jib VS pack

After digging a bit deeper, I realized something interesting. The project wasn’t using a Dockerfile at all. Instead, it was using Jib.

Inspired by .NET's native container support and tools like Jib (Java) and ko (Go), pycontainer-build provides a Python-native way to create OCI-compliant container images.

We use jib at work (https://github.com/GoogleContainerTools/jib) which also skips the Dockerfile and builds an image for a Java project directly.

This certainly looks like a much nicer experience than docker build, especially given that there can be a cache hit after a cache miss.

Official documentation: https://github.com/GoogleContainerTools/jib

GitHub - GoogleContainerTools/jib: 🏗 Build container images for your Java applications.

Worth to mention the benefits of using Jib Maven Plugin to build our Spring Boot applications images. Jib help us with image build optimization and customization.

You need to build Docker images for each app. This is specific to the JHipster application used in this tutorial which uses Jib to build the images. Make sure you are logged into Docker using docker login. Navigate to each app folder (store, invoice, product) and run the following command:

JIB

It is pretty easy to do with https://github.com/GoogleContainerTools/jib.

Cloud Run (GCR) -- the latest serverless platform; OCI-compliant containers (Docker, Buildpacks, etc.) Cloud Functions (GCF) -- originally serverless functions to compete with AWS Lambda; latest generation rebranded as Cloud Run Functions

I suspect that the GP was really asking "why not use a different tool", like buildah <https://buildah.io>, buildpacks <https://buildpacks.io>, nix <https://nix.dev/tutorials/nixos/building-and-running-docker-...>,

Broadly speaking, a buildpack takes application code and makes it runnable through a build process. So then, Cloud Native Buildpacks take your application source code and turn it into runnable, reproducible OCI images, implementing your requirements for image security, performance optimization, and container build order. It’s like having the exact Dockerfile you need — only you don’t need to write one.

The other way to run a containerized app on GCR is to not use Docker explicitly. If the Dockerfile is missing, Cloud Build uses Buildpacks, a tool built on open standards that automatically inspects application files and dynamically determines the best way to build & containerize apps. This is clearly the option for those new to Docker, don't know Docker, want to avoid Docker, or don't even think about containers. More specifically, Buildpacks adopted by Google is how images can be built & deployed on GCR without Docker.

What if I tell you that you can create a Docker image without creating a Dockerfile? We can build docker images directly from the Gralde or Maven plugin using Cloud Native Buildpacks. Some platforms (like Heroku or Cloud Foundry) use Buildpacks to convert provided jar files into runnable images.

Docker containers do not fit perfectly into ensuring the secure development of your AI project because they cannot track the model and data lifecycle. However, you can use other container-based technology tools like Buildpacks or KitOps to package your AI project and transform it into container images or open container initiative (OCI) artifacts.

Part of a platform engineering strategy is assembling a bunch of bricks to provide a well-rounded developer experience. In this article, I will explore how packaging applications using open-source Cloud Native Buildpacks can become a core element of that platform engineering toolkit by offering advanced application packaging features. Let's dive in!

For example, with BuildPacks developers don't even need to make a Dockerfile anymore. When integrated into a GitOps pipeline, serverless development becomes a breeze.