fix(be) #639: OAuth로 가입할 때, 겹치지 않는 닉네임을 주입하여 가입되도록 변경 #86
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| name: be-cd | |
| on: | |
| push: | |
| branches: | |
| - release | |
| paths: | |
| - 'be/**' | |
| env: | |
| ROOT_PATH: ${{ github.workspace }}/be | |
| MAIN_RESOURCE_PATH: ${{ github.workspace }}/be/src/main/resources | |
| TEST_RESOURCE_PATH: ${{ github.workspace }}/be/src/test/resources | |
| jobs: | |
| be-cd: | |
| runs-on: ubuntu-latest | |
| steps: | |
| - name: 레포지토리를 체크아웃한다 | |
| uses: actions/checkout@v4 | |
| - name: 자바를 설치한다 | |
| uses: actions/setup-java@v3 | |
| with: | |
| distribution: 'corretto' | |
| java-version: '11' | |
| - name: 설정파일을 추가한다 | |
| run: | | |
| cd ${{ env.MAIN_RESOURCE_PATH }} | |
| echo "${{ secrets.APPLICATION_AWS_YML }}" > application-aws.yml | |
| echo "${{ secrets.APPLICATION_JWT_YML }}" > application-jwt.yml | |
| echo "${{ secrets.APPLICATION_OAUTH_YML }}" > application-oauth.yml | |
| - name: 어플리케이션을 빌드한다 | |
| run: | | |
| chmod +x gradlew | |
| ./gradlew build | |
| working-directory: ${{ env.ROOT_PATH }} | |
| - name: 도커 허브에 로그인한다 | |
| uses: docker/login-action@v2 | |
| with: | |
| username: ${{ secrets.DOCKER_HUB_USERNAME }} | |
| password: ${{ secrets.DOCKER_HUB_PASSWORD }} | |
| - name: 어플리케이션의 도커 이미지를 빌드하고 도커 허브에 푸시한다 | |
| uses: docker/build-push-action@v4 | |
| with: | |
| context: . | |
| file: ./Dockerfile.be | |
| push: true | |
| tags: ${{ secrets.BE_DOCKER_IMAGE_NAME }} | |
| - name: 어플리케이션을 배포한다 | |
| env: | |
| PRIVATE_KEY: ${{ secrets.EC2_SSH_PRIVATE_KEY }} | |
| HOST: ${{ secrets.HOST_ADDRESS }} | |
| USER: ${{ secrets.HOST_USERNAME }} | |
| TAG: ${{ secrets.BE_DOCKER_IMAGE_NAME }} | |
| run: | | |
| # Private key를 파일로 생성합니다. | |
| echo "$PRIVATE_KEY" > private_key.pem | |
| chmod 600 private_key.pem | |
| # EC2 인스턴스에 SSH로 접속하여 Docker 컨테이너를 관리합니다. | |
| ssh -o StrictHostKeyChecking=no -i private_key.pem $USER@$HOST " | |
| sudo docker compose -f docker-compose-be-app.yml down -v | |
| sudo docker compose -f docker-compose-be-app.yml pull | |
| sudo docker compose -f docker-compose-be-app.yml up -d | |
| sudo docker image prune -f | |
| " |