This lab is currently in Beta, content may be updated as we refine the material
LABINTERMEDIATE

Deploy Vector Database on Kubernetes

Deploy Chroma vector database on Kubernetes with persistent storage. Configure collections and implement basic similarity search.

60 minutes
ai-infrastructure/rag
Deploy Vector Database on Kubernetes - Platform Engineering Hands-On Lab Icon

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

vector-databasechromakuberneteshelmembeddingssemantic-search

Part of a Course

This lab is part of the RAG Architectures and Vector Databases course

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