serverless-graphql VS copilot-cli

Since then, the ecosystem has changed. Using the Serverless Framework makes deployment simpler. We released the managed Tracetest App making any serverless-based systems simpler to instrument and test. You can now test public-facing apps with no infra overhead!

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!

When we think about AWS serverless service, the first thing that comes to our mind is Lambda function. Yes, the quickest way to deploy this backend Express JS app to AWS is to deploy it as a Lambda function. The easiest way is using Serverless Framework.

Serverless Framework: https://www.serverless.com/

Github | Website

In this example, we're using the serverless framework to quickly set up the Lambda function along with an API gateway for the entry point. The lambda function is a simple Koa REST API with a few functional endpoints.

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.

1 - Serverless + AWS CDK + Lift: An integration that amps up the traditional Serverless Framework with Lift's static frontend construct and CDK's robust infra definition.

It's a bit easier in Python if you use tools like https://www.serverless.com/. I'm not sure if Rust has something similar yet.

Serverless

AWS Copilot CLI is an open source command line interface for running containers on AWS App Runner, Amazon Elastic Container Service (ECS), and AWS Fargate.

sudo curl -Lo /usr/local/bin/copilot https://github.com/aws/copilot-cli/releases/latest/download/copilot-linux && sudo chmod +x /usr/local/bin/copilot

Check out AWS Copilot CLI: https://aws.github.io/copilot-cli/

This is by far the best way to deploy compute into AWS in containerized workloads.

The abstraction you want is Jobs: ttps://aws.github.io/copilot-cli/docs/concepts/jobs/

Building this any other way on AWS would require provisioning multiple artifacts. The Copilot Jobs abstraction basically encapsulates the provisioning of those artifacts into one repeatable pattern.

AWS Copilot CLI is a tool that lets you deploy production-ready, scalable services on AWS from a Dockerfile in one command.

and here is the copilot page if you are interested https://aws.github.io/copilot-cli/

For larger high availability required things, AWS ECS with RDS, ElastiCache, CloudFront, S3, etc.. Really like Copilot for deployment/env/secret/sidecar management (probably needs a rename now): https://aws.github.io/copilot-cli/

We are spending about 60% less. Workload has actually lessened since AWS is so much more stable. Getting to a similar DX as Heroku was quite the lift, but once it's done, it's done. These days we generally only have outages when we screw something up ourselves. I recommend https://github.com/aws/copilot-cli for starting out on ECS.

I'd recommend checking out AWS Copilot (https://aws.github.io/copilot-cli/)