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People often build New Year's resolutions around goals they have in their personal lives, such as spending more time with family, meditating daily or eating more vegetables.
The new year also provides an opportunity for people to reflect on their professional lives and find areas to improve. IT professionals might set goals to earn certifications or reform certain processes.
Along those lines, VDI administrators should seek out weak points in their organization's VDI management strategy.
Save time and money with thin clients
VDI allows organizations to use thin clients, stripped-down endpoints that often rely on server-based computing power and that come with a lower price tag than PCs or laptops. Thin clients can simplify VDI management.
The Google Chromebook, for example, is priced as low as $150 for certain models. The Chromebook only requires minimal provisioning and can automate patch and update deployments, as well as performing security audits and automatic reboots when the device detects suspicious behavior. These local management functions can save IT pros from handling these tasks, which frees them up to focus on other critical jobs.
Other thin clients from vendors such as Dell, Lenovo and HP range in functionality and price. On the high-priced end, there is HP's mt42 thin client that costs more than $1,000, can run Windows 10 IoT Enterprise and offers multimedia redirection. For bargain hunters, Raspberry Pi thin clients cost only $30, but these devices need some hardware add-ons, such as memory cards and monitors, to function as effective endpoints.
Trust AIOps to simplify management
To ease VDI management in 2019, IT professionals can trust AI for IT operations (AIOps) -- a broad term for AI in the context of helping IT pros identify and fix problems -- to manage storage, monitor resource usage and more. VDI vendors such as Citrix and VMware have incorporated AIOps into Citrix Analytics and VMware Workspace One Intelligence respectively.
AIOps can detect and respond automatically to problems such as desktop delivery disruptions, storage failures or security breaches. By taking immediate action to address these types of problems, AIOps relieves some of the VDI management burden on IT. In addition, this automated response by AI puts out the fire so IT can investigate the source of the problem and ensure that the issue doesn't happen again.
Machine learning, which uses algorithms to improve the accuracy of predictive software without specific programming directions, can help detect VDI issues. The longer a VDI platform runs, the more time it has to gather data for machine learning and to correlate data from applications, desktops and devices. The platform can then apply this data to improve an organization's workflows, identify and anticipate security issues quicker, and provide recommendations on how to improve a VDI deployment.
Machine learning can improve VDI workflows and management over time as it continually gathers more data. The improvements enhance the user experience and help IT pros manage VDI more effectively.
Understand that one size does not fit all
Treating all end users the same way can create issues for users and IT alike. In 2019, IT must tailor its VDI architectures to its users' specific needs.
There are many subtle needs that differentiate users. For example, a network supporting VDI for a large number of remote users may need additional hardware or new hardware altogether to address the needs of different users. In some cases, IT pros should change the architecture of VDI to include edge computing technology, which improves remote users' desktop performance by moving processing closer to users and at the periphery of the network.
Admins should also factor user type into their VDI management strategy. IT can categorize users based on the tasks they run. Task and kiosk workers only run a basic app or two, such as a web browser, but other workers run multiple apps that require plenty of processing power, such as video editing software.
Users who run resource-intensive applications are called power workers, and IT pros must ensure that their endpoints have access to the resources they need to run those more complex applications. One way to do so is to add graphics processing units -- hardware that improves a device's graphics processing by taking the task off of the CPU -- to the deployment. Otherwise, power users could experience significant performance issues.
By identifying which users need which resources, IT can not only avoid under-provisioning resources, but also overprovisioning them. Overprovisioning resources can make costs skyrocket because IT ends up spending money where it doesn't need to. IT should accurately provision VDI resources, including IOPS.
Vendor provisioning recommendations often go overboard because the vendors don't factor in efficiency -- only guaranteed performance. To be accurate, IT professionals should run their own tests to ensure that VDI is running efficiently.