image-spec VS flyctl

A buildpack is a software, designed to transform application source code into executable (OCI) images that can run on a variety of cloud platforms. At its core, a buildpack is a directory that includes a specific file named buildpack.toml. This file contains metadata and configuration details that dictate how the buildpack should behave. Buildpacks in simple terms, is a set of standards defining how the different steps that are required to build a compliant container image can be automated. Using those standards, there are projects that have been built round enabling that using an CLI or an API. The most common way of doing that is through the Cloud Native Buildpacks' Pack project. Pack is a CLI command that can run in the same system the developers are using to actually go through creating a Dockerfile.

Eventually, once zstd support gets fully supported, and tiny gzip compression windows are not a limitation, then compressing a full layer would almost certainly have a better ratio over several smaller layers

https://github.com/opencontainers/image-spec/issues/803

Please note that label-schema has been superseded by https://github.com/opencontainers/image-spec/blob/main/annotations.md<^

GitHub Container Registry stores container images within your organization or personal account, and allows you to associate an image with a repository. It currently supports both the Docker Image Manifest V2, Schema 2 and Open Container Initiative (OCI) specifications.

We build all services as containerized workloads, i.e., OCI images - sometimes called Docker images. We deploy these to the Kubernetes product offered by the cloud vendor. Whenever we need some capability, containers are the answer. This insulates our applications from the vendor. In principle, we could switch providers as long as Kubernetes is available.

Build images with anything that makes OCI compliant images, push, and profit.

it's funny that you mention this because it is actually the thing that is next on my agenda for the image, as you can probably see already I bake in OCI image annotations in our image, which is great for including some core pieces of meta data. In addition to this though I will soon be including custom labels for Base64 encoded YAMLs for Kubernetes deployments using this image. I will look at including helm configuration as well. Then it should be just as easy as: $ docker pull registry.gitlab.com/crafty-controller/crafty-4:latest $ docker image inspect registry.gitlab.com/crafty-controller/crafty-4:latest | jq -r ".[].Config.Labels.\"org.arcadiatech.crafty.k8s.deployment\"" | base64 -d | kubectl apply -f -

They still don't do anything really of substance, they're just gateways to their vendor's world - booking systems, payment systems, etc. You learn those as you go along. Yes, as a potential employee, you need to be able to tick those boxes on your CV, but if you understand the underlying technology, it's mostly a matter of booking your own AWS or Azure server for $5-10 a month for a few weeks, and fooling around. (Docker is a bit different in the sense that they were the first to popularize today's de-facto container image standard, the "Docker container", which has since been accepted as a proper standard and renamed to "OCI image format"; but at the end of the day, at this point in time, Docker in itself is still just a company out for the money, and the multi-GB installation of their product can, for the essential functionality part, be replaced by a few hundred lines of Bash code. The cool boys today don't use Docker, they use [Podman(https://podman.io/), which is essentially a much more lightweight drop-in replacement ;-) )

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

Alternatives explored: * northflank: While running the wrk test, requests were taking 3-7 seconds. Couldn't repeat Heroku's phenomenon of "400ms-800ms" during such a load test. * fly.io: Reliability: It’s Not Great * render.com: I remember the time when indiehackers.com was down because of an outage on Render, not sure if it's worth trusting.