The landscape of Artificial Intelligence and Machine Learning  is continuously evolving, transforming how organizations across various sectors leverage data for strategic insights and innovative application development. 

Red Hat OpenShift AI is a platform that runs on top Red Hat OpenShift Container Platform, offering tools across the AI/ML lifecycle, including rapid development, training, serving, and monitoring of machine learning models on-site, in the public cloud, or at the edge​​​​.
The platform supports a range of popular open-source tooling, providing a familiar environment for data scientists and developers with integrated MLOps components for model serving and data science pipelines.

We are first looking at Dell APEX Cloud Platform for Red Hat OpenShift and then how the combination with OpenShift AI provides synergies and business outcomes for customers.

Dell APEX Cloud Platform for Red Hat OpenShift

ACP for Red Hat OpenShift is designed collaboratively with Red Hat to optimize and extend OpenShift deployments on-premises. This platform integrates seamlessly with Red Hat OpenShift, simplifying deployment and enabling a consistent, automated operational experience across on-premises and cloud OpenShift deployments.

Core Components and Features

Integrated and Automated Operations: The APEX Cloud Platform incorporates deep integrations and intelligent automation between Dell and OpenShift technology stacks. This results in a significant reduction in complexity and time-to-value for deployments.

High-Performance Architecture: The platform leverages a bare-metal architecture, ensuring high performance, security, and linear scalability. This is pivotal in meeting stringent SLAs and supporting demanding workloads.

Advanced Lifecycle Management: The platform embodies advanced lifecycle-management capabilities, ensuring that the technology stack remains compliant, secure, and up to date. This includes rapid availability of patches and updates.

Unified Management Interface: The Dell APEX Cloud Platform integrates infrastructure management into a single, unified OpenShift management user interface base on OpenShift Web Console, thereby eliminating the need to manage different layers through multiple consoles.

Security and Compliance: The platform integrates intrinsic multi-layer security, bolstering the security posture across deployments. This includes centralized OpenShift governance and compliance enforcement.

Scalability and Flexibility: Based on common hardware building blocks, compute and storage nodes can scale independently.
The platform offers scalable, high-performance Dell Software-Defined Storage, optimized for both traditional and modern AI, ML, and analytics workloads.

OpenShift AI with ACP for Red Hat OpenShift

The integration of  the OpenShift AI capabilities with the APEX Cloud Platform for Red Hat OpenShift opens new possibilities for businesses to innovate and modernize applications. 

Organizations can swiftly move from experimentation to production in AI/ML projects. The integration of tools like Jupyter notebooks and frameworks such as TensorFlow and PyTorch within Red Hat OpenShift AI, combined with the robust infrastructure of Dell APEX Cloud Platform, streamlines the entire AI/ML development lifecycle​​.

The combined strength of Red Hat OpenShift AI’s model serving stack and Dell’s automated deployment capabilities enable businesses to scale their AI models efficiently. This scalability is crucial for handling varying workloads and rapidly deploying AI models in different environments, from on-premises to the cloud​​.

The efficient handling and deployment of LLMs on the Dell APEX Cloud Platform, powered by Red Hat OpenShift AI, enable organizations to utilize complex AI models effectively.
The platform’s ability to handle the computational demands of running LLMs ensures cost-effective usage of underlying hardware, particularly GPUs, which is critical for AI-driven applications​​.

Key Features of Red Hat OpenShift AI

Full Lifecycle AI/ML Platform: Red Hat OpenShift AI provides tools across the entire lifecycle of AI/ML experiments and models. This includes training, serving, monitoring, and managing AI/ML models and AI-enabled applications​​​​.
The model serving software stack, based on KServe, OpenShift Serverless, and OpenShift Service Mesh, encapsulates the complexity involved in networking, service configuration, autoscaling, and health checking for production model serving​​.

Enterprise-Ready Hybrid MLOps Platform: It is built as a single, consistent, enterprise-ready hybrid platform that is versatile for MLOps, aiding in the development and deployment of AI and ML applications​​.

Security and Reliability: The platform is designed to be secure and reliable, ensuring that the environments are not exposed to known security vulnerabilities​​.

Flexibility and Scalability: It is a flexible and scalable MLOps platform, supporting a variety of use cases and scales according to the needs of the organization​​.

Want to learn more? The Dell Validated Design for Red Hat OpenShift AI on APEX Cloud Platform offers organizations a simple and straightforward way to start getting value with GenAI by implementing a digital assistant. Click here to see the full validated design and here to learn more about APEX Cloud Platform for Red Hat OpenShift.