In this 2-day workshop, participants will be deploying and securing AI workloads in an AI enterprise service provider environment. It covers Cisco AI PODs architecture for multi-tenant, AI-driven security strategies, and integration with Red Hat OpenShift AI for scalable and resilient AI operations. Students will gain hands-on experience in managing AI deployments while enhancing security and performance.
Learning Objectives:
- Understand Cisco AI PODs architecture and capabilities.
- Deploy AI-driven security and automation in service provider networks.
- Utilize Red Hat OpenShift AI for scalable AI/ML workloads.
- Implement AI-powered threat detection and defense.
- Integrate AI workflows into existing network infrastructures.
- Optimize network performance using AI-based insights.
- Configure and manage AI-driven service assurance.
- Leverage automation tools for AI/ML lifecycle management.
Course Outline
Introduction to Cisco AI & ML Infrastructure
Understanding Cisco AI PODs
Cisco AI Defense – Security in AI Deployments
Introduction to Red Hat OpenShift AI in Multi-tenant Environments
Cisco UCS C845A M8 Rack Server – The Next-Gen AI Server
AI Infrastructure Best Practices & Use Cases
Splunk Infrastructure and Application Performance Monitoring
Lab Outline
Deploying a Standard Cisco AI POD (Instructor Demo)
Deploying AI Models on Red Hat OpenShift AI
Implementing AI-Agents for Multi-tenant environments.
Implementing AI Defense Strategies
Securing AI Deployments
Day 2 Operations with Splunk Observability for Infrastructure and Applications
- Cloud Infrastructure Architects
- Networks Administrators
- Service providers
- Network Engineers
- AI/ML practitioners
- Security Professionals