In the rapidly evolving landscape of artificial intelligence (AI), businesses are constantly seeking ways to leverage AI to drive innovation, efficiency, and growth. OpenShift AI emerges as a powerful platform that enables enterprises to develop, deploy, and manage AI models with ease. This blog series aims to provide a comprehensive guide to OpenShift AI, starting with an introduction to its capabilities and benefits.
What is OpenShift AI?
OpenShift AI is an AI-focused platform provided by Red Hat that offers tools to train, tune, serve, monitor, and manage AI/ML experiments and models. Built on the robust OpenShift Container Platform, it integrates seamlessly with existing infrastructures and supports a wide range of AI/ML frameworks such as TensorFlow, PyTorch, and JupyterLab.
OpenShift AI provides a unified platform for data scientists, developers, and operations teams, enabling them to collaborate effectively. With features like scalable model training, deployment, and monitoring, it ensures that AI models can move swiftly from development to production .
Components of OpenShift AI
This diagram illustrates the components of OpenShift AI and how they interact, providing a visual overview of the platform’s capabilities.
OpenShift AI as Hybrid MLOps Platform
Model development
Conduct exploratory data science in JupyterLab with access to core AI / ML libraries and frameworks including TensorFlow and PyTorch using our notebook images or your own.
Model serving & monitoring
Deploy models across any cloud, fully managed, and
self-managed OpenShift footprint and centrally monitor their performance.
Lifecycle Management
Create repeatable data science pipelines for model training and validation and integrate them with DevOps pipelines for delivery of models across your enterprise.
Increased capabilities / collaboration
Create projects and share them across teams. Combine Red Hat components, open sourcesoftware, and ISV certified software.
OpenShift AI Key features
Why Choose OpenShift for AI?
OpenShift AI offers several key benefits for enterprises:
Scalability:Â OpenShift AI allows businesses to easily scale their AI workloads to meet increasing demands. Whether you need to process large datasets or run complex models, OpenShift AI can handle the load.
Flexibility:Â Supporting hybrid and multi-cloud environments, OpenShift AI enables deployment across on-premises, public cloud, and edge locations. This flexibility ensures that AI models can be deployed wherever they are needed most.
Security With comprehensive security features, OpenShift AI protects your AI models and data. From automated security scanning to vulnerability management, OpenShift AI ensures that your AI projects are secure from development to deployment.
Integration: OpenShift AI seamlessly integrates with Red Hat’s portfolio and third-party tools, providing a unified AI/ML workflow. This integration simplifies the process of developing and deploying AI models, allowing teams to focus on innovation.
Getting Started with OpenShift AI
To get started with OpenShift AI, follow these basic steps:
Set Up OpenShift:Â Install and configure the OpenShift Container Platform. This provides the foundational infrastructure needed for OpenShift AI.
Deploy OpenShift AI:Â Use the OpenShift AI components to set up your AI environment. This includes deploying tools and frameworks such as TensorFlow, PyTorch, and JupyterLab.
Develop and Deploy Models:Â Utilize the supported tools and frameworks to develop and deploy AI models. OpenShift AI supports the entire lifecycle of AI development, from data preparation and model training to deployment and monitoring.
OpenShift AI is a powerful platform that offers the tools and capabilities needed to unlock the full potential of AI in your enterprise. With its scalability, flexibility, security, and integration, OpenShift AI simplifies the process of developing and deploying AI models.
Stay tuned for the next part of this series, where we’ll delve deeper into building and deploying AI models with OpenShift AI.
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