KubeSphere 3.2.0 Release Brings AI-Oriented GPU Resource Management

KubeSphere, a fast-growing open-source community, has released KubeSphere 3.2.0, the most recent version of a complete Kubernetes management platform. In the latest version of KubeSphere, GPU resource scheduling and management and GPU usage monitoring would further improve user experience in cloud-native AI scenarios.

Multi-cluster management, multi-tenant management, observability, DevOps, app store, and service mesh are just a few of the enhanced features in KubeSphere that would further help to improve the interactive design for a better user experience.

In the age of artificial intelligence (AI) and machine learning (ML), keeping track of GPU utilization and managing GPU resource limitations is critical. Users may define GPU workloads on the GUI, schedule GPU resources, and manage GPU resource quotas by tenants using KubeSphere 3.2.0. It is also compatible with NVIDIA and vGPU solutions.

“Open source and internationalization are two solid pillars to KubeSphere,” said Ray Zhou, Head of the KubeSphere project. “Tens of thousands of individual users and enterprises across the globe are using KubeSphere in production environments, and what we can repay them is to continue our commitment to providing cutting-edge cloud-native stacks and helping enterprises to embrace Kubernetes with ease.”

Multi-Cluster and Multi-Cloud

KubeSpere’s v.3.10 released six months ago including edge computing capabilities, metering, and billing, extending Kubernetes from the cloud to the edge and allowing organizations to better monitor the operational costs of infrastructure and applications.

Enhanced capabilities such as multiple Kubernetes cluster management, multi-tenant management, observability, DevOps, App store, and service governance are now available in KubeSphere 3.2.0, further perfecting interactive design for a better user experience.

KubeSphere is designed to handle multi-cluster and multi-cloud issues. It offers a uniform control plane and allows for the distribution of applications and replicas over numerous clusters in both public and private clouds. Furthermore, KubeSphere offers observability across clusters in several dimensions, including monitoring, logs, events, and auditing logs.

Open-Source Project

KubeSphere maintains its open-source commitment with a thriving ecosystem that would include a number of lightweight, efficient toolkits for making Kubernetes simple. KubeKey, an open-source installer, leverages Docker as the default container runtime to effectively install Kubernetes, and since Dockershim’s deprecation, it now now supports CRI runtimes including containerd, CRI-O, and iSula. Other intelligent tools, like OpenFunction, OpenELB, and Fluent Operator, are free to use, and users may access code and documentation through GitHub repositories.

KubeSphere is making great advances on its international journey as an open-source project, with over 700,000 downloads across 90 countries and regions so far. According to the project, KubeSphere is gaining great appeal among medium and large companies for its expertise in security, scalability, high availability, and more, in addition to reducing the learning curve of Kubernetes for individual users.

KubeSphere announced a partnership with Amazon Web Services (AWS) Quick Start, DigitalOcean Marketplace, and Microsoft Azure Marketplace (China) in 2021, significantly speeding up its adoption and globalization in the expanding cloud-native market.

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