Leveraging OpenStack and Sunbeam to Deploy a Sovereign AI Cloud

Overview

Discover how to build an enterprise-grade AI infrastructure using OpenStack, Kubernetes, and Kubeflow for orchestrating workloads on virtual machines, containers, and bare metal - all with open-source solutions.

Syllabus

• Introduction to OpenStack
Overview of Cloud Computing
Key Features and Components of OpenStack
OpenStack Architecture and Components
Setting up an OpenStack Environment
• Installing and Configuring OpenStack
Hardware and Software Requirements
Installation of OpenStack using DevStack
Configuring Keystone, Glance, Nova, Neutron, and other services
• Introduction to Kubernetes and Sunbeam
Kubernetes Fundamentals
Overview of Sunbeam and its Role in Kubernetes
Setting up a Kubernetes Cluster with Sunbeam
• Integrating Kubernetes with OpenStack
Using Kubernetes on OpenStack Infrastructure
Networking, Storage, and Compute Management with OpenStack and Kubernetes
Security and Access Control
• Introduction to Kubeflow
Overview of Kubeflow
Kubeflow Architecture and Components
Setting up Kubeflow on Kubernetes Infrastructure
• Deploying ML Workloads with Kubeflow
Managing Machine Learning Pipelines
Orchestrating Containers and Bare Metal Resources
Monitoring and Scaling AI Workloads
• Managing and Scaling AI Infrastructure
High Availability and Fault Tolerance
Best Practices for Resource Management
Tools for Monitoring and Logging in a Hybrid Environment
• Case Studies and Real-World Applications
Enterprise Use Cases of AI on OpenStack/Kubernetes
Success Stories and Lessons Learned
• Project: Building a Sovereign AI Cloud
Defining Project Goals and Requirements
Designing and Deploying the AI Infrastructure
Performance Analysis and Optimization
• Conclusion
Recap of Key Learnings
Future Trends in AI Cloud Infrastructure
Additional Resources and Further Learning Opportunities

Subjects

Programming