Intel AMX accelerated Multicloud GitOps with Openshift AI

Organizations are aiming to develop, deploy, and operate applications on an open hybrid cloud in a stable, simple, and secure way. This hybrid strategy includes multi-cloud deployments where workloads might be running on multiple clusters and on multiple clouds, private or public. This strategy requires an infrastructure-as-code approach: GitOps. GitOps uses Git repositories as a single source of truth to deliver infrastructure-as-code. Submitted code checks the continuous integration (CI) process, while the continuous delivery (CD) process checks and applies requirements for things like security, infrastructure-as-code, or any other boundaries set for the application framework. All changes to code are tracked, making updates easy while also providing version control should a rollback be needed. Moreover, organizations are looking for solutions that increase efficiency and at the same time reduce costs, what is possible using 5th Generation Intel Xeon Scalable Processors with a new build-in accelerator - Intel Advanced Matrix Extensions.

An enterprise-ready Kubernetes container platform built for an open hybrid cloud strategy. It provides a consistent application platform to manage hybrid cloud, public cloud, and edge deployments. It delivers a complete application platform for both traditional and cloud-native applications, allowing them to run anywhere. OpenShift has a pre-configured, pre-installed, and self-updating monitoring stack that provides monitoring for core platform components. It also enables the use of external secret management systems, for example, HashiCorp Vault in this case, to securely add secrets into the OpenShift platform.

A declarative application continuous delivery tool for Kubernetes based on the ArgoCD project. Application definitions, configurations, and environments are declarative and version controlled in Git. It can automatically push the desired application state into a cluster, quickly find out if the application state is in sync with the desired state, and manage applications in multi-cluster environments.

Controls clusters and applications from a single console, with built-in security policies. Extends the value of Red Hat OpenShift by deploying apps, managing multiple clusters, and enforcing policies across multiple clusters at scale.

Provides an enterprise framework for building and operating IT automation at scale across hybrid clouds including edge deployments. It enables users across an organization to create, share, and manage automation, from development and operations to security and network teams.

A flexible, scalable MLOps platform with tools to build, deploy, and manage AI-enabled applications. OpenShift AI (previously called Red Hat OpenShift Data Science) supports the full lifecycle of AI/ML experiments and models, on-premise and in the public cloud.

The Operator includes OpenVINO™ Notebooks for development of AI optimized workloads and OpenVINO™ Model Server for deployment that enables AI inference execution at scale, and exposes AI models via gRPC and REST API interfaces.

A new built-in accelerator that improves the performance of deep-learning training and inference on the CPU and is ideal for workloads like natural-language processing, recommendation systems and image recognition.

Provides a secure centralized store for dynamic infrastructure and applications across clusters, including over low-trust networks between clouds and data centers.