Red Hat, the world’s leading provider of open source solutions, highlighted that more organizations are using Red Hat OpenShift as the foundation for building artificial intelligence (AI) and machine-learning (ML) data science workflows and AI-powered intelligent applications.
OpenShift helps to provide agility, flexibility, portability and scalability across the hybrid cloud, from cloud infrastructure to edge computing deployments, a necessity for developing and deploying ML models and intelligent applications into production more quickly and without vendor lock-in.
As a production-proven enterprise container and Kubernetes platform, OpenShift delivers integrated DevOps capabilities for independent software vendors (ISVs) via Kubernetes Operators and NVIDIA GPU-powered infrastructure platforms.
This combination can help organizations simplify the deployment and lifecycle management of AI/ML toolchains as well as support hybrid cloud infrastructure. With these enhancements, data scientists and software developers are empowered to better collaborate and innovate in the hybrid cloud rather than simply manage infrastructure resource requests.
Customer and ecosystem interest in AI/ML
The customer momentum seen by Red Hat validates the AI/ML findings from the recent 2020 Red Hat Global Customer Tech Outlook report. The report surveyed 876 Red Hat customers on their top IT priorities and found that 30% of respondents plan on using AI/ML over the next 12 months, ranking AI/ML as the top emerging technology workload consideration for companies surveyed in 2020.
For example, Kasikorn Business-Technology Group (KBTG) supports the day-to-day operations of KBank, one of Thailand’s largest commercial banks, and also provides technology developer and partner services for fintech firms across Thailand.
To support the doubling of KBank’s user base, KBTG developed K PLUS AI-Driven Experience (KADE) to help analyze customer behavior and deliver a more personalized experience and also launched UCenter, a unified notification feed system, built and deployed on Red Hat OpenShift.
Other customer cases of AI/ML solutions on Red Hat OpenShift include Boston Children’s Hospital and more.
Along with these customers using OpenShift to accelerate AI/ML workflows and deliver AI-powered intelligent applications, AI/ML ISV partners including CognitiveScale, Dotscience, NVIDIA and Seldon have recently developed OpenShift integrations via certified Kubernetes Operators.
OpenShift is also powering IBM Cloud Paks to help customers accelerate their journey to the cloud and transform business operations in support of new workloads, including AI/ML/DL.
Additionally, to streamline the adoption of AI-enabled infrastructure in the enterprise datacenters, Red Hat has collaborated with Hewlett Packard Enterprise (HPE) and NVIDIA on a new Accelerated AI Reference Architecture, which offers design and deployment guidelines to help mutual customers bring AI-based applications to production more quickly.
Driving open AI innovation
Red Hat continues to be an active contributor to the Kubeflow open source community project, which focuses on simplifying ML workflows for Kubernetes while enhancing workload portability and scalability.
Kubeflow can now run on OpenShift as documented here, and a Kubeflow Kubernetes Operator is in development to help simplify the deployment and lifecycle management of Kubeflow on OpenShift.
Additionally, Red Hat leads the Open Data Hub community project to provide a blueprint for building an AI-as-a-Service platform with Red Hat OpenShift, Red Hat Ceph Storage and more.
Open Data Hub v0.5.1 is now available and includes tools like JupyterHub 3.0.7, Apache Spark Operator 1.0.5 for managing spark clusters on OpenShift and the Apache Superset data exploration and visualization tool.