SAP on Red Hat OpenShift Virtualization

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So you want to install your SAP workload on Red Hat OpenShift? The good news is that it’s technically possible. The bad news is that it’s not supported by SAP for production workloads. But assume for a moment that you want to install a development or training or demo system. In that case, you can run your workload in a traditional virtual machine (VM) using OpenShift Virtualization. You want the setup and tuning to be done automatically? There are Ansible roles to cover that. First, of course, you need an OpenShift cluster. If you don't already have one, read Installing a user-provisioned cluster on bare meta to learn more about how to set one up, or you can get one from your preferred cloud provider. You can also automate the install. What is OpenShift Virtualization? OpenShift Virtualization is a feature of OpenShift that enables you to run and manage both virtualized and containerized workloads together within the Kubernetes-based OpenShift environment.

Developed by Red Hat, OpenShift Virtualization provides the ability to unify diverse workloads by allowing you to deploy and manage traditional virtual machines alongside containerized applications. This integration helps you leverage the benefits of both virtualization and containerization, providing better optimized resource utilization, scalability, and flexibility in your IT infrastructure. OpenShift Canada Mobile Database Virtualization is designed to help simplify the management of mixed workloads, offering a more consistent and efficient solution for running applications across various deployment models within the OpenShift application platform. Configuring the OpenShift cluster Your worker nodes must all be identical, with the same amount of RAM, CPUs, disks, and network cards. The network cards must be in the same PCI slots as the ports, which must be named identically. Let’s take a look at this in action. Red Hat and Intel private 5G for Minsait Minsait, an Indra company, has taken the joint solution from Red Hat and Intel to market and has already seen the benefits in multiple edge- and AI-enabled use cases including: Wind farm wildlife and fire detection: helps wildlife protection in wind farms while significantly reducing operating costs. Through AI, it can detect protected birds and make real-time decisions to avoid collisions.



Another feature includes the early and reliable detection of wildfires or nearby incidents through artificial vision. Logistics and asset management with indoor drones: this has allowed for a new logistics and asset management system that is connected, flexible and versatile. Based on the implementation of a new industrial drone, this system is intelligent and capable of working collaboratively in an indoor environment, safely alongside humans. This system provides asset search, inventory management and traceability, with the capability to scale with new features. This solution can also enable a fleet of intelligent mobile devices to operate continuously and autonomously with no action required from the system operator. Oil spill response management: the deployment of private 5G in oil refineries or on offshore platforms and ports helps provide better maintenance for these remote facilities, helping provide security capabilities in critical infrastructures aided by cameras and AI algorithms that can be supported by drones or robots. It can also help detect oil spills at port entry using intelligent algorithms and data collection from sensors, radar and infrared cameras deployed along the port area reducing possible hazards or accidents.