Funding rolls in as the Texas startup prepares to enter beta testing for its innovative management appliance.
Startups looking for venture funding in this economic climate find it tough going. One new startup, however, managed to come away with another $15 million in second-round funding in three months time, bringing its total to $39 million.
Vieo Inc., an Austin, Texas, startup focused on the applications management space, yesterday announced its new funding round as it prepares to enter beta testing for its management appliance.
The company is pursuing a different strategy when it comes to what officials call adaptive applications infrastructure management (AAIM). It has created a high-performance management appliance that sits in the data pathrather than outside it as a passive observerto measure, analyze and dynamically affect the application environment in real time to insure quality of service, according to Bob Fabbio, founder and CEO of Vieo.
Fabbio, who founded Tivoli Systems, pulled together a number of Tivoli alumni to lead the startup.
The high-speed management appliance provides the connectivity to link to all the entities that need to be managed in the application environment.
"For years software solutions sat outside the application environment and tried to probe into the tiers of an application. They put a tax on the environment," described Fabbio of existing management tools. "Our approach is to get off the sidelines and be part of the application environment, see everything in real time and really affect the resources that allow organizations to satisfy quality of service expectations," he added.
The appliance, with up to 200 Ethernet ports, can see every packet between all peers in the environment and perform "sophisticated analysis on whats going on and make adjustments," Fabbio added.
In order to capture and analyze high-speed data flowing through the appliance, Vieo incorporated proprietary chips and switches capable of moving hundreds of megabytes of data through it.
The appliance can automatically discover the applications environment and send agents out to end systems if necessary. It watches behavior patterns in the applications environment over a period of days to model it and predict application quality of service deviances from the norm. End users only have to identify which transactions are important to watch.
Beta testing for the AAIM appliance begins at the end of this quarter. It is expected to ship by mid-year.