How to use Gitlab and Kubernetes to automate deployment

GitlabK8s automated deployment

With the popularity of cloud computing and containerization technology, enterprises are increasingly deploying applications on Kubernetes. In order to better manage applications in the Kubernetes environment, more and more enterprises choose to use the combination of Gitlab and Kubernetes to realize automatic construction, testing and deployment of containerized applications. This article will introduce how to use Gitlab and Kubernetes to implement automated deployment.

What is Gitlab?

GitLab is a Git repository-based web application used to store, manage, and collaborate on code between developers. GitLab provides a series of tools, such as code management, issue tracking, code review, construction, deployment and other tools, to facilitate developers for team collaboration and version control. The open source version of GitLab is free, while the enterprise version offers more features and support.

What is Kubernetes?

Kubernetes is an open source platform for containerized applications, initiated by Google and handed over to the management of the Cloud Native Computing Foundation (CNCF). Kubernetes provides a set of API interfaces for automating the deployment, scaling, and management of containerized applications. It supports multiple containerization platforms such as Docker and rkt, and can be used on various cloud platforms.

Benefits of GitlabK8s automated deployment

The benefits of using GitlabK8s automated deployment are:

1. Automate the build and deployment process and improve deployment efficiency.
2. Automated testing to increase deployment confidence.
3. Program version control and review to facilitate application maintenance.

Implementation of GitlabK8s automated deployment

Implementing GitlabK8s automated deployment requires the following steps:

1. Create a warehouse in GitLab to store application code.
2. Create a CI/CD configuration file (.gitlab-ci.yml) in GitLab for automated build, testing and deployment.
3. Configure GitLab Runner.
4. Create a namespace and a deployment in Kubernetes to store and run applications.
5. Configure a Kubernetes storage volume to store application data.

The following is a sample .gitlab-ci.yml file:

image: docker:latest

services:
  - docker:dind

stages:
  - build
  - test
  - deploy

variables:
  DOCKER_DRIVER: overlay2
  CONTAINER_TEST_IMAGE: registry.example.com/app-container:$CI_COMMIT_SHA
  CONTAINER_PROD_IMAGE: registry.example.com/app-container:latest

before_script:
  - docker info
  - docker login -u gitlab-ci-token -p $CI_JOB_TOKEN registry.example.com

build:
  stage: build
  script:
    - docker build -t $CONTAINER_TEST_IMAGE .
    - docker push $CONTAINER_TEST_IMAGE

test:
  stage: test
  script:
    - docker run --rm $CONTAINER_TEST_IMAGE npm test

deploy:
  stage: deploy
  script:
    - kubectl config set-cluster kubernetes --server=https://kubernetes.example.com
    - kubectl config set-credentials gitlab --token=$KUBE_TOKEN
    - kubectl config set-context default --cluster=kubernetes --user=gitlab
    - kubectl apply -f kubernetes/

In this example, we use the Docker image as the build and test environment, and use the built Docker The image is pushed to the private Docker image repository. Finally, use the kubectl command to apply the YAML file in Kubernetes to deploy the application.

Summary

Through GitlabK8s automated deployment, we can better manage applications on Kubernetes. Automated build, testing, and deployment increase deployment efficiency and confidence, and version control and review facilitate application maintenance. GitlabK8s automated deployment also provides flexible configuration that can be adjusted and optimized according to the actual situation of the enterprise.

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