In this article we are sharing how to statically compile a crystal program and then share the executable inside a docker image. We will create the smallest docker image possible. Smaller images are easier to manage, distribute and boot.

Note: The way docker works, each command/line creates a layer (with context).

The good news about crystal lang is the they distribute the docker image with all the libraries so that we can build static compiled executable(s). Attaching the docker file I wrote to statically compile a crystal language program.

Note: The program uses the Kemal web framework, so this could also be considered an article on how to statically compile and distribute a kemal web app.

Docker is a popular tool to containerize and share images. Recently we ported a POS system into a docker image and had to share it with a client before we setup a private registry. This is how we share the image from my dev machine to clients local server.

Dev Machine: Kubuntu, 22.04

Developing and deploying to the cloud has become a mandatory requirement than a nice to have skill. The promise of the cloud is that it abstracts all the complexity of managing a server and you only pay for what you use. If you accept that at face value, then the cloud is 100% legit. You only pay for what you use (just the cost is high), and they do abstract the regular complexity, and create some new complexity to worry about. There is a reason why AWS offers certificate programs. AWS Certified Cloud Practitioner/Architect/SysOps Admin/Developer/Solution Architect/Dev Ops Engineer all these shouldn’t be there if all the complexity were truly abstracted.

Now that I have finished writing my frustration about cloud, lets return to the main topic of this article. Recently I was tasked with reducing our AWS bill. Our general approach to reduction in system performance have been to increase the server spec or DB spec. Looking at which resource was maxing out. DB or Server.

Docker has become a popular tool in recent years for building and deploying applications in a portable and scalable way. However, the build process can sometimes be slow, especially for large applications with many dependencies. In this article, we’ll explore how we can optimize our Dockerfile to speed it up.

When building a rails app for production we would need to do the following steps in the docker file

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COPY . .
bundle install
yarn install
bundle exec rails assets:precompile

Docker after building each step it will cache that step. If the instructions/context of that steps or steps before haven’t change then docker will use the cache.

So we need to make docker understand that there is no change, hence we can use the cache instead of rebuilding it.

Docker engine has inbuild API service that allows you to control & modify your docker engine and docker instance using HTTP.