WVD delivers virtual desktops and apps seamlessly from Azure that can be accessed anywhere anytime and from any device
Cognizant WorkNEXT Cloud Workspace – Windows Virtual Desktop offering includes professional services for WVD with consulting, assessment, design & Implementation combined with our industry-proven managed services support. Our solution encompasses both Microsoft native as well as hybrid model with Citrix Workspace.
Cognizant’s WVD offering will help you to plan & execute the adoption of WVD into your current IT environment or migrate from your existing on premise VDI infrastructure to cloud workspaces.
Cognizant’s WVD also offers a fast track production WVD deployment due to the prevailing COVID-19 emergency. Customers can leverage the fast track WVD deployment program to deploy 100-500 WVDs in up to 4 weeks.
The WVD fast track program includes fast track design and WVD deployment with base applications included in the Win 10 master image. Customers will be able to dynamically scale the Windows Virtual Desktop platform later, enabling them to respond to urgent demand for work from home scenarios.
Cognizant understands changing the complete desktop environment of an enterprise is a big undertaking and that’s why we offer a Proof of Concept with free Azure credits to begin with, to judge if the Virtual desktops solution delivers business and technical value against your needs. Once the business value is evident, then we can scale it up to drive long-term business impact.
Cognizant’s phased approach for a smooth transition to a complete Windows Virtual Desktop environment: Phase 1: Assessment - Assess existing environment to understand current user landscape Phase 2: Design – Design secure and resilient WVD Azure environment Phase 3: Build – Build and deploy user-persona based WVD host pools and Win 10 images Phase 4: Migration – Phased migration to the new WVD environment, which includes change management and user training Phase 5: Managed Support – Monitor and manage the health of the solution as well as continued optimization