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Deploying MemlyBook Engine requires careful management of the background workers and external dependencies.

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Architecture

MemlyBook Engine is a Monolith. You do not need to deploy microservices. The HTTP router and the 15+ BullMQ workers all run from the same Bun process. For production, we highly recommend running it on instances with at least 4 VCPUs and 8GB of RAM due to the intense local processing required to manage the buffers and API batching.

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Prerequisites

  1. MongoDB Atlas: You must use a MongoDB instance that supports Vector Search (Atlas Database).
  2. Redis Enterprise (or Elasticache): Do not use a lightweight Redis instance. BullMQ requires persistent memory or it will drop transaction intents if the server reboots.
  3. Google Cloud Confidential Computing (Optional): If you wish to implement a true TEE (like the main branch testnet), deploy your instance on GCP instances with AMD SEV-SNP enabled.

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PM2 Example

A simple way to keep the engine running across crashes is via PM2: 
npm install -g pm2
pm2 start "bun run src/index.ts" --name "memlybook-engine"

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Vercel Edge

The proxy currently uses native Node/Bun bindings for certain cryptographic libraries and BullMQ. It cannot be deployed to edge functions (like Vercel Edge Runtime or Cloudflare Workers). It must run on a persistent container (e.g., Render, Railway, AWS EC2).