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Google Cloud Therapist on Bringing AI to Cloud Native Infrastructure

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Manage episode 481361748 series 75006
Content provided by The New Stack Podcast and The New Stack. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The New Stack Podcast and The New Stack or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

At Google Cloud Next, Bobby Allen, Group Product Manager for Google Kubernetes Engine (GKE), emphasized GKE’s foundational role in supporting AI platforms. While AI dominates current tech conversations, Allen highlighted that cloud-native infrastructure like Kubernetes is what enables AI workloads to function efficiently. GKE powers key Google services like Vertex AI and is trusted by organizations including DeepMind, gaming companies, and healthcare providers for AI model training and inference.

Allen explained that GKE offers scalability, elasticity, and support for AI-specific hardware like GPUs and TPUs, making it ideal for modern workloads. He noted that Kubernetes was built with capabilities—like high availability and secure orchestration—that are now essential for AI deployment. Looking forward, GKE aims to evolve into a model router, allowing developers to access the right AI model based on function, not vendor, streamlining the development experience. Allen described GKE as offering maximum control with minimal technical debt, future-proofed by Google’s continued investment in open source and scalable architecture.

Learn more from The New Stack about the latest insights with Google Cloud:

Google Kubernetes Engine Customized for Faster AI Work

KubeCon Europe: How Google Will Evolve Kubernetes in the AI Era

Apache Ray Finds a Home on the Google Kubernetes Engine

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

895 episodes

Artwork
iconShare
 
Manage episode 481361748 series 75006
Content provided by The New Stack Podcast and The New Stack. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The New Stack Podcast and The New Stack or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

At Google Cloud Next, Bobby Allen, Group Product Manager for Google Kubernetes Engine (GKE), emphasized GKE’s foundational role in supporting AI platforms. While AI dominates current tech conversations, Allen highlighted that cloud-native infrastructure like Kubernetes is what enables AI workloads to function efficiently. GKE powers key Google services like Vertex AI and is trusted by organizations including DeepMind, gaming companies, and healthcare providers for AI model training and inference.

Allen explained that GKE offers scalability, elasticity, and support for AI-specific hardware like GPUs and TPUs, making it ideal for modern workloads. He noted that Kubernetes was built with capabilities—like high availability and secure orchestration—that are now essential for AI deployment. Looking forward, GKE aims to evolve into a model router, allowing developers to access the right AI model based on function, not vendor, streamlining the development experience. Allen described GKE as offering maximum control with minimal technical debt, future-proofed by Google’s continued investment in open source and scalable architecture.

Learn more from The New Stack about the latest insights with Google Cloud:

Google Kubernetes Engine Customized for Faster AI Work

KubeCon Europe: How Google Will Evolve Kubernetes in the AI Era

Apache Ray Finds a Home on the Google Kubernetes Engine

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

  continue reading

895 episodes

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