feat: implement Docker deployment plan with web, API, and ML services
This commit is contained in:
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# Docker Deployment Implementation Plan
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> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
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**Goal:** Add Docker, Docker Compose, and GitHub Actions deployment for the web, API, and ML services behind Traefik on the VPS.
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**Architecture:** Build three independent images: Vite static web served by Nginx, Bun/Elysia API, and FastAPI/Uvicorn ML service. Push all images to GHCR, then SSH to `/opt/ZeaVis-Edu` and run Docker Compose on the external Traefik network `app-shared-net`.
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**Tech Stack:** Docker, Docker Compose, GitHub Actions, GHCR, Traefik, Bun, Vite, Nginx, FastAPI, Uvicorn, TensorFlow.
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---
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## File structure
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- Create `.dockerignore`: keep Docker build contexts small and avoid copying local/generated artifacts into images.
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- Create `apps/web/Dockerfile`: build the Vite app with Bun and serve `dist` with Nginx on port `80`.
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- Create `apps/web/nginx.conf`: SPA fallback and optional `/api` reverse proxy to the public API domain for same-origin paths.
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- Create `apps/api/Dockerfile`: install Bun workspace dependencies and run `apps/api/src/index.ts` on port `3000`.
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- Create `apps/ml-service/Dockerfile`: install Python dependencies and run Uvicorn on port `8000`.
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- Create `docker-compose.yml`: define the three production services, Traefik labels, GHCR images, and `app-shared-net`.
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- Create `.github/workflows/deploy.yml`: build/push the three images and deploy them to the VPS.
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- Modify `.gitignore` only if needed after checking whether `.env` is already ignored.
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## Task 1: Add Docker ignore rules
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**Files:**
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- Create: `.dockerignore`
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- [ ] **Step 1: Create `.dockerignore`**
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Write this exact file:
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```dockerignore
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.git
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.github
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.claude
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.moon/cache
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node_modules
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**/node_modules
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bun.lock
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.env
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.env.*
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!.env.example
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Dockerfile
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docker-compose.yml
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Machine_Learning/dataset
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Machine_Learning/dataset.zip
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Machine_Learning/dataset_*.zip
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Machine_Learning/model
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Machine_Learning/best_model
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apps/web/dist
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apps/api/dist
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__pycache__
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*.pyc
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.pytest_cache
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.venv
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venv
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```
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- [ ] **Step 2: Verify ignore file exists**
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Run:
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```bash
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test -f .dockerignore && grep -q 'Machine_Learning/dataset' .dockerignore
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```
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Expected: command exits with status `0` and prints nothing.
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- [ ] **Step 3: Commit**
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```bash
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git add .dockerignore
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git commit -m "chore: add Docker ignore rules"
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```
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## Task 2: Add web Docker image
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**Files:**
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- Create: `apps/web/Dockerfile`
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- Create: `apps/web/nginx.conf`
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- [ ] **Step 1: Create `apps/web/nginx.conf`**
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Write this exact file:
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```nginx
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server {
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listen 80;
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server_name _;
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root /usr/share/nginx/html;
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index index.html;
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location /api/ {
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proxy_pass https://api.zeavisedu.asepharyana.tech/api/;
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proxy_set_header Host api.zeavisedu.asepharyana.tech;
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proxy_set_header X-Real-IP $remote_addr;
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proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
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proxy_set_header X-Forwarded-Proto $scheme;
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}
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location / {
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try_files $uri $uri/ /index.html;
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}
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}
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```
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- [ ] **Step 2: Create `apps/web/Dockerfile`**
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Write this exact file:
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```dockerfile
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FROM oven/bun:1 AS deps
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WORKDIR /app
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COPY package.json bun.lock ./
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COPY apps/web/package.json apps/web/package.json
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COPY packages/shared/package.json packages/shared/package.json
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RUN bun install --frozen-lockfile
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FROM oven/bun:1 AS builder
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WORKDIR /app
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COPY --from=deps /app/node_modules ./node_modules
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COPY --from=deps /app/apps/web/node_modules ./apps/web/node_modules
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COPY --from=deps /app/packages/shared/node_modules ./packages/shared/node_modules
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COPY package.json bun.lock ./
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COPY apps/web ./apps/web
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COPY packages/shared ./packages/shared
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WORKDIR /app/apps/web
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ENV VITE_API_BASE_URL=
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RUN bun run build
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FROM nginx:1.27-alpine AS runner
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COPY apps/web/nginx.conf /etc/nginx/conf.d/default.conf
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COPY --from=builder /app/apps/web/dist /usr/share/nginx/html
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EXPOSE 80
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CMD ["nginx", "-g", "daemon off;"]
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```
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- [ ] **Step 3: Build the web image locally**
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Run:
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```bash
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docker build -f apps/web/Dockerfile -t zeavis-web:test .
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```
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Expected: Docker build completes successfully and includes the `bun run build` step.
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- [ ] **Step 4: Commit**
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```bash
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git add apps/web/Dockerfile apps/web/nginx.conf
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git commit -m "feat: add web Docker image"
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```
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## Task 3: Add API Docker image
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**Files:**
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- Create: `apps/api/Dockerfile`
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- [ ] **Step 1: Create `apps/api/Dockerfile`**
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Write this exact file:
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```dockerfile
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FROM oven/bun:1 AS deps
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WORKDIR /app
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COPY package.json bun.lock ./
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COPY apps/api/package.json apps/api/package.json
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COPY packages/shared/package.json packages/shared/package.json
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RUN bun install --frozen-lockfile --production
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FROM oven/bun:1 AS runner
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WORKDIR /app
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ENV NODE_ENV=production
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ENV API_PORT=3000
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COPY --from=deps /app/node_modules ./node_modules
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COPY --from=deps /app/apps/api/node_modules ./apps/api/node_modules
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COPY --from=deps /app/packages/shared/node_modules ./packages/shared/node_modules
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COPY package.json bun.lock ./
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COPY apps/api ./apps/api
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COPY packages/shared ./packages/shared
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EXPOSE 3000
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CMD ["bun", "--env-file=.env", "apps/api/src/index.ts"]
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```
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- [ ] **Step 2: Build the API image locally**
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Run:
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```bash
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docker build -f apps/api/Dockerfile -t zeavis-api:test .
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```
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Expected: Docker build completes successfully.
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- [ ] **Step 3: Verify the API image starts far enough to read required env**
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Run:
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```bash
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docker run --rm -e DATABASE_URL=postgres://user:pass@example.com:5432/db -e SESSION_SECRET=abcdefghijklmnopqrstuvwxyz123456 -e WEB_APP_URL=https://zeavisedu.asepharyana.tech -e ML_SERVICE_URL=https://ml.zeavisedu.asepharyana.tech zeavis-api:test bun apps/api/src/index.ts
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```
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Expected: container starts and prints `ZeaVis Edu API running`. Stop it with `Ctrl+C` after seeing the log.
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- [ ] **Step 4: Commit**
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```bash
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git add apps/api/Dockerfile
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git commit -m "feat: add API Docker image"
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```
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## Task 4: Add ML service Docker image
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**Files:**
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- Create: `apps/ml-service/Dockerfile`
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- [ ] **Step 1: Create `apps/ml-service/Dockerfile`**
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Write this exact file:
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```dockerfile
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FROM python:3.11-slim AS runner
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WORKDIR /app
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ENV PYTHONUNBUFFERED=1
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ENV MODEL_PATH=/app/model/best_model.keras
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ENV MODEL_INPUT_SIZE=224
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends libgomp1 \
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&& rm -rf /var/lib/apt/lists/*
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COPY apps/ml-service/requirements.txt ./requirements.txt
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RUN pip install --no-cache-dir -r requirements.txt
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COPY apps/ml-service ./
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COPY Machine_Learning/best_model/best_model.keras /app/model/best_model.keras
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EXPOSE 8000
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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```
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- [ ] **Step 2: Check whether the model artifact exists locally**
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Run:
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```bash
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test -f Machine_Learning/best_model/best_model.keras
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```
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Expected: status `0`. If it fails, get the model artifact before building; this Dockerfile intentionally requires the production model to be present.
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- [ ] **Step 3: Build the ML image locally**
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Run:
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```bash
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docker build -f apps/ml-service/Dockerfile -t zeavis-ml:test .
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```
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Expected: Docker build completes successfully.
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- [ ] **Step 4: Verify the ML image health endpoint**
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Run:
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```bash
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docker run --rm -p 8000:8000 zeavis-ml:test
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```
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In another terminal, run:
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```bash
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curl -fsS http://localhost:8000/health
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```
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Expected: JSON response includes `"status":"ok"`. Stop the container with `Ctrl+C`.
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- [ ] **Step 5: Commit**
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```bash
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git add apps/ml-service/Dockerfile
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git commit -m "feat: add ML service Docker image"
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```
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## Task 5: Add production Docker Compose
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**Files:**
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- Create: `docker-compose.yml`
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- [ ] **Step 1: Create `docker-compose.yml`**
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Write this exact file:
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```yaml
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networks:
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app-shared-net:
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external: true
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name: app-shared-net
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services:
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web:
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image: ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/web:main
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container_name: zeavis-web
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restart: always
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networks:
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- app-shared-net
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env_file:
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- .env
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labels:
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traefik.enable: "true"
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traefik.http.routers.zeavis-web.rule: Host(`zeavisedu.asepharyana.tech`)
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traefik.http.routers.zeavis-web.entrypoints: websecure
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traefik.http.routers.zeavis-web.tls: "true"
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traefik.http.routers.zeavis-web.tls.certresolver: letsencrypt
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traefik.http.services.zeavis-web.loadbalancer.server.port: "80"
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api:
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image: ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/api:main
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container_name: zeavis-api
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restart: always
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networks:
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- app-shared-net
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env_file:
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- .env
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environment:
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NODE_ENV: production
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API_PORT: "3000"
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WEB_APP_URL: https://zeavisedu.asepharyana.tech
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ML_SERVICE_URL: https://ml.zeavisedu.asepharyana.tech
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labels:
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traefik.enable: "true"
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traefik.http.routers.zeavis-api.rule: Host(`api.zeavisedu.asepharyana.tech`)
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traefik.http.routers.zeavis-api.entrypoints: websecure
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traefik.http.routers.zeavis-api.tls: "true"
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traefik.http.routers.zeavis-api.tls.certresolver: letsencrypt
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traefik.http.services.zeavis-api.loadbalancer.server.port: "3000"
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ml:
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image: ghcr.io/${GITHUB_REPOSITORY:-mytheclipse/zeavis-edu}/ml:main
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container_name: zeavis-ml
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restart: always
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networks:
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- app-shared-net
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env_file:
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- .env
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environment:
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MODEL_PATH: /app/model/best_model.keras
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MODEL_INPUT_SIZE: "224"
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labels:
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traefik.enable: "true"
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traefik.http.routers.zeavis-ml.rule: Host(`ml.zeavisedu.asepharyana.tech`)
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traefik.http.routers.zeavis-ml.entrypoints: websecure
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traefik.http.routers.zeavis-ml.tls: "true"
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traefik.http.routers.zeavis-ml.tls.certresolver: letsencrypt
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traefik.http.services.zeavis-ml.loadbalancer.server.port: "8000"
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```
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- [ ] **Step 2: Validate compose syntax**
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Run:
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```bash
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GITHUB_REPOSITORY=mytheclipse/zeavis-edu docker compose config >/tmp/zeavis-compose.yml
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```
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Expected: command exits with status `0`.
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- [ ] **Step 3: Commit**
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```bash
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git add docker-compose.yml
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git commit -m "feat: add production Docker Compose"
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```
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## Task 6: Add GitHub Actions deploy workflow
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**Files:**
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- Create: `.github/workflows/deploy.yml`
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- [ ] **Step 1: Create `.github/workflows/deploy.yml`**
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Write this exact file:
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```yaml
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name: Build and Deploy
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on:
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push:
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branches:
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- main
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workflow_dispatch:
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env:
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REGISTRY: ghcr.io
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IMAGE_PREFIX: ghcr.io/${{ github.repository }}
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jobs:
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build:
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runs-on: ubuntu-latest
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permissions:
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contents: read
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packages: write
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strategy:
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fail-fast: false
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matrix:
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service:
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- name: web
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dockerfile: apps/web/Dockerfile
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- name: api
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dockerfile: apps/api/Dockerfile
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- name: ml
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dockerfile: apps/ml-service/Dockerfile
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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: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Log in to GHCR
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uses: docker/login-action@v3
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Extract metadata
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: ${{ env.IMAGE_PREFIX }}/${{ matrix.service.name }}
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tags: |
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type=ref,event=branch
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type=sha
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- name: Build and push image
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uses: docker/build-push-action@v5
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with:
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context: .
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file: ${{ matrix.service.dockerfile }}
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push: true
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha,scope=${{ matrix.service.name }}
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cache-to: type=gha,mode=max,scope=${{ matrix.service.name }}
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deploy:
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needs: build
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runs-on: ubuntu-latest
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if: github.ref == 'refs/heads/main'
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permissions:
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contents: read
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packages: read
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steps:
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- name: Deploy to VPS
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uses: appleboy/ssh-action@master
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with:
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host: ${{ secrets.VPS_HOST }}
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username: ${{ secrets.VPS_USER }}
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key: ${{ secrets.VPS_SSH_KEY }}
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port: ${{ secrets.VPS_PORT || 22 }}
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script: |
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set -e
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cd /opt/ZeaVis-Edu
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git pull origin main
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cat > .env << 'ENVEOF'
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GITHUB_REPOSITORY=${{ github.repository }}
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DATABASE_URL=${{ secrets.DATABASE_URL }}
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SESSION_SECRET=${{ secrets.SESSION_SECRET }}
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WEB_APP_URL=https://zeavisedu.asepharyana.tech
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ML_SERVICE_URL=https://ml.zeavisedu.asepharyana.tech
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ENVEOF
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docker login ghcr.io -u ${{ github.actor }} -p ${{ secrets.GITHUB_TOKEN }}
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docker network create app-shared-net 2>/dev/null || true
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docker compose pull
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docker compose up -d
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docker compose ps
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docker compose ps | grep -q "zeavis-web.*Up" || exit 1
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docker compose ps | grep -q "zeavis-api.*Up" || exit 1
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docker compose ps | grep -q "zeavis-ml.*Up" || exit 1
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```
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||||
- [ ] **Step 2: Validate workflow YAML exists and has all services**
|
||||
|
||||
Run:
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|
||||
```bash
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grep -q 'apps/web/Dockerfile' .github/workflows/deploy.yml && grep -q 'apps/api/Dockerfile' .github/workflows/deploy.yml && grep -q 'apps/ml-service/Dockerfile' .github/workflows/deploy.yml
|
||||
```
|
||||
|
||||
Expected: command exits with status `0` and prints nothing.
|
||||
|
||||
- [ ] **Step 3: Commit**
|
||||
|
||||
```bash
|
||||
git add .github/workflows/deploy.yml
|
||||
git commit -m "ci: deploy Docker images to VPS"
|
||||
```
|
||||
|
||||
## Task 7: Run final local verification
|
||||
|
||||
**Files:**
|
||||
- Verify all files from previous tasks.
|
||||
|
||||
- [ ] **Step 1: Run typecheck**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
bun run typecheck
|
||||
```
|
||||
|
||||
Expected: command exits with status `0`.
|
||||
|
||||
- [ ] **Step 2: Build all Docker images**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
docker build -f apps/web/Dockerfile -t zeavis-web:test . && docker build -f apps/api/Dockerfile -t zeavis-api:test . && docker build -f apps/ml-service/Dockerfile -t zeavis-ml:test .
|
||||
```
|
||||
|
||||
Expected: all three Docker builds complete successfully.
|
||||
|
||||
- [ ] **Step 3: Validate compose config**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
GITHUB_REPOSITORY=mytheclipse/zeavis-edu docker compose config >/tmp/zeavis-compose.yml
|
||||
```
|
||||
|
||||
Expected: command exits with status `0`.
|
||||
|
||||
- [ ] **Step 4: Check final git status**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
git status --short
|
||||
```
|
||||
|
||||
Expected: no uncommitted changes.
|
||||
|
||||
## Task 8: Configure GitHub secrets and trigger deploy
|
||||
|
||||
**Files:**
|
||||
- No repo file changes.
|
||||
|
||||
- [ ] **Step 1: Confirm required secrets exist**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
gh secret list
|
||||
```
|
||||
|
||||
Expected: output includes `VPS_HOST`, `VPS_USER`, `VPS_PORT`, `VPS_SSH_KEY`, `DATABASE_URL`, and `SESSION_SECRET`.
|
||||
|
||||
- [ ] **Step 2: Add missing secrets if needed**
|
||||
|
||||
Use these commands only for missing secrets:
|
||||
|
||||
```bash
|
||||
gh secret set VPS_HOST --body "<vps-host>"
|
||||
gh secret set VPS_USER --body "root"
|
||||
gh secret set VPS_PORT --body "22"
|
||||
gh secret set VPS_SSH_KEY < ~/.ssh/id_ed25519
|
||||
gh secret set DATABASE_URL --body "<production-database-url>"
|
||||
gh secret set SESSION_SECRET --body "<at-least-32-character-secret>"
|
||||
```
|
||||
|
||||
Expected: `gh secret list` shows all required secret names. Replace angle-bracket values with the real production values before running.
|
||||
|
||||
- [ ] **Step 3: Push commits to main**
|
||||
|
||||
Run only after the user approves pushing:
|
||||
|
||||
```bash
|
||||
git push origin main
|
||||
```
|
||||
|
||||
Expected: push succeeds and GitHub Actions starts the `Build and Deploy` workflow.
|
||||
|
||||
## Task 9: Verify production deployment
|
||||
|
||||
**Files:**
|
||||
- No repo file changes.
|
||||
|
||||
- [ ] **Step 1: Check workflow status**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
gh run list --workflow deploy.yml --limit 1
|
||||
```
|
||||
|
||||
Expected: latest run eventually shows `completed` and `success`.
|
||||
|
||||
- [ ] **Step 2: Check VPS containers**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
ssh <vps-user>@<vps-host> "cd /opt/ZeaVis-Edu && docker compose ps"
|
||||
```
|
||||
|
||||
Expected: `zeavis-web`, `zeavis-api`, and `zeavis-ml` show `Up`.
|
||||
|
||||
- [ ] **Step 3: Check service logs**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
ssh <vps-user>@<vps-host> "docker logs --tail 100 zeavis-web && docker logs --tail 100 zeavis-api && docker logs --tail 100 zeavis-ml"
|
||||
```
|
||||
|
||||
Expected: no startup crash loops or missing required environment errors.
|
||||
|
||||
- [ ] **Step 4: Check public domains**
|
||||
|
||||
Run:
|
||||
|
||||
```bash
|
||||
curl -I https://zeavisedu.asepharyana.tech/
|
||||
curl -I https://api.zeavisedu.asepharyana.tech/health
|
||||
curl -I https://ml.zeavisedu.asepharyana.tech/health
|
||||
```
|
||||
|
||||
Expected: frontend does not return Traefik `404 page not found`; API and ML health endpoints return an expected application response.
|
||||
Reference in New Issue
Block a user