One-Click Deployment of Spring Cloud Microservices Using Jenkins, Docker, and Kubernetes

The article demonstrates how to achieve one‑click deployment of a Spring Cloud microservice by leveraging Jenkins, Docker, and Kubernetes. The workflow consists of five main steps: developers push code to Git, Jenkins automatically pulls the code, Maven builds the project, the built JAR is packaged into a Docker image and pushed to a Docker registry, and the image is deployed or updated on a Kubernetes cluster.

1. Configure SSH‑KEY for Git access – Generate an ed25519 key pair with ssh-keygen -t ed25519 -C "[email protected]", add the public key to the Git platform (e.g., Gitee), and verify connectivity using ssh -T [email protected].

2. Create Jenkins pipeline – Define a pipeline job with a parameter for the Git branch. The pipeline script includes stages for pulling code, compiling with Maven, building the Docker image, and deploying to Kubernetes. Example snippet:

pipeline {
    agent any
    environment {
        REPOSITORY = "[email protected]:xxxxxx/cloud-demo.git"
        REPOSITORY_VERSION = "${params.BRANCH}"
    }
    stages {
        stage('拉代码') {
            steps {
                deleteDir()
                git branch: "${REPOSITORY_VERSION}", url: "${REPOSITORY}"
            }
        }
        // ... other stages ...
    }
}

3. Maven build – Install Maven on Jenkins, then run a series of mvn -U clean install commands across multiple modules (project, dependencies, common, test modules, etc.) within the 编译代码 stage.

4. Build and push Docker image – Prepare a directory containing build.sh, Dockerfile, and Spring Cloud configuration files. The build.sh script tags the image with the Git revision and timestamp, builds it with docker build, pushes it to the registry, and writes the full image name to an IMAGE file.

#!/usr/bin/env bash
REPOSITORY_VERSION=$1
GIT_REVISION=$(git log -1 --pretty=format:"%h")
TIME=$(date "+%Y.%m.%d.%H.%M")
IMAGE_NAME=192.168.31.100:5000/cloud-demo/cloud-demo-m-test-dubbo-service
IMAGE_TAG=${REPOSITORY_VERSION}-${GIT_REVISION}-${TIME}

docker build -t ${IMAGE_NAME}:${IMAGE_TAG} .

docker push ${IMAGE_NAME}:${IMAGE_TAG}

echo "${IMAGE_NAME}:${IMAGE_TAG}" > IMAGE

5. Kubernetes deployment – Create a cloud-demo-m-test-dubbo-service.yaml file defining a Deployment and a NodePort Service. The placeholder IMAGE_AND_TAG is replaced with the actual image name read from the IMAGE file during the 发布 stage, then applied with kubectl apply -f.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: cloud-demo-m-test-dubbo-service
spec:
  replicas: 1
  selector:
    matchLabels:
      app: cloud-demo-m-test-dubbo-service
  template:
    metadata:
      labels:
        app: cloud-demo-m-test-dubbo-service
    spec:
      containers:
      - name: cloud-demo-m-test-dubbo-service
        image: IMAGE_AND_TAG
        ports:
        - containerPort: 20881
---
apiVersion: v1
kind: Service
metadata:
  name: cloud-demo-m-test-dubbo-service
spec:
  type: NodePort
  ports:
  - port: 20881
    targetPort: 20881
  selector:
    app: cloud-demo-m-test-dubbo-service

After the pipeline runs, the image is available in the registry (e.g.,

cloud-demo/cloud-demo-m-test-dubbo-service:master-7012e1d-2023.05.01.10.16

) and the service is reachable via the assigned NodePort. The article concludes with a brief promotional note encouraging readers to follow the author.