Juicebox Deploy Integration
Overview
Deploy a containerized Juicebox AI analysis integration service with Docker. This skill covers building a production image that connects to the Juicebox API for managing datasets, running AI-powered analyses, and retrieving structured insights. Includes environment configuration for dataset access and analysis pipelines, health checks that verify API connectivity and dataset availability, and rolling update strategies for zero-downtime deployments serving real-time analysis results.
Docker Configuration
FROM node:20-slim AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY tsconfig.json ./
COPY src/ ./src/
RUN npm run build
FROM node:20-slim
RUN addgroup --system app && adduser --system --ingroup app app
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/node_modules ./node_modules
COPY package*.json ./
USER app
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=5s --retries=3 \
CMD curl -f http://localhost:3000/health || exit 1
CMD ["node", "dist/index.js"]
Environment Variables
export JUICEBOX_API_KEY="jb_live_xxxxxxxxxxxx"
export JUICEBOX_BASE_URL="https://api.juicebox.ai/v1"
export JUICEBOX_WORKSPACE_ID="ws_xxxxxxxxxxxx"
export LOG_LEVEL="info"
export PORT="3000"
export NODE_ENV="production"
Health Check Endpoint
import express from 'express';
const app = express();
app.get('/health', async (req, res) => {
try {
const response = await fetch(`${process.env.JUICEBOX_BASE_URL}/datasets`, {
headers: { 'Authorization': `Bearer ${process.env.JUICEBOX_API_KEY}` },
});
if (!response.ok) throw new Error(`Juicebox API returned ${response.status}`);
res.json({ status: 'healthy', service: 'juicebox-integration', timestamp: new Date().toISOString() });
} catch (error) {
res.status(503).json({ status: 'unhealthy', error: (error as Error).message });
}
});
