Your Red Hat account gives you access to your member profile and preferences, and the following services based on your customer status:
Not registered yet? Here are a few reasons why you should be:
- Browse Knowledgebase articles, manage support cases and subscriptions, download updates, and more from one place.
- View users in your organization, and edit their account information, preferences, and permissions.
- Manage your Red Hat certifications, view exam history, and download certification-related logos and documents.
Your Red Hat account gives you access to your member profile, preferences, and other services depending on your customer status.
For your security, if you're on a public computer and have finished using your Red Hat services, please be sure to log out.Log out
AI Partner Ecosystem
Accelerate machine learning pipelines and intelligent application delivery
Build a hybrid cloud platform for AI/ML workloads
Leaders in a variety of industries are using the power of artificial intelligence (AI) and machine learning (ML) to deliver business outcomes.
Red Hat has the leading open hybrid cloud platform powered by containers, Kubernetes, DevOps, and a broad ecosystem of partner technologies to help you build a solid foundation for production-ready AI/ML environments, along with AI cloud services and training for rapid adoption.
Why AI/ML is important
Intelligent applications powered by AI and ML can help you accelerate business-critical initiatives. Many organizations are using AI/ML in production with intelligent applications that automatically discover, learn, and offer predictions and recommendations—gaining a competitive advantage and informing strategic planning.
Use cases include: autonomous driving, predictive maintenance, improved supply chains, improved risk analysis, reduced fraud, more personalized services, quicker research outcomes and disease identification and treatment, and protection of life and health of citizens via smart cities, weather and climate modeling, and population health.
While there are many benefits, adopting AI/ML can pose significant challenges. In addition to hardware investments, there are architectural, cultural, and process considerations associated with creating an agile AI/ML environment. Proprietary solutions are complex and inflexible, making it increasingly difficult to integrate and operate AI/ML workloads at scale.
Open source containers and Kubernetes DevOps practices are key to accelerating the AI and ML life cycles and intelligent application delivery. These technologies give data scientists much-needed agility, flexibility, portability, and scalability to train, test, and deploy models in production.
A leader among multicloud container development platforms,1 Red Hat® OpenShift® enables collaboration between data scientists and software developers. It accelerates the rollout of intelligent applications across hybrid cloud environments, from the data center to the edge to multiple clouds.
Create a unified environment for application development, delivery, integration, and automation. Data integration services help you build effective data pipelines, runtime services simplify application development, and process automation streamlines and automates business processes and decisions.
The Red Hat certified partner ecosystem allows you to integrate your choice of AI/ML and application development tools into this architecture, enabling you to successfully adopt AI/ML for intelligent applications with better business results.
1 Bartoletti D, Dai C, et al., "The Forrester Wave™: Multicloud Container Development Platforms 2020 Q3 report," Forrester Research, September 2020.
Red Hat and our certified partners provide the solutions you need to accelerate AI/ML initiatives with confidence.
Customers value the broad partner ecosystem Red Hat has created around Red Hat Enterprise Linux® since 2002, which Red Hat has expanded to address additional enterprise needs for AI solutions running in containers on Kubernetes. These robust ecosystems demonstrate Red Hat’s long and ongoing commitment to delivering productive environments, populated by software partners.
AI/ML framework on Kubernetes
Red Hat works closely with an ecosystem of certified partners, who extend and enhance our portfolio of infrastructure solutions and end-to-end integration to provide tailored solutions that directly address your use cases and enable success.
A key part of accelerating the ML life cycle are Kubernetes Operators—a method of packaging, deploying, and managing a Kubernetes application that accompanies a partner’s solution. Red Hat OpenShift relies on operators to reduce operations effort and cost, increase service reliability, and spur innovation by freeing teams from repetitive maintenance work. Red Hat works closely with partners to meet key certification standards. Operator Hub, integrated into Red Hat OpenShift, provides easy access to fully certified operators from our partners that meet a high bar of quality standards.
Why deploy containers, Kubernetes, and DevOps for AI/ML?
Certified partner software solutions for AI/ML
Red Hat AI partners build on the Red Hat Infrastructure to complete and optimize AI/ML application development. They help to complete the AI pipeline with solutions ranging from data integration and preparation, to AI model development and training, to model serving and inferencing (making predictions) based on new data. All of this is supported on a self-service hybrid multicloud platform that empowers data scientists, data engineers, and software developers to be agile and collaborative, with a consistent experience across on-premises, public clouds, and edge locations.
Royal Bank of Canada (RBC) and its AI research institute, Borealis AI, partnered with Red Hat and NVIDIA to build a private cloud AI that could bring transformative intelligent applications to market faster and enhance the customer experience. With Red Hat OpenShift and NVIDIA’s DGX AI computing systems, RBC can run thousands of simulations and analyze millions of data points in a fraction of the time previously required.
Red Hat and SAS collaborate to enable organizations to use open, hybrid cloud technologies and analytical capabilities to drive business-level intelligence.
Red Hat OpenShift is optimized for H2O Driverless AI and H2O Open Source, making it easier to deploy and manage H2O.ai products across the hybrid cloud.
Anaconda and Red Hat address innovation in AI by bridging the gap between data science and IT in the enterprise to quickly deliver insights into the hands of decision makers.