Deploy Vector Database on Kubernetes
Deploy Chroma vector database on Kubernetes with persistent storage. Configure collections and implement basic similarity search.
Lab Overview
🛠Lab from the AI Platform Engineering Bootcamp. Used in Week 3. Bootcamp landing page: https://academy.tekanaid.com/bootcamps/ai-platform-engineering-bootcamp Parent course(s):
- Week 3: RAG Architectures and Vector Databases (slug: rag-architectures-103)
🟡 Beta bootcamp lab. Hands-on instructions, check scripts, and solve scripts are in place. Lab is part of the running Platform Assistant capstone arc that grows across all 8 weeks of the bootcamp.
This hands-on lab teaches you to deploy and operate Chroma vector database on Kubernetes.
You'll learn to:
- Deploy Chroma using Helm with persistent storage
- Create collections and verify CRUD operations
- Implement basic similarity search with sample documents
- Configure health checks and resource monitoring
This lab establishes the vector database foundation for your RAG system.
What You'll Learn
Deploy Chroma vector database on Kubernetes with persistent storage
Create collections and perform CRUD operations on vector data
Implement semantic similarity search with metadata filtering
Configure health monitoring and resource tracking for Chroma
Prerequisites
kubernetes-fundamentals
helm-basics
embeddings-concepts
Technologies Covered
Part of a Course
This lab is part of the RAG Architectures and Vector Databases course
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