kaniko VS dive

If all you need to do is build container, you can use https://github.com/GoogleContainerTools/kaniko

Kaniko for building the container images

kaniko

You should maybe look into Kaniko or use some other build tool

If you are using the docker socket just for building container images, you might want to look into kaniko. It doesn't use docker to build images. If you use the socket also for starting containers (we are actually doing that in our CI pipelines), you could think about limiting the pods Kubernetes schedules on a node (you can change the default of 110 using the kubelet config file).

Check out Kaniko for building containers https://github.com/GoogleContainerTools/kaniko . Only issue is it doesnt support windows containers.

It took less than 5 minutes to install. It quickly analysed the repo and identified easy ways to make the project more secure. Priya Wadhwa, Kaniko

I'd suggest to take a look at the Kaniko project, combined with custom container images in Lambda functions.

kaniko is a tool that allows you to build container images inside Kubernetes without the need for the Docker daemon. Effectively, it allows you to build Docker images without docker build.

Kubernetes prefers to pull containers from registries. You may be able to work around it by specifying a local image in your Kube manifest. Both https://github.com/GoogleContainerTools/kaniko and/ or https://www.devspace.sh/ may help.

Cool, gonna try this soon. Would be great to use in combination with Dive (https://github.com/wagoodman/dive)

Dive is an open-source tool that allows you to explore the various layers of a Docker image. It shows you the content of each layer and helps you identify voluminous or unnecessary parts.

Dive is a great tool for debugging this. I like image reduction work just because it gives me a chance to play with Dive: https://github.com/wagoodman/dive

One easy low hanging fruit I see a LOT for ballooning image sizes is people including the kitchen sink SDK/CLI for their cloud provider (like AWS or GCP), when they really only need 1/100 of that. The full versions of both of these tools are several hundred mb each

This post is going to be shorter. I'd like to highlight a tool that I really enjoy working with called "Dive" It is an essential tool when working to build and optimize docker containers.

Whether you work with Docker regularly or even create your own Docker containers, Dive is a great tool for streamlining image sizes, potentially helping you save storage costs and speed up deployments.