/update/delete files that map to GET X/id, GET X, POST X, POST X/id, DELETE/id. It works out well, it's easy to reason about, and deploys (a sizable a backend) in about 10min on GitHub Actions (which I'm going to swap out probably for something faster).

I agree with the secrets/permissions aspect and I like that it's stupid-simple for me to attach secrets/permissions at a low level if I want.

I use NodeJS and startup isn't horrible and once it's up the requests as very quick. For my needs, an the nature of the software I'm writing, lambda makes a ton of sense (mostly never used, but when it's used it's used heavily and needs to scale up high).

[0] https://sst.dev

We will start by building a project with SST that provisions an API Gateway, a Lambda, and an S3 bucket. Once implemented, we'll look into testing for concurrent write conflicts or exceeding capacity limits.

I recently deployed a node websocket server using the SST Service construct. Until this point my stack had been functions and buckets. While I had no users 😢, I also had no costs 🤡.

Most my personal and side-business projects have very spiky load or just low load in general. Because of that I love using AWS Lambda as my backend since it scales to 0 and scales to whatever you have your limits set at.

I use SST [0] for my backend with NodeJS (TypeScript) and Vue (Quasar) for my frontend. For my database I use either Postgres or DynamoDB if the fit is right (Single Table Design is really neat). For Postgres I like Neon [1] though their recent pricing changes make it less appealing.

[0] https://sst.dev

[1] https://neon.tech

Yup. Entire core business product for a succeeding startup, though it's a small team of contributors (<10), and a much smaller platform team. Serverless backend started in 2018. Been a blessing in many regards, but it has its warts (often related to how new this architecture is, and of course we've made our own mistakes along the way).

I really like the model of functions decoupled through events. Big fan of that. It's very flexible and iterative. Keep that as your focus and it's great. Be careful of duplicating config, look for ways to compose/reuse (duh, but definitely a lesson learnt) and same with CI, structure your project so it can use something off-the-shelf like serverless-compose. Definitely monorepo/monolith it, I'd be losing my mind with 100-150 repos/"microservices" with a team this size. If starting now I'd maybe look at SST framework[0] because redeploying every change during development gets old fast

I couldn't go back to any other way to be honest, for cloud-heavy backends at least. By far the most productive I've ever been

Definitely has its warts though, it's not all roses.

[0] http://sst.dev

Along the way, you find an excellent framework, SST. Which is much faster than CDK and provides a better DX1. Here is how you then define your MultiPipelineStack.

SST is a powerful framework that simplifies the development of serverless applications. It offers a straightforward and opinionated approach to defining serverless apps using TypeScript. Built on top of AWS CDK, SST handles the complexity of setting up your serverless infrastructure automatically. SST is an open-source framework and is completely free to use.

SST is an open-source framework designed to facilitate the development and deployment of Serverless stacks on AWS. It operates under the hood by integrating with Amazon CDK. However, its primary benefit is in allowing us to concentrate on creating resources using familiar languages like TypeScript, treating them as Infrastructure as Code (IaC).