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Red Hat OpenShift Data Science
Red Hat® OpenShift® Data Science is a managed cloud service that IT operations teams can enable for data scientists and developers of intelligent applications. It provides a fully supported environment in which to rapidly develop, train, and test machine learning (ML) models in the public cloud before deploying in production.
Accelerate your data science
Red Hat OpenShift Data Science allows organizations to quickly build and deploy artificial intelligence (AI)/ML models by integrating open source tooling with commercial partner applications.
The ML models built in Red Hat OpenShift Data Science are easily portable to other platforms, allowing teams to deploy them in production, on containers, whether on-premise, at the edge or in the public cloud.
- Quickly build models with Jupyter notebooks, TensorFlow, and PyTorch support without worrying about the underlying infrastructure.
- Consistently deploy models to production in a container-ready format across hybrid cloud and edge environments.
- Provide a user friendly platform that can scale up and down with little effort.
- Choose from over 30 leading AI/ML partner offerings.
- Develop MLOps best practices to deploy and operate machine learning workloads at scale with Red Hat’s consulting services, including Open Innovation Labs.
Spend less time managing AI infrastructure
Through this AI/ML add-on service to Red Hat OpenShift Dedicated or 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.
Tested, supported AI/ML tooling
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, and model serving on our Red Hat OpenShift cloud service, so you and your data scientists do not have to. OpenShift Data Science draws from years of incubation in Red Hat’s Chief Technology Officer’s Open Data Hub community project.
Expand your capabilities with technology partners
Extend the core Red Hat OpenShift Data Science 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, and Pachyderm.
Start fast and scale quickly
Data practitioners can easily choose their cluster size to suit their environments without having to provision hardware. Hardware acceleration images from NVIDIA and Intel can be easily selected for more challenging ML workloads. And the ability to create custom Jupyter notebook images using libraries and packages chosen by the organization provides flexibility for data scientists while maintaining control for IT operations.
Develop best practices
Unite your disparate operations teams and data scientist teams through Red Hat’s AI/ML consulting services. Improve cross-functional collaboration and simplify maintenance with a single platform. Learn best practices and build your own ML pipeline project using DevOps and MLOps through Red Hat’s proven methodology.
Engage a managed cloud service to build models using Jupyter notebooks. Red Hat OpenShift Data Science tracks changes to Jupyter, TensorFlow, and PyTorch, and other open source AI technologies, integrating them into the service faster so you can speed up innovation.
As the Kubernetes expert, Red Hat helps you easily integrate your data science projects into intelligent applications for hybrid cloud deployment. IT Ops teams benefit by having an easy-to-manage ML platform, including expanding model serving capabilities to increase operational efficiency.
Red Hat OpenShift Data Science integrates open source tools with Red Hat's AI/ML partner ecosystem to accelerate project development and enhance platform capabilities. With Red Hat's hybrid cloud approach you can eliminate cloud provider lock-ins and minimize vendor lock-ins.