Microsoft Research Predicting Problems in the Data Center

Microsoft posts on its Techfest event and Predicting Problems in the Data Center.

Moises Goldszmidt (above), principal researcher at Microsoft Research Silicon Valley, is showing a pair of demos, in conjunction with lab colleague Mihai Budiu, that examines performance in data centers.

"The challenge," Goldszmidt says, "is: How do I summarize thousands of machines and hundreds of metrics and find the key elements over that huge space that's giving us surprises, such that I can let it retrieve that fingerprint? How do I do that automatically?"

The demo is called Predicting Problems in the Data Center.

"We are using very sophisticated machine-learning techniques," Goldszmidt states, "that build automated models that are able to extract the main characteristics of each one of these crises."

The value of such work is readily apparent.

"Eighty percent of the time, we're predicting one hour in advance a set of actions we need to do to mitigate a problem," he says, resulting in "less downtime, less latency for our clients using our services. Our services are more efficient to run, because we don't have to have that many people look at the problem."