Metafor’s unsupervised self-learning technology is enabling our customers to prevent security and performance problems while minimizing false positives and annoying alerts.
Portland, OR. (PRWEB) May 06, 2014
Metafor Software, a leading provider of real-time anomaly detection for IT security and performance, today announced it has been selected as a "Cool Vendor" in the Application Performance Monitoring (APM) and IT Operations Analytics (ITOA) report by Gartner, Inc.
Metafor’s innovative machine learning based anomaly detection technology can analyze thousands of metrics and events in real-time from virtually any data source. It automatically establishes what normal behavior looks like and uses advanced anomaly detection algorithms to accurately identify activities indicative of security threats or impending performance problems.
“We are excited and honored to be included in the Cool Vendor report by Gartner. This is clear confirmation of the importance of real-time anomaly detection for IT security and performance,” explains Jenny Yang, CEO of Metafor. “IT operations and security teams have a big data problem that traditional monitoring solutions can’t address. Metafor’s unsupervised self-learning technology is enabling our customers to prevent security and performance problems while minimizing false positives and annoying alerts.”
Metafor was chosen as one of five vendors profiled in Gartner’s 2014 Cool Vendors in Application Performance Monitoring and IT Operations Analytics report. Gartner defines a Cool Vendor as a company that offers technologies or solutions that are innovative, impactful and intriguing. According to Gartner, “The analytics capabilities provided by APM and ITOA providers can be applied to problem solving and the isolation of root causes in large volumes of unstructured data.”
In the report, Gartner evaluated Metafor’s machine learning based anomaly detection and alerting service, as well as Metafor’s configuration analytics module. Often behavioral anomalies are symptoms of an underlying environment anomaly. Metafor’s configuration analytics module automatically monitors change and configuration data in the server environment, detecting unwanted environment anomalies for accelerated root cause isolation.
Toufic Boubez, CTO at Metafor, is presenting at the Monitorama conference May 5-7, in Portland, OR. To arrange a meeting with Toufic, contact @tboubez or email info(at)metaforsoftware(dot)com
About Metafor Software:
Metafor’s machine learning technology analyzes the streams of real-time data generated by your IT infrastructure and applications to accurately identify anomalous behavior so you can fix problems at the first sign of trouble. It automatically establishes what normal behavior looks like and uses advanced behavioral analytics to identify activity indicative of security threats and impending performance problems. Metafor’s unique unsupervised self-learning algorithms use spatial context to know what normal is. This means that unlike most anomaly detection methods, Metafor doesn't require a training period or a continuous investment in re-modeling as various qualities of your data streams change. For more information, visit: http://metaforsoftware.com
Disclaimer: Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Gartner “Cool Vendors in Application Performance Monitoring and IT Operations Analytics, 2014” by Jonah Kowall, Will Cappelli, and Colin Fletcher, 28 April 2014.
Read the full report at: https://www.gartner.com/doc/2722217/cool-vendors-application-performance-monitoring-it-operations-analytics (subscription required).