Today, Citrix and Microsoft announced that Azure Remote App will be deprecated, and a new version of Citrix XenApp on Azure will be the go-forward Cloud-based application virtualization offering. This is game-changing news within the virtualization industry, but what exactly does this mean for customers and the industry as a whole? Further, the timing of this announcement couldn’t be more relevant.
End User Computing
End User Computing (EUC) is the emperor’s new clothes. It is the new nomenclature for what used to be termed “VDI” (virtual desktop infrastructure). It is, however, much more, encompassing all aspects of desktop and endpoint management: (Read More)
- Application Virtualization: The art of abstracting the application and its presence from the desktop, making it truly mobile across locations and devices
- Personalization Virtualization: The art of abstracting the user and their presence from the desktop
- Presentation Virtualization: An application delivery method that delivers desktops or applications from a shared server
- Desktop Virtualization: The art of delivering a full desktop experience remotely
- Endpoint Management: The art of managing and securing access to data
- Application Layering: “on-demand” application delivery from a single image
End User Computing is an important overarching paradigm for companies that wish to ensure that users get a consistent experience and consistent access to information across multiple devices—for example, desktop computers, laptops, notebooks, tablets, and phones—and across disparate operating systems like Windows, Linux, iOS, and Android.
Major areas of focus include barriers to adoption, progress on the part of End User Computing vendors in alleviating those barriers, and management of the transition from a static desktop to the mobile martini world of “anyplace, anytime, anywhere, on any device.”
Microsoft is preparing to launch a new range of GPU-enabled virtual machines. Built using NVIDIA Tesla-series M60 and K80 GPUs, the new virtual machines offer the fastest GPUs available in the public cloud. This move leapfrogs Azure over AWS in both performance and number of supported platforms.
In my previous article, I introduced the idea of data locality in HCI. I also explored some basic math that illustrates the impact of scaling an HCI cluster. I compared a cluster without data locality to a cluster that does have locality. Today, I want to look at what happens when we need more than two copies of data, as well as to examine the impact of IO size on the storage network. My third article in this series will discuss the causes and effects of incomplete data locality, and it will also present a special case of data locality.
When VDI and DaaS were first introduced, many claims were made for their superiority over distributed desktops. They were cheaper, faster, more secure, easier to manage, etc. At the time, with few exceptions, these claims were no more than fantasy. Over the last few years, though, sufficient improvements in the core platforms and underlying infrastructure have brought some truth to most of these claims. Management tools have improved beyond measure. High-performance converged infrastructure appliances can deliver performance as good as or better than even that of the fastest desktops, and they do so at a cost that is less than that of a managed, enterprise-class desktop PC.
Thursday marked the closing of the 20th BriForum conference in Boston, Massachusetts, and the end of an era. As the largest independent virtualization industry conference, it’s a place where geeks explain how products really work (or don’t) and where unfiltered side-by-side comparisons are the norm.