136 lines
4.9 KiB
YAML
136 lines
4.9 KiB
YAML
# Gitea Actions Workflow: Backend ECR Deployment
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# Place at: .gitea/workflows/backend-ecr.yaml (in repository root)
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name: Backend ECR Deployment
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on:
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push:
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branches: ['**']
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workflow_dispatch: {}
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permissions:
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contents: read
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packages: write
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env:
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# Build-time / workflow context
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BACKEND_DIR: workspace/sprint_1_2/CODEBASE/backend
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ECR_REGISTRY: public.ecr.aws
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ECR_REPOSITORY: ${{ vars.ECR_PUBLIC_REGISTRY_ALIAS }}/msk-cv-inference-server
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DOCKERFILE_PATH: deps/implementation/backend_deploy/Dockerfile
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# CV inference server runtime configuration
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# These are Gitea repository variables (or secrets) that are forwarded
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# to the container at deploy time. The Docker image itself does NOT bake
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# them in — the FastAPI app reads them from the environment via pydantic-settings.
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TRITON_ENDPOINT: ${{ vars.TRITON_ENDPOINT }}
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CV_INFERENCE_HOST: ${{ vars.CV_INFERENCE_HOST }}
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CV_INFERENCE_PORT: ${{ vars.CV_INFERENCE_PORT }}
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BASE_URL: ${{ vars.BASE_URL }}
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CORS_ORIGINS: ${{ vars.CORS_ORIGINS }}
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jobs:
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build-and-push:
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runs-on: ubuntu-latest
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container:
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image: gitea-modal-runner:latest
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timeout-minutes: 30
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Lint backend code
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run: |
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ls workspace/sprint_1_2/CODEBASE
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python -m py_compile workspace/sprint_1_2/CODEBASE/backend/cv_inference_server.py
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find backend -name '*.py' -exec python -m py_compile {} +
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# - name: Configure AWS credentials
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# uses: aws-actions/configure-aws-credentials@v4
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# with:
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# aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
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# aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
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# aws-region: us-east-1
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# - name: Login to Amazon ECR Public
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# id: login-ecr
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# uses: aws-actions/amazon-ecr-login@v2
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# with:
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# registry-type: public
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# mask-password: 'true'
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- name: Extract metadata for Docker
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id: meta
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uses: docker/metadata-action@v5
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with:
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# Full ECR Public image reference: public.ecr.aws/{alias}/{repo}
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images: ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}
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tags: |
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type=ref,event=branch
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type=sha,prefix=
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type=raw,value=latest,enable={{is_default_branch}}
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labels: |
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org.opencontainers.image.source=${{ github.server_url }}/${{ github.repository }}
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org.opencontainers.image.revision=${{ github.sha }}
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org.opencontainers.image.title=VKIST CV Inference Server
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- name: Build and push Docker image
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uses: docker/build-push-action@v5
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with:
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context: ./${{ env.BACKEND_DIR }}
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file: ./${{ env.DOCKERFILE_PATH }}
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push: true
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platforms: linux/amd64,linux/arm64
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha
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cache-to: type=gha,mode=max
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- name: Print image URI and digest
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run: |
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echo "Pushed ${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:${{ steps.meta.outputs.version }}"
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echo "Digest: ${{ steps.meta.outputs.tags }}"
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# trigger-triton:
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# needs: build-and-push
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# if: success() && github.event_name == 'push'
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# runs-on: ubuntu-latest
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# steps:
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# - name: Trigger Modal Triton deployment
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# uses: gitea/gitea-actions-workflow-trigger@v1
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# with:
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# repository: ${{ github.repository }}
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# workflow: trigger_modal_triton.yaml
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# ref: ${{ github.ref }}
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# inputs: '{}'
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notify-deploy:
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needs: build-and-push
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if: success() && github.event_name == 'push'
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runs-on: ubuntu-latest
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steps:
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- name: Trigger deployment webhook
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if: env.DEPLOY_WEBHOOK_URL != ''
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env:
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DEPLOY_WEBHOOK_URL: ${{ secrets.DEPLOY_WEBHOOK_URL }}
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WEBHOOK_SECRET: ${{ secrets.WEBHOOK_SECRET }}
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run: |
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cat <<EOF | curl -X POST "${DEPLOY_WEBHOOK_URL}" \
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-H "Content-Type: application/json" \
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-H "X-Gitea-Signature: sha256=$(echo -n '@-' | openssl dgst -sha256 -hmac "${WEBHOOK_SECRET}" | cut -d' ' -f2)" \
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-d @-
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{
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"service": "cv-inference-server",
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"image": "${{ env.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:${{ steps.meta.outputs.version }}",
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"env": {
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"TRITON_ENDPOINT": "${{ vars.TRITON_ENDPOINT }}",
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"CV_INFERENCE_HOST": "${{ vars.CV_INFERENCE_HOST }}",
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"CV_INFERENCE_PORT": "${{ vars.CV_INFERENCE_PORT }}",
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"BASE_URL": "${{ vars.BASE_URL }}",
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"CORS_ORIGINS": "${{ vars.CORS_ORIGINS }}",
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"ECR_PUBLIC_REGISTRY_ALIAS": "${{ vars.ECR_PUBLIC_REGISTRY_ALIAS }}"
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}
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}
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EOF
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