GenAI Factory | Episode 3: RAG with Cloud Run & Vector Search

Описание: In this episode, we explore how to implement Retrieval-Augmented Generation (RAG) on Google Cloud using Cloud Run, Vertex AI, and Vector Search.

🔑 What you’ll learn in this video:

How a Cloud Run job ingests sample movie data from Cloud Storage
How to generate text embeddings with Vertex AI
How embeddings are stored and searched in Vector Search
How a Cloud Run frontend leverages these embeddings to answer user queries in JSON format
Security and networking best practices with VPC, Load Balancers, and Cloud Armor

⚡ Architecture Highlights:

Ingestion subsystem with Cloud Run + Vertex Embeddings + Vector Search
Frontend subsystem with global/internal load balancers, managed certificates, Cloud Armor, and private VPC access
Fully secured and production-ready RAG pipeline
This setup allows you to build scalable, secure, and real-world RAG solutions on Google Cloud 🚀

👉 Don’t forget to check out Episode 1 & 2 of the GenAI Factory series for the complete journey!

#GenAI #CloudRun #VectorSearch #GoogleCloud #RAG #AI #sumitk #thecloudbaba 🚀 Kickstart Your Cloud Career in Just 8 Weeks!
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