openvscode-server VS serverless-application-model

If you’ve ever wanted the flexibility of running VS Code directly in your browser, now’s the time to give it a try. After experimenting with various solutions, I’ve found a standout option: openvscode-server by github.com/gitpod-io/openvscode-server – a fork of Microsoft’s VS Code.

> Yeah, sadly there are entry level laptops cheaper than a phone or said monitor plus a keyboard and mouse

Many people already have a monitor, mouse, and keyboard lying around. They'll also have a phone already. Plus, there are very cheap docks where you can just slide your phone into a laptop shell, priced similarly to the worst and most awful Chromebooks imaginable.

> So nothing works offline.

You can run a vscode server on your phone (https://github.com/gitpod-io/openvscode-server/releases). What's lacking is the VSCode GUI, so pointing a browser at http://[::1]:8080/ will work just fine.

This already exists!! https://www.gitpod.io/

The next part is the 'Public access' parameter which needs to be aligned with the DB Subnet Group configuration. When set to No, the provisioned ENI will only have Private IP. If you try to access it from the Internet, your PC or a cloud development environment such as Gitpod that would obviously not be accessible. However, if you set it to Yes, the ENI will also have a Public IP and a Public hostname (DNS endpoint). This settings can be changed without the need to re-provision the RDS which is quite handy.

https://www.gitpod.io/ does this

Not sure what .devcontainer means, but you can take a look to https://github.com/gitpod-io/openvscode-server or https://github.com/coder/code-server

I am using this project (https://github.com/gitpod-io/openvscode-server/) to run on my Linux box, then I can access it's server through my web browser.

We look forward to integrating more with Gitpod in the future! Check out the Gitpod homepage for more information and new development environment templates.

I suggest you check out https://www.gitpod.io, which does more general provisioning of GitOps clusters/Pods in their managed Kubernetes clusters. It's not specifically ML, but we've looked at it for POC ML projects that want basic hosting.

My first stop was AWS SAM (Serverless Application Model), which is AWS's official tool for local development. With SAM, you can invoke a Lambda function on your machine using sam local invoke, or even spin up a local API Gateway using sam local start-api. This means you can test API calls before deploying to AWS, which is super useful.

To expose your FastAPI endpoints using AWS API Gateway, you will use AWS Serverless Application Model (AWS SAM). AWS SAM simplifies the process of building and deploying serverless applications on AWS by providing a simplified syntax for defining AWS resources such as Lambda functions, API Gateway, IAM roles, and other related services, all within a template.yaml file.

AWS SAM GitHub Repository

This further enables you design your infrastructure visually, generate Infrastructure as Code and deploy it using AWS SAM (AWS Serverless Application Model) https://aws.amazon.com/serverless/sam/.

Right now I’m working on a project where REST API is built using AWS lambdas as request handlers. The whole thing uses AWS SAM to define lambdas, layers and connect it to Api Gateway in nice template.yaml file.

Container images (Dockerfiles), infrastructure as code with AWS CloudFormation, AWS Serverless Application Model (SAM), or HashiCorp Terraform can all be generated, updated, or optimized using AI-assisted tools.

When you use the AWS Serverless Application Model, you need to ensure that the resource definition does not result in multiple resources. (This will lead to multiple values being the same, which will break the rendering of the tree view.)

In my example I am using the Serverless Application Model (SAM) as my Infrastructure as Code tool. If you click on the links you can find more information about SAM and it's associated CLI (SAM CLI).

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.