Building the Next Generation of AI Infrastructure: Enterprise-Grade Performance with Public Cloud and Open Source Technologies

Prologue....7

1. Long Live the AI Infrastructure....9

The Business Landscape Is Changing and AI Is King....10

You Are Feeling the Pressure (and You Are Not Alone)....12

The Multiple Ways of AI Infrastructure....13

At the End of the Day, Its All About Foundations....18

2. Compliance, Security, and Sustainability Are Not Optional Anymore....23

Everything You Need to Think About....24

Align Your Approach with the Pace of Innovation....24

Keep It as Pragmatic as Possible....24

Leverage and Make the Most of the Increasing Compliance Requirements....25

Treat Data as Your Most Valuable Asset....30

Use AI Infrastructure as an Opportunity to Connect Your Teams....30

Plan the Evolution in Sprints....33

Sustainability Requirements Will Become Even More Important....34

3. There Are Multiple Factors....35

Think in Terms of AI Lifecycle....35

Application-Level Considerations....38

Operating Systems for AI....39

Skilling to Expand Your Infrastructure....40

Exploring New Scenarios....40

Conclusion....42

About the Author....43

Choosing the right AI infrastructure has never been more complex. As AI adoption accelerates, leaders face growing pressure to innovate quickly while controlling costs, maintaining security, and meeting compliance requirements. AI workloads introduce new demands across the stack, forcing organizations to rethink long-standing assumptions about hardware, operating systems, cloud platforms, and applications. The report helps you navigate those decisions with clarity and confidence.

Written for technical and business architects, IT administrators, and executives responsible for infrastructure strategy, this report examines the trade-offs involved in supporting modern AI workloads. You'll explore how open source, public cloud, and the next-generation hardware fit into an overall AI infrastructure strategy, and how to evaluate options across performance, cost, flexibility, scalability, and risk. Rather than prescribing a single solution, the report provides a framework for making informed decisions that align technical choices with business priorities in regulated and security-sensitive environments.

• Understand the infrastructure challenges organizations face when adopting AI
• Evaluate trade-offs across hardware, platform, operating system, and applications
• Compare open source, cloud, and alternative technologies for AI workloads
• Balance cost, performance, security, and flexibility in infrastructure decisions
• Apply a practical framework for managing risk and reward in AI infrastructure planning