The cost of VDI is the single most important factor in any customer conversation:
- Rapidly rising cost of software licensing for both the server and VDI components
- Most VDI infrastructure is sitting idle 85% of the time
- The high cost of cross-functional server, storage, networking, server virtualization, desktop virtualization teams to operate VDI
- The high cost of support for VDI
For this blog post, we will focus on how AI helps Workspot DaaS on Amazon WorkSpaces Core optimize the cost of infrastructure.
Optimize Cost of AWS
In an on-premises VDI deployment, the infrastructure sits idle 85+% of the time. Why? It’s simple.
- Most users work 40 hours out of a 144 hour work week (27% of the time)
- Infrastructure has to be provisioned for peak usage which may happen at 11am on Monday morning
On AWS, you don’t need to operate a user’s virtual desktop 24×7. Our research shows that an average full time employee uses their desktop 120 hours in a month and an average contractor uses their desktop 60 hours in a month (out of 720 hours in a month). With AI, we can provision a user’s virtual desktop on Amazon WorkSpaces Core just-in-time, and we can provision just-enough desktops so that users are not waiting to log in, thereby matching cost to usage curves as closely as possible. With these AI-driven optimizations, the focus shifts to $/hr models which can be billed to business units with tagging.
