UBIX.AI Operator Achieves Red Hat OpenShift Operator Certification

Mar 3, 2020


Enables automated deployment of AI projects across the hybrid cloud using enterprise Kubernetes & containers


San Juan Capistrano, Mar 3, 2020 (Issuewire.com) - UBIX, the open-source AI-on-Demand company, is pleased to announce the availability of the UBIX Kubernetes Operator for Red Hat OpenShift. This helps simplify and accelerate machine learning (ML) workflows and development of AI powered intelligent applications on the Red Hat OpenShift Container Platform. It has achieved Red Hat OpenShift Operator Certification and is now available in the Red Hat Container Catalog.

UBIX is an open-source data science platform designed to manage the complete machine learning lifecycle. It automates and scales all the critical tasks across the end-end data and analytics pipeline. It's learning engine analyzes and learns from the tasks of the data science teams to make recommendations so that users of all skill levels can contribute to the development of AI applications at scale. UBIX is a natural fit for AI application development on a modern hybrid cloud and container infrastructure.

Containers and Kubernetes can help accelerate ML workflows as these technologies provide agility, flexibility, scalability and portability that data scientists and application developers need to develop and deploy ML models and intelligent applications into production.

Red Hat OpenShift is the industry's most comprehensive enterprise Kubernetes platform for deploying cloud-native workloads across the hybrid cloud. It integrates the capabilities of  Kubernetes Operators, DevOps tools and GPU hardware acceleration to enable better collaboration between data scientists and software developers. This helps to speed the roll-out of intelligent applications across hybrid cloud environments.

Kubernetes Operators codify operational knowledge and workflows to automate the installation and lifecycle management of containerized applications and infrastructure with Kubernetes.

The UBIX Kubernetes Operator helps automate the deployment of UBIX on Red Hat OpenShift so that OpenShift customers can focus on accelerating machine learning workflows and delivering AI applications across hybrid cloud instead of dealing with cloud infrastructure management.

"Deploying AI applications on hybrid cloud infrastructure is now easier to achieve with Red Hat OpenShift and UBIX," said Douglas Barton, President and CEO of UBIX. "Partnering with Red Hat OpenShift provides our customers with a force multiplier for the practice of data science and application of AI enterprise-wide."

"UBIX Operator has achieved Red Hat OpenShift Operator Certification and is part of the Red Hat Partner Connect ecosystem," said Julio Tapia, director, Cloud Platforms ecosystem, Red Hat. "Kubernetes Operators are appealing because they help encode the human operational logic normally required to manage services running as a Kubernetes-native application and aim to make day-to-day operations easier. By providing Operators on Red Hat OpenShift, users can begin experiencing the next level of benefits from a Kubernetes-native infrastructure, with services designed to 'just work' across the cloud where Kubernetes runs."

About UBIX 
UBIX offers a cognitive, AI-on-Demand platform that empowers users of all skill levels to develop and deploy open-source, big, fast data architecture and data science pipelines faster and better than ever. Our patented data shaping and patent-pending learning engine are trained by each input, interaction, and outcome, growing in knowledge and impact over time. Together, we improve productivity, creativity, eliminate errors, support governance, and ultimately accelerate time to value. UBIX is privately funded and based in Orange County, CA. For more information, visit www.ubix.ai or follow us on LinkedIn.

Media Contact
Douglas Barton
UBIX
[email protected]

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Media Contact

UBIX.AI


[email protected]

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32234 Paseo Adelanto, Suite A

http://www.ubix.ai

Source :UBIX.AI

This article was originally published by IssueWire. Read the original article here.

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