Overview
For the EMEA region, Red Hat OpenShift AI enables companies to solve critical business challenges by providing a fully managed cloud service environment on Red Hat OpenShift Service on AWS. Red Hat OpenShift AI allows organizations to quickly build and deploy artificial intelligence (AI)/ML models by integrating open source tools with commercial partner solutions.
Red Hat OpenShift AI is an easy-to-configure cloud service that provides a powerful platform for building AI/ML models and applications. It combines the self-service data scientists and developers want, with the confidence enterprise IT demands into one common platform. Common tooling, such as Jupyter notebooks and associated TensorFlow and Pytorch frameworks are provided as an add-on to Red Hat OpenShift Service on AWS, an application platform cloud service powered by Kubernetes and jointly supported by Red Hat and AWS.
The ML models built in Red Hat OpenShift AI are easily portable to other platforms, allowing teams to deploy them in production, on containers, and in the hybrid cloud. Having a trusted foundation reduces friction throughout the life cycle: From a powerful platform to experiment in, to a broad ecosystem of certified tools, to familiar workflows for collaboration. Red Hat OpenShift AI helps teams get intelligent apps into the market faster, where they can deliver the greatest value to the business.
To get started, you first need to deploy Red Hat OpenShift Service on AWS. That cluster runs on AWS infrastructure under your AWS account. Then you can install the Red Hat OpenShift AI add-on into that cluster.
Highlights
- Through this AI/ML add-on service to Red Hat OpenShift Services for AWS, your data science teams can start their projects faster. Instead of standing up and managing your own Kubernetes infrastructure, you can focus on deploying intelligent applications, integrating the models you develop. Gain added benefits like security and operator life cycle integration, built into intelligent applications to simplify the deployment and maintenance of your models.
- Get quick updates and support for core open source tooling. Red Hat tracks, integrates, tests, and supports common AI/ML tooling like Jupyter, TensorFlow, PyTorch, common libraries like Pandas and NumPy, and the source-to-image framework on our Red Hat OpenShift cloud service, so you and your data scientists do not have to.
- Extend the core Red Hat OpenShift AI platform with other integrated Red Hat services like Red Hat OpenShift Streams for Apache Kafka and several leading AI/ML software technology partners including Starburst, Anaconda, IBM, Intel, and Pachyderm through Red Hat Marketplace.
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Dimension | Cost/unit |
|---|---|
vCPU usage in hours. Example: 2 hours on m5.xlarge = 8 vCPU hours | $0.022 |
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