UPDATED 18:14 EDT / NOVEMBER 18 2024

How AI is transforming cloud-native platforms and driving machine vision, enabling scalable, reliable and developer-friendly solutions. BIG DATA

Empowering developers: How T-Mobile leverages Kubernetes for AI and machine vision

T-Mobile’s innovative use of Kubernetes showcases how enterprises can scale cloud-native architectures to drive efficiency and developer autonomy.

The company’s journey with Kubernetes and Portworx by Pure Storage Inc. began in 2017, during the early stages of the telecommunications giant’s transition to cloud-native architectures. It focuses on enabling self-service for developers, fostering trust to reduce dependency on the platform team, and ensuring maintenance and updates are performed seamlessly without impacting users.

“The majority of our applications run within Kubernetes now, and the efficiency we’re getting compared to architectures before is pretty amazing,” said Ameer Dixit (pictured, right), platform architect at T-Mobile.

Portworx’s Venkat Ramakrishnan and T-Mobile’s Ameer Dixit discuss AI use cases.

Dixit and Venkat Ramakrishnan (left), vice president of engineering and products of Portworx, spoke with theCUBE Research’s Savannah Peterson and Rob Strechay at KubeCon + CloudNativeCon NA, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed T-Mobile’s journey with Kubernetes, the transformative role of AI in fields like machine vision, and how Portworx is enabling organizations to scale innovation. (* Disclosure below.)

 

 

Kubernetes catalyzes cloud-native transformation in AI, DevOps and machine vision

Artificial intelligence relies on vast amounts of data. However, a realization surfacing gradually is that the use case for streamlined data management extends beyond gen AI into other cutting-edge fields such as machine vision and autonomous vehicle tech. Companies increasingly rely on comprehensive platforms addressing all cloud-native data needs, and Portworx has moved beyond storage to support that soaring demand for a broader scope of data-intensive AI applications.

“We have helped our customers build autonomous cars, machine vision, and most of the large language models and supervised and unsupervised machine learning models actually run on Kubernetes,” Ramakrishnan said. “What we see now is this huge outgrowth in all of these models coming out and a lot of research and a lot of development that has been going on for many years are actually now out there for people to take advantage of.”

Kubernetes has become the backbone of cloud-native applications, transforming how enterprises manage workloads. T-Mobile’s Kubernetes journey and use of Portworx’s infrastructure enabled it to streamline application deployment across hundreds of clusters and tens of thousands of nodes.

The shift from stateless to stateful applications in Kubernetes has been significant. Given the platform’s consistent uptime and performance, concerns about storage reliability have largely dissipated. This transition has reduced operational burdens, allowing developers to focus on innovation rather than infrastructure, according to Dixit.

“We have storage classes — we have a very small amount of documentation and it works for this very large user base,” he said. “We do have some busy storage workloads and again, happy with their performance and I’m not fighting too many battles with that.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of KubeCon + CloudNativeCon NA

(* Disclosure: Portworx at Pure Storage Inc. sponsored this segment of theCUBE. Neither Portworx nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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