Innovators Weekly

Hello Reader,

I hope you're doing well! It's been a while, I have been building and executing some new plans. I'm glad you're still here, and I hope you enjoy our weekly spin-off writing on AI entrepreneurs on Substack. I would love to hear from you if you have anything in mind to share with me or anything you want me to cover in cloud-native and AI tech.

I'm also happy to share that we have opened our new Reddit community r/cvisiona! Join us from here if you're interested!

Everyone’s buzzing about AI… but behind every breakthrough, every lightning-fast response, every cloud-scaled model, there’s an invisible superhero doing the real heavy lifting. It’s Kubernetes.

You see, in 2025, ChatGPT hit 800 million weekly active users. When OpenAI handles billions of requests per day, Kubernetes silently spins up thousands of GPU pods during peak demand… and tears them down the moment traffic drops. No human babysitting.

The same thing happens in gaming. When millions of players simultaneously jump into Xbox Cloud Gaming, Kubernetes automatically scales services to ensure that no one experiences lag or downtime.

And here’s the part nobody talks about: today’s most innovative AI startups run their production workloads on Kubernetes.

So… what does Kubernetes have to do with AI?

When people imagine what’s behind AI, they picture massive data centers packed with powerful GPUs. That’s AI infrastructure, it's a combination of hardware and software stack built to train massive AI models.

But here’s the part most people missed: brutal AI infrastructure helps you train powerful AI models… but running and managing these models at a global scale is a completely different challenge. This is where Kubernetes comes into play! Btw if you're curious about how LLMs are actually trained, there’s a full video already on the channel, check it out if you’re interested.

Kubernetes automates the hardest parts of AI workloads: GPU scheduling at scale, workload orchestration, load-balancing inference traffic, autoscaling fleets of containers, and keeping distributed systems alive 24/7.

Remember when NVIDIA acquired Run.ai? That wasn’t random. Run.ai built a GPU orchestration layer on top of Kubernetes, letting teams dynamically allocate GPUs, schedule jobs, share resources, and squeeze maximum performance out of their compute. Click 'Read more' to read the remaining of article.

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We appreciate and are grateful for your continued support. Best wishes to you for all your new challenges this week. Have a wonderful day, and let's stay tuned!

Thanks, community! I look forward to embarking on this exciting journey with you! ​ Mélony Qin (aka. CloudMelon) - Founder @iMelonArt

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