Deploying a GenAI app on Google Cloud | Code walkthrough

This video walks you through Google's jump start solution for deploying a GenAI app on Google Cloud.

It includes and explains some best practices:
- using Terraform from HashiCorp for infrastructure-as-code (IaC)
- using PostGreSQL as vector database
- use Gemini-Flash-2.0 (or any other) as LLM
- use serverless Cloud Run for deploying a scalable API - great service
- use Cloud Run Jobs to ingest data into the vector database.

Code: https://github.com/GoogleCloudPlatform/cloudsql-jump-start-solution-for-genai
Blog post "Vector databases are the wrong abstraction": https://www.timescale.com/blog/vector-databases-are-the-wrong-abstraction

Table of contents:
09:00: RAG
11:40: Cloud SQL, vector databases
15:40 gcloud SDK
16:15: Terraform, tfenv
22:05: Bootstrapping terraform
29:20: Using Claude.ai for debugging
33:45: Setting up all infrastructure
38:30: Discussing “Vector databases are the wrong abstraction”
53:55: Creating app images
54:55: Initializing the database
1:10:50: Loading the embeddings
1:23:05: Explaining the Chatbot API
1:36:05: Debugging embeddings job