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ExtraHop Co-founder Raja Mukerji. (ExtraHop photo)

Last October, when a series of distributed denial of service (DDoS) attacks knocked out major websites like Amazon and Twitter, one financial firm was prepared.

The company was an early tester of Addy, a new product from Seattle IT Analytics company ExtraHop. Using Addy, the financial firm was able to detect the attack in real-time and route traffic on the affected server through a different region to avoid downtime.

ExtraHop designed Addy as a first line of defense in situations like the DDoS attack, as well as an insights portal across an organization’s IT operations.

The technology observes all digital interactions happening within a network and uses machine learning to look for anomalies and potential issues.

“Addy is about bringing insights to our users so that they can make data-driven decisions and this has significant implications for our customers in terms of performance management, in terms of security, as well as business intelligence,” said Raja Mukerji, ExtraHop’s Chief Customer Officer and Co-Founder. “It’s not forensic anymore. The old methods of gathering locked files and gathering things and trying to churn on them in retrospect and glean insights after the fact, it’s no longer good enough.”

ExtraHop’s Addy tool.

Addy will be available starting at $2,990 a month beginning in April. It’s one of the first big product rollouts since Arif Kareem took the helm as CEO of ExtraHop last July. It was one of many big moves for the company in 2016, including expanding into the Asia-Pacific region, growing to more than 500 enterprise customers, and expanding to just over 300 employees.

Since 2007, ExtraHop has been building real-time IT analytics products for companies like Adobe, Lockheed Martin, and Sony.

“I think this is absolutely the natural evolution for the company,” said Mukerji. “We have always been a company that has prided itself on bringing insights to our customers … ExtraHop has been all about taking huge amounts of information and bringing insights to our end users. Machine learning is a natural fit for that.”

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