The GPU cloud market is booming - but for NeoClouds and cloud service providers, explosive growth is quickly becoming a race to the bottom. In this episode, Edward Ionel of Mirantis breaks down why raw compute is no longer enough to sustain a profitable business, and what operators must do to protect their margins before the window closes.

Edward walks through the full monetization maturity model - from commoditized bare metal to a fully managed AI factory platforms capable of delivering 50%+ profit margins - and explains why evolving from selling compute to selling outcomes is no longer optional. If you're building or operating GPU infrastructure, this episode is a must-listen.

Reach out to Edward directly for a demo: eionel@mirantis.com

A full list of this episode's topics include:

1. Emerging GPU Cloud and AI Infrastructure opportunity
2. Evolution and challenges for NeoClouds
3. Transforming AI Services
4. GPU depreciation gap and market erosion
5. The 4 stages of GPU monetization
6. Building an AI Service platform
7. Building an AI Factory
8. A hyperscaler-like experience for AI
9. Real world case study

If you want to listen to more episodes of Radio Cloud Native, please visit https://www.mirantis.com/radiocloudnative/ to download, or find them wherever you prefer to consume your podcasts.

If you are interested in contributing to Radio Cloud Native, please reach out to our podcast team: podcasts@mirantis.com

In this month's episode Sr. Solution Architect at Mirantis, Zachary Fanelle, will walk you through the basics for getting started with gRPC and how to easily start integrating it into your Kubernetes workflows.

He will cover HTTP and REST APIs, as well as how these web technologies prompted Google to create gRPC in the first place. You will gain practical knowledge about what gPRC is, why it is leveraged by many developers in many use cases, and how it is supported in Kubernetes as of K8s version 1.24.

A full list of this episode's topics include:

1. What is gRPC?
2. Why leverage gRPC?
3. gRPC use cases
4. Drawbacks of gRPC
5. How to get started with gRPC

If you want to listen to more episodes of Radio Cloud Native, please visit https://www.mirantis.com/radiocloudnative/ to download, or find them wherever you prefer to consume your podcasts.

If you are interested in contributing to Radio Cloud Native, please reach out to our podcast team: podcasts@mirantis.com

In this month's installment, Sergey Goncharov, Sr. Product Manager for Mirantis Kubernetes Engine 4k (MKE 4k) is back to help you tackle the ever-emerging problem of Platform Engineering for complex multi-cluster, multi-cloud Kubernetes workloads. With the rise of AI/Ml, these are becoming more and more prevalent in enterprises around the world.

Overcoming this complexity requires a multi-cluster approach: designing clusters tailored to specific workloads with declarative services and policies, ensuring consistent lifecycle management (LCM), and scaling this strategy across your environments. By optimizing platforms for specific use cases (Kubernetes-based platforms that is), you can improve agility, streamline operations, boost workload availability, enhance security, and maintain compliance - without implementing a global multi-cluster architecture at smaller scales.

A full list of this episode's topics include:

• Challenges with Kubernetes complexity
• Multi-cluster thinking is key
• Building use case-optimzied platforms at scale
• Example open source tools for multi-cluster K8s

If you want to listen to more episodes of Radio Cloud Native, please visit https://www.mirantis.com/radiocloudnative/ to download, or find them wherever you prefer to consume your podcasts.

If you are interested in contributing to Radio Cloud Native, please reach out to our podcast team: podcasts@mirantis.com