[{"data":1,"prerenderedAt":707},["ShallowReactive",2],{"/en-us/blog/gitops-with-gitlab-auto-devops/":3,"navigation-en-us":37,"banner-en-us":454,"footer-en-us":469,"Viktor Nagy":679,"next-steps-en-us":692},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"seo":8,"content":16,"config":27,"_id":30,"_type":31,"title":32,"_source":33,"_file":34,"_stem":35,"_extension":36},"/en-us/blog/gitops-with-gitlab-auto-devops","blog",false,"",{"title":9,"description":10,"ogTitle":9,"ogDescription":10,"noIndex":6,"ogImage":11,"ogUrl":12,"ogSiteName":13,"ogType":14,"canonicalUrls":12,"schema":15},"Connecting Kubernetes clusters to GitLab with Auto DevOps","This is the 6th article in a series of tutorials on how to do GitOps with GitLab","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663397/Blog/Hero%20Images/logoforblogpost.jpg","https://about.gitlab.com/blog/gitops-with-gitlab-auto-devops","https://about.gitlab.com","article","\n                        {\n        \"@context\": \"https://schema.org\",\n        \"@type\": \"Article\",\n        \"headline\": \"GitOps with GitLab: Connecting GitLab with a Kubernetes cluster - Auto DevOps\",\n        \"author\": [{\"@type\":\"Person\",\"name\":\"Viktor Nagy\"}],\n        \"datePublished\": \"2022-02-08\",\n      }",{"title":17,"description":10,"authors":18,"heroImage":11,"date":20,"body":21,"category":22,"tags":23},"GitOps with GitLab: Connecting GitLab with a Kubernetes cluster - Auto DevOps",[19],"Viktor Nagy","2022-02-08","\n_It is possible to use GitLab as a best-in-class GitOps tool, and this blog post series is going to show you how. These easy-to-follow tutorials will focus on different user problems, including provisioning, managing a base infrastructure, and deploying various third-party or custom applications on top of them. You can find the entire \"Ultimate guide to GitOps with GitLab\" tutorial series [here](/blog/the-ultimate-guide-to-gitops-with-gitlab/)._\n\nIn this article we will look at how one can use Auto DevOps with all its bells and whistles to easily manage deployments.\n\n## Prerequisites\n\nThis article builds upon the previous tutorials in this series. We will assume that you have a Kubernetes cluster connected to GitLab using the GitLab Agent for Kubernetes, and you understand how the CI/CD tunnel works.\n\nIf this is not the case, I recommend to follow the previous articles to have a similar setup from where we will start today.\n\n## What is Auto DevOps\n\nAuto DevOps is GitLab's answer to the complexity of software application delivery. It is a set of opinionated templates that can be used \"as-is\" or can be used to fast-track your own pipeline building. For some setups it works from testing through various security and compliance checks to canary deployments. Even if you have a less supported setup, you should be able to reuse some of its components, from security linting to deployment.\n\nYou can read more about the various [features built into Auto DevOps in our documentation](https://docs.gitlab.com/ee/topics/autodevops/).\n\n## The plan for building and deploying a minimul application\n\nThe plan for this article is to build and deploy a minimal application. The focus will be on showing how you can get started quickly, without any modifications on the Auto Deploy pipelines.\n\nThis setup will use the already known CI/CD tunnel. There will be a separate article that shows how to replace the \"Auto Deploy\" part of Auto DevOps with GitOps style deployments.\n\nIn this article, we will deploy a simple hello world application. This is not a tutorial about Auto DevOps, so we will only focus on the setup needed when used together with the GitLab Agent for Kubernetes.\n\nYou can see the final repository under https://gitlab.com/gitlab-examples/ops/gitops-demo/hello-world-service/.\n\n## How to build the application\n\nIn this section we will create our super simple hello world application and put a Dockerfile beside it.\n\n1. Start a new project.\n1. Add `src/main.py` with the following content:\n    ```python\n    # From https://gist.github.com/davidbgk/b10113c3779b8388e96e6d0c44e03a74\n    import http.server\n    import socketserver\n    from http import HTTPStatus\n\n    class Handler(http.server.SimpleHTTPRequestHandler):\n        def do_GET(self):\n            self.send_response(HTTPStatus.OK)\n            self.end_headers()\n            self.wfile.write(b'Hello world')\n\n    httpd = socketserver.TCPServer(('', 5000), Handler)\n    httpd.serve_forever()\n    ```\n1. Create the `Dockerfile` with:\n   ```\n   FROM python:3.9.10-slim-bullseye\n\n   WORKDIR /app\n\n   COPY ./src .\n\n   EXPOSE 5000\n\n   CMD [ \"python\", \"main.py\" ]\n   ```\n1. Commit the change to the repository.\n\n## How to set up Auto DevOps\n\n1. [Share the CI/CD tunnel](https://docs.gitlab.com/ee/user/clusters/agent/work_with_agent.html) with the hello-world project. Note, that the Agent configuration project amd the application project should be in the same project hierarchy and the Agent configuration project needs to be higher in this hierarchy.\n    ```yaml\n    ci_access:\n      # This agent is accessible from CI jobs in projects in these groups\n      projects:\n        - id: \u003Cpath>/\u003Cto>/\u003Cyour>/\u003Cproject>\n    ```\n1. Find out the Kubernetes context name. The agent context name is `\u003Cnamespace>/\u003Cgroup>/\u003Cproject>:\u003Cagent-name>`. You can see the available contexts in CI with the following job:\n    ```yaml\n    contexts:\n      stage: .pre\n      image:\n        name: bitnami/kubectl:latest\n        entrypoint: [\"\"]\n      script:\n        - kubectl config get-contexts \n    ```\n1. Create your `.gitlab-ci.yml` file to have Auto DevOps working:\n    ```yaml\n    include:\n        template: Auto-DevOps.gitlab-ci.yml\n\n    variables:\n        # KUBE_INGRESS_BASE_DOMAIN is the application deployment domain and should be set as a variable at the group or project level.\n        KUBE_INGRESS_BASE_DOMAIN: 74.220.23.215.nip.io\n        KUBE_CONTEXT: \"gitlab-examples/ops/gitops-demo/k8s-agents:demo-agent\"\n        KUBE_NAMESPACE: \"demo-agent\"\n\n        # Feel free to enable any of these\n        TEST_DISABLED: \"true\"\n        CODE_QUALITY_DISABLED: \"true\"\n        LICENSE_MANAGEMENT_DISABLED: \"true\"\n        BROWSER_PERFORMANCE_DISABLED: \"true\"\n        LOAD_PERFORMANCE_DISABLED: \"true\"\n        SAST_DISABLED: \"true\"\n        SECRET_DETECTION_DISABLED: \"true\"\n        DEPENDENCY_SCANNING_DISABLED: \"true\"\n        CONTAINER_SCANNING_DISABLED: \"true\"\n        DAST_DISABLED: \"true\"\n        REVIEW_DISABLED: \"true\"\n        CODE_INTELLIGENCE_DISABLED: \"true\"\n        CLUSTER_IMAGE_SCANNING_DISABLED: \"true\"\n        POSTGRES_ENABLED: \"false\"\n    ```\n1. Commit the changes.\n\nAs you can see, I disabled many Auto DevOps functionalities in the above CI YAML. I did this for two reasons:\n\n1. Some of these features require a Premium or Ultimate license or tests in the repo. I wanted to keep this tutorial \"stable\" for everyone.\n1. Every use case differs a little bit and Auto DevOps allows a large number of customizations. I wanted to highlight this by showing you the most basic ones. Read more about [customizing Auto DevOps](https://docs.gitlab.com/ee/topics/autodevops/customize.html). If you would like [Review Apps](https://docs.gitlab.com/ee/ci/review_apps/) support, just remove the `REVIEW_DISABLED` line.\n\nThere are actually only three settings to get the Auto DevOps pipeline up and running:\n\n- The `KUBE_CONTEXT` specifies the context used for the connection, it's provided by the GitLab Agent for Kubernetes.\n- The `KUBE_NAMESPACE` specifies the Kubernetes namespace to target with the deployments. This namespace will be used as we apply the Helm charts used behind the hood.\n- The `KUBE_INGRESS_BASE_DOMAIN` sets up an Ingress and enables user friendly access to the deployed service. \n\n## Recap\n\nA very common setup I see with GitLab customers is that the development team is responsible for writing the application code and packaging it into a Docker container. During this process, they take care of basic testing as well, but they are not familiar with all the security and compliance requirements or the deployment pipelines used within the company. The presented setup and the Auto DevOps suite of templates serves these teams. 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