genqlient VS flyctl

The client support in particular is currently very awkward. For instance, there's this discussion around Hasura in the Khan/genqlient repo: https://github.com/Khan/genqlient/issues/272

An example of a Snowflake API request using Go. This example uses the Go standard library, so it doesn’t require additional dependencies; however, in production, you could use a library like shurcooL/graphql or Khan/genqlient for stronger typing.

I also use https://github.com/Khan/genqlient in tandam with it to generate strongly typed graphql clients. Here is a decent example of a golang CLI using it: https://github.com/superfly/flyctl/tree/master/gql

You might also be interested in genqlient, which Khan Academy released earlier this year. It's closer to what you've done, though I don't think we support uploads because that isn't something we've needed to support.

If you want to just generate a client based on a schema, I highly recommend https://github.com/Khan/genqlient which we use at work.

Although it is supposedly not ready for production, I'm personally using https://github.com/Khan/genqlient from the Khan Academy folks.

To begin with, you could go with a Platform-as-a-Service (PaaS) provider like Heroku, or Fly for a more seamless experience. You can also do a bit of DevOps: set up a Docker installation on a VPS and deploy your app there.

To begin visit fly.io to create an account. Next install flyctl a command line tool for creating and deploying fly apps. macOS

For frontend deployment, I used Netlify (for the generous free package) and the recommended fly.io for server + database (also cheap package).

Create an account on Fly.io.

You can learn more about fly.io and tigris, we will need to create an account on both platforms for this project regardless. Anyway with the theory out of the way let's get started in the next section as we create our accounts and start building the app.

Fly.io is a platform that helps you run your apps and databases closer to your users all around the world. It takes your app code, packages it up neatly, and puts it on virtual machines that can be quickly started or stopped. This makes your app faster for users and more reliable. Fly.io is easy to use, works well for small projects or personal apps. It's a great way to make sure your app runs smoothly for people no matter where they are.

In this post, we'll start from scratch, running FerretDB locally via Docker, trying out the connection with mongosh and the MongoDB Node.js client, and finally deploy FerretDB to Fly.io for a production ready set up.

2- fly.io

Fly is a cloud platform that focuses on global edge computing. Fly specializes in high-performance hosting and provides a global network of edge locations. Fly is known for its scalability and performance optimizations.

But videototextai.com is built using NextJS + Firebase auth + Firestore and a backend deployed at fly.io . Fly makes it really easy to deploy docker containers and that is IMO the fastest way to develop, you can setup a local setup