Red Hat bolsters partner ecosystem to accelerate data science across open hybrid cloud

Red Hat has announced the availability of Red Hat OpenShift Data Science as a field trial, as well as an expanded partner ecosystem focused on this new cloud service offering.

As artificial intelligence and machine-learning partners support the service, Red Hat customers are provided with a range of solutions optimised for Red Hat OpenShift, letting them select the technologies to best meet their specific machine learning needs across the open hybrid cloud and edge computing environments.

Red Hat OpenShift Data Science is a cloud service offering tailored for machine learning on Red Hat OpenShift. Enabled by Kubernetes operators, Red Hat OpenShift Data Science gives enterprises flexibility in selecting the technologies to develop, test and deploy ML models, while removing the overhead associated with running and maintaining a production platform.

As a fully-managed cloud service, Red Hat OpenShift Data Science moves operational responsibility and support to Red Hat. This gives organisations the freedom to use their chosen AI/ML tools in developing the next-generation of intelligent applications to drive valuable business insights.

Several key members of Red Hat's AI/ML partner ecosystem are now pre-integrated into the user interface dashboard, providing access to the latest in hardware and software acceleration solutions as well as tools to support the model operationalisation lifecycle.

This includes Intel toolkits and, planned in the near future, NVIDIA-accelerated computing support, which will enable customers to benefit from:

Access to a fully-integrated model development environment, with the ability to optimise and tailor model behaviour on Intel hardware, using Intel OpenVINO Pro for Enterprise; and accelerated speed to insights with the Intel oneAPI AI Analytics Toolkit, which provides data scientists with a series of tools and frameworks optimised for maximum performance on Intel-based CPUs. With these offerings from Intel, data scientists not only have integrated access to the tools and frameworks needed to build and deploy their model, but also help deliver high performance on Intel hardware.

Accelerated computing support through the use of NVIDIA GPU technology, which can enable data scientists to scale their computationally expensive neural networks to large, complex architectures without sacrificing productivity. This allows data scientists to cut down the time spent on training models with minimal code changes.

In addition to Intel and NVIDIA, Red Hat OpenShift Data Science includes support from several other leading AI/ML partners, including:

• Anaconda Commercial Edition for more secure, consistent and repeatable data science package distribution and management
• IBM Watson Studio with AutoAI to build, run, and manage AI models at scale
• Seldon Deploy to simplify and accelerate deploying, managing and monitoring machine learning models
• Starburst Galaxy to unlock the value of data by making it faster and easier to access data across the hybrid cloud

"As enterprises invest in AI/ML to drive business decisions and gain actionable insights from data, we have seen a highly-competitive marketplace for MLOps solutions that strive to operationalise the ML lifecycle," Red Hat says.

"Red Hat OpenShift Data Science offers enterprise customers a customisable alternative to prescriptive AI/ML solutions, through its open workflow platform including Jupyter notebooks and common frameworks including Pytorch and Tensorflow, and complemented by access to certified partner technology from Red Hat Marketplace."

Red Hat OpenShift Data Science is available via field trial as an add-on to Red Hat OpenShift Dedicated and on Red Hat OpenShift Service on AWS. The field trial release of Red Hat OpenShift Data Science offers general availability-level quality and support, allowing customers to try out the service, while only paying for the underlying Red Hat OpenShift Dedicated or Red Hat OpenShift Service on AWS and AWS infrastructure.

"Data science and machine learning are helping drive innovation and business value in nearly every industry," says Mike Piech, vice president and general manager, Cloud Data Services, Red Hat.

"For many companies the biggest barrier to adoption is the complexity of wiring together the necessary data sources with diverse model training and model deployment technologies," he says.

"With Red Hat OpenShift Data Science, Red Hat's contributions to Open Data Hub, and our extensive partner ecosystem, were helping organisations overcome such complexity to begin harnessing the full potential of machine learning from the leader in trusted open source technology."