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What is Red Hat Advanced Cluster Management?

Red Hat Advanced Cluster Management for Kubernetes offers a centralized platform for monitoring clusters and applications, integrated with security policies. It enriches the functionalities of Red Hat OpenShift, enabling seamless application deployment, efficient management of multiple clusters, and the establishment of policies across a wide range of clusters at scale. This solution ensures compliance, monitors usage, and preserves consistency throughout deployments. Included with Red Hat OpenShift Platform Plus, it features a comprehensive set of robust tools aimed at securing, protecting, and effectively managing applications. Users benefit from the flexibility to operate in any environment supporting Red Hat OpenShift, allowing for the management of any Kubernetes cluster within their infrastructure. The self-service provisioning capability accelerates development pipelines, facilitating rapid deployment of both legacy and cloud-native applications across distributed clusters. Additionally, the self-service cluster deployment feature enhances IT departments' efficiency by automating the application delivery process, enabling a focus on higher-level strategic goals. Consequently, organizations realize improved efficiency and agility within their IT operations while enhancing collaboration across teams. This streamlined approach not only optimizes resource allocation but also fosters innovation through faster time-to-market for new applications.

What is Bright Cluster Manager?

Bright Cluster Manager provides a diverse array of machine learning frameworks, such as Torch and TensorFlow, to streamline your deep learning endeavors. In addition to these frameworks, Bright features some of the most widely used machine learning libraries, which facilitate dataset access, including MLPython, NVIDIA's cuDNN, the Deep Learning GPU Training System (DIGITS), and CaffeOnSpark, a Spark package designed for deep learning applications. The platform simplifies the process of locating, configuring, and deploying essential components required to operate these libraries and frameworks effectively. With over 400MB of Python modules available, users can easily implement various machine learning packages. Moreover, Bright ensures that all necessary NVIDIA hardware drivers, as well as CUDA (a parallel computing platform API), CUB (CUDA building blocks), and NCCL (a library for collective communication routines), are included to support optimal performance. This comprehensive setup not only enhances usability but also allows for seamless integration with advanced computational resources.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Ansible
IBM Cloud
Kubernetes
Microsoft Azure
Red Hat OpenShift

Integrations Supported

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

Red Hat

Date Founded

1993

Company Location

United States

Company Website

www.redhat.com/en/technologies/management/advanced-cluster-management

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/bright-cluster-manager

Categories and Features

Categories and Features

Cluster Management

Not specified

Deep Learning

ML Algorithm Library

HPC

Not specified

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