StarWind Virtual SAN (VSAN) Integrations

Hyper-V is Microsoft's hardware virtualization product. It lets you create and run a software version of a computer, called a virtual machine. Each virtual machine acts like a complete computer, running an operating system and programs. When you need computing resources, virtual machines give you more flexibility, help save time and money, and are a more efficient way to use hardware than just running one operating system on physical hardware. Each supported guest operating system has a customized set of services and drivers, called integration services, that make it easier to use the operating system in a Hyper-V virtual machine. Hyper-V includes Virtual Machine Connection, a remote connection tool for use with both Windows and Linux. Unlike Remote Desktop, this tool gives you console access, so you can see what's happening in the guest even when the operating system isn't booted yet.

Take your server virtualization platform to the next level. XenServer 8 is now supported for production use, including Windows 11. Transition from Citrix Hypervisor to XenServer, on us! XenServer is now an entitlement of the Citrix for Private Cloud, Citrix Universal Hybrid Multi-Cloud, and Citrix Platform License subscriptions for running your Citrix workloads. Citrix customers that have not yet transitioned to these new subscriptions can participate in our special promotion and receive 10,000 XenServer Premium Edition socket licenses for free.

Get the power of the enterprise workload engine. Boost workload performance, improve security and speed up innovation for your business. vSphere delivers essential services for the modern hybrid cloud. The new vSphere has been rearchitected with native Kubernetes to run existing enterprise applications alongside modern containerized applications in a unified manner. Transform on-premises infrastructure with cloud integration. Boost productivity with central management, global insights and automation. Power up with add-on cloud services. Meet the throughput and latency needs of distributed workloads by accelerating networking functions on the DPU. Free up GPU resources for faster AI/ML model training and higher complexity models.