In the quest for digital transformation, enterprises are increasingly turning to artificial intelligence (AI) to unlock new insights, drive innovation, and enhance customer experiences. Red Hat OpenShift AI emerges as a game-changer in this landscape, seamlessly integrating AI capabilities within the powerful OpenShift container platform.
Red Hat OpenShift AI integrates advanced AI capabilities with the robust Kubernetes-based container platform of Red Hat OpenShift, offering a comprehensive solution for organizations seeking to harness the power of artificial intelligence:
- Containerized AI Services: Incorporates popular AI frameworks like TensorFlow, PyTorch, and scikit-learn within Docker containers, facilitating seamless deployment and scaling of AI workloads across diverse environments
- Kubernetes Orchestration: Automated deployment, scaling, and management of AI applications, optimizing resource utilization and ensuring high availability. Declarative configuration and self-healing capabilities minimize administrative overhead
- Data Pipelines and Integration: Enables creation of data pipelines for ingesting, processing, and analyzing large volumes of data. Integration with data lakes, databases, and streaming platforms supports real-time analytics, empowering actionable insights
- Model Training and Inference: Supports distributed training and inference for efficient development and deployment of AI models at scale. Utilizes distributed computing resources effectively to handle complex models and large datasets, ensuring performance in production environments
- Security and Governance: Prioritizes data protection with built-in features such as encryption, role-based access control (RBAC), and audit logging. Ensures confidentiality, integrity, and availability of AI assets, crucial for maintaining trust and compliance
Red Hat OpenShift AI enhances organizational agility, scalability, and security, enabling innovation and competitive advantage in today's data-driven world.
In this webinar, we’ll cover:
- Introduction to Artificial Intelligence
- Describe the main features, architecture, components of Red Hat OpenShift AI
- Challenges it solves
- Organize code and configuration by using data science projects, workbenches, and data connections
- Installing Red Hat OpenShift AI by using the web console and the CLI, and managing Red Hat OpenShift AI components
Any questions? Please email Viral Gohel.
Monika Gugnani
Technical Account Manager, Red Hat
Monika is an IT professional with more than 19 years of experience in Linux and open source technologies.
An Open Source enthusiast and an expert in advocating the requirements of automation and containerization technologies on hybrid cloud environments to enterprise customers in achieving better ROI and business demands.
Monika, in her current role, as Technical Account Manager, is a technical advisor to the IT customers and helps streamline deployments, resolve issues, and strategically plan for the future in Red Hat Openshift. She has deep technical knowledge and develops a personal relationship to drive performance and growth, and proactively ensure a stable and secure product experience.
She has certifications in RHEL Automation,Red Hat Openshift and Red Hat Middleware.
Ravikumar Jaiswal
Senior Technical Account Manager, Red Hat
Ravikumar is an IT professional with more than 16 years of Industry experience.
He specializes in Middleware technologies and the Openshift Container platform.
As Technical Account Manager, Ravi engages with a variety of customers spread across various Business sectors like Retail Banking, prominent Public Sector Undertaking and IT service provider partners. Ravi proactively looks for a customer environment and shares his advice regularly about any change in technology suitable for customer's infrastructure.
