So, in my opinion, everyone should be familiar with this project, especially if you are a Golang developer. Ko simplifies building container images also it securely does that by providing features such as not requiring any running daemon process, without the need for Dockerfile, providing build information for reproducibility, and creating/pushing SBOM (Software Bill of Materials) automatically, don’t worry if you are not familiar none of these, today, we’ll be explaining all of them in general, and also deploying Go applications on Kubernetes environments easily and quickly. Ko is a simple, fast container image builder for Go applications. So there is still a chance you can find something helpful in this article. Still, I suppose you are curious about automatic SBOM generation, a reproducible image builds, and multi-platform images. Since the ko project is specific to Golang, this article is for Golang developers mostly. I’m also super excited to talk about ko’s latest improvements in the supply chain security area.įirst, let’s explain which audience this article is targeting. In this article, we do not compare their strengths or weaknesses to each other, and we’ll be focusing on the ko project and will talk about its features from oldest to newest. To be honest, Docker is not the only way of creating container images, and there are many tools out there to achieve the same thing, such as Kaniko, apko, img, BuildKit, Buildx, Podman, Buildah, ko, Jib, Buildpacks and many more. Since containerization has become more and more popular with the help of Docker, I’m assuming you must have run the “ docker build” at least once. The first step you should do is create container images for your applications. If you are already familiar with containerization, I assume you are because the basic containerization knowledge is required for this article. By using this name in our clab file we can make use of this image in our lab.With the rise of containerization, it becomes essential to deploy applications as containers and manages them through orchestration systems at scale. Let's imagine that we have a private repository from which we pulled the image with a name /pub/vr-sros:20.10.R3. rename the image so it can be pushed to another repository.This can be needed for various purposes, but most common needs are: With a docker tag command it is possible to "rename" an image to something else. At the same time an image named myregistry.local/private/alpine:custom is already a fully qualified name and indicates the container registry ( myregistry.local) image repository name ( private/alpine) and its tag ( custom). A short form of alpine will be expanded by docker daemon to docker.io/alpine:latest. Tagging images #Ī container image name can appear in various forms. If in the example above, the image named myregistry.local/private/alpine:custom was not loaded to docker local image store before, containerlab will attempt to pull this image and will expect the private registry to be reachable.Ĭontainer images offer a great flexibility and reproducibility of lab builds, to embrace it fully, we wanted to capture some basic image management operations and workflows in this article. When containerlab launches a lab, it reads the image name from the topology file and expects to find the referenced images locally or by pulling them from the registry. Name : images topology : nodes : node1 : # image from docker hub registry with implicit `latest` tag image : alpine node2 : # image from docker hub with explicit tag image : ubuntu:20.04 node3 : # image from github registry image : ghcr.io/hellt/network-multitool node4 : # image from some private registry image : myregistry.local/private/alpine:custom Cumulus Linux (docker runtime) and Host.5-stage SR Linux based Clos fabric with config engine.Image management Image management Table of contents.
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