Module 4: Production Edge RAG at Scale

Overview

Deploy and operate Retrieval-Augmented Generation (RAG) systems at production scale on edge infrastructure within sovereign cloud environments. Master real-world deployment patterns, optimization techniques, and enterprise operations.

Duration: 10-12 hours
Learning Tracks: Both Sales & Technical
Prerequisites: Level 200 Edge RAG completion

Learning Objectives

Sales Track

  • ✅ Articulate production RAG use cases
  • ✅ Understand performance and cost trade-offs
  • ✅ Discuss enterprise SLA commitments
  • ✅ Position consulting and professional services

Technical Track

  • ✅ Design production RAG architectures
  • ✅ Optimize inference and retrieval performance
  • ✅ Implement MLOps for edge models
  • ✅ Manage knowledge bases at scale
  • ✅ Operate production RAG systems
  • ✅ Implement disaster recovery and failover

Core Topics

  1. Production Architecture → edge-rag-architecture-production.md
  2. Performance Optimization → edge-rag-optimization.md
  3. MLOps & Model Management → edge-rag-mlops.md
  4. Hands-On Lab → edge-rag-production-lab.md

Production Architecture

Performance Optimization

MLOps Workflow

Advanced Topics

Scaling Patterns

  • Multi-node inference
  • Distributed retrieval
  • Load balancing strategies
  • Horizontal scaling considerations

Knowledge Base Management

  • Ingestion pipelines
  • Vector embedding updates
  • Semantic search optimization
  • Knowledge graph integration

Enterprise Operations

  • SLA management
  • Performance monitoring
  • Cost tracking
  • Capacity planning
  1. Start: Production Architecture
  2. Optimize: Performance Tuning
  3. Automate: MLOps Pipeline
  4. Hands-On: Lab

Module Duration: 10-12 hours
Estimated Completion: 1.5-2 weeks @ 6 hrs/week