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Architecting the AI-Driven Node.js Backend: Building Scalable Infrastructure for Deep Learning Applications
Paperback
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ISBN13: 9798171850012
Publisher: Independently Published
Published: Sep 4 2026
Pages: 194
Weight: 0.76
Height: 0.41 Width: 7.00 Depth: 10.00
Language: English
Publisher: Independently Published
Published: Sep 4 2026
Pages: 194
Weight: 0.76
Height: 0.41 Width: 7.00 Depth: 10.00
Language: English
Your AI model may be powerful-but without the right backend, it cannot become a reliable production system.
Architecting the AI-Driven Node.js Backend is a practical guide for developers, software architects, and AI engineers who want to build scalable infrastructure for deep learning applications using Node.js.
Architecting the AI-Driven Node.js Backend is a practical guide for developers, software architects, and AI engineers who want to build scalable infrastructure for deep learning applications using Node.js.
Instead of treating AI as a standalone model, this book focuses on the backend architecture required to connect models with APIs, data pipelines, databases, asynchronous workflows, security systems, and production infrastructure.
Inside, you'll learn how to:
Inside, you'll learn how to:
- Design REST, GraphQL, and gRPC APIs for machine learning inference
- Build asynchronous AI workflows with Redis, BullMQ, and distributed workers
- Process high-volume data streams and optimize preprocessing with Node.js
- Connect Python-based AI models to Node.js through APIs, IPC, child processes, and WebAssembly
- Run inference directly with ONNX Runtime
- Scale AI backends using load balancing, auto-scaling, rate limiting, and stateless services
- Store vector embeddings, AI metadata, training data, and application state effectively
- Secure machine learning APIs with authentication, access control, encryption, and auditing
- Test and debug deep learning pipelines, memory leaks, and asynchronous bottlenecks
- Containerize and deploy Node.js AI services with Docker, CI/CD, and zero-downtime strategies
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