Criar um backend de gerenciamento de mídia escalável: integrando Node.js, Armazenamento de blobs Azure e MongoDB

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SAS_TOKEN="YOUR_SAS_TOKEN"
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ACCOUNT_NAME="YOUR_ACCOUNT_NAME"
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CONTAINER_NAME="YOUR_CONTAINER_NAME"

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MONGODB_URI="mongodb+srv://<user>:<password>@<cluster>.mongodb.net/"

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npm install --save @azure/storage-blob mongodb dotenv

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import http from 'http';
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import { BlobServiceClient } from '@azure/storage-blob';
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import { MongoClient } from 'mongodb';
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import 'dotenv/config';

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// Load in environment variables
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const mongodbUri = process.env.MONGODB_URI;
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const accountName = process.env.ACCOUNT_NAME;
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const sasToken = process.env.SAS_TOKEN;
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const containerName = process.env.CONTAINER_NAME;
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// Establishes a connection with Azure Blob Storage
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const blobServiceClient = new BlobServiceClient(`https://${accountName}.blob.core.windows.net/?${sasToken}`);
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const containerClient = blobServiceClient.getContainerClient(containerName);
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// Connect to MongoDB
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const client = new MongoClient(mongodbUri);
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client.connect();

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const server = http.createServer(handleImageUpload);
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const port = 3000;
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server.listen(port, () => {
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  console.log(`Server listening on port ${port}`);
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});

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async function handleImageUpload(req, res) {
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  res.setHeader('Content-Type', 'application/json');
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  if (req.url === '/api/upload' && req.method === 'POST') {
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    try {
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      // Extract metadata from headers
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      const {fileName, caption, fileType } = await extractMetadata(req.headers);
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      // Upload the image as a to Azure Storage Blob as a stream
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      const imageUrl = await uploadImageStreamed(fileName, req);
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      // Store the metadata in MongoDB
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      await storeMetadata(fileName, caption, fileType, imageUrl);
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      res.writeHead(201);
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      res.end(JSON.stringify({ message: 'Image uploaded and metadata stored successfully', imageUrl }));
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    } catch (error) {
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      console.error('Error:', error);
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      res.writeHead(500);
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      res.end(JSON.stringify({ error: 'Internal Server Error' }));
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    }
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  } else {
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    res.writeHead(404);
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    res.end(JSON.stringify({ error: 'Not Found' }));
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  }
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}

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async function extractMetadata(headers) {
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  const contentType = headers['content-type'];
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  const fileType = contentType.split('/')[1];
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  const contentDisposition = headers['content-disposition'] || '';
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  const caption = headers['x-image-caption'] || 'No caption provided';
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  const matches = /filename="([^"]+)"/i.exec(contentDisposition);
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  const fileName = matches?.[1] || `image-${Date.now()}.${fileType}`;
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  return { fileName, caption, fileType };
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}

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async function uploadImageStreamed(blobName, dataStream) {
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  const blobClient = containerClient.getBlockBlobClient(blobName);
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  await blobClient.uploadStream(dataStream);
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  return blobClient.url;
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}

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async function storeMetadata(name, caption, fileType, imageUrl) {
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  const collection = client.db("tutorial").collection('metadata');
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  await collection.insertOne({ name, caption, fileType, imageUrl });
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}

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curl -X POST \
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  -H "Content-Type: image/png" \
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  -H "Content-Disposition: attachment; filename=\"mongodb-is-webscale.png\"" \
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  -H "X-Image-Caption: Your Image Caption Here" \
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  --data-binary @"/path/to/your/mongodb-is-webscale.png" \
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  http://localhost:3000/api/upload