Prelert announced Anomaly Detective, an advanced machine intelligence solution for Splunk Enterprise environments.
The introduction of Anomaly Detective expands Prelert’s line of diagnostic predictive analytics products that integrate with a customer’s existing IT management tools and quickly provide value by finding problematic behavior changes hidden in huge volumes of operations data.
Anomaly Detective’s self-learning predictive analytics with machine intelligence assistance recognize both normal and abnormal machine behavior. Using highly advanced pattern recognition algorithms, Anomaly Detective identifies developing issues and provides detailed diagnostic data.
IT personnel who utilize Splunk Enterprise software in infrastructure, applications performance and security can now additionally benefit from machine learning to automatically spot anomalies and isolate their root causes in minutes, saving time and resolving problems before the business is impacted.
Anomaly Detective is easily downloadable software that installs and provides value in minutes as a tightly integrated application for Splunk Enterprise. Because it leverages recent advances in machine intelligence, Anomaly Detective is 100 percent self-learning and requires minimal configuration.
Anomaly Detective augments existing IT expertise, empowering IT staff to spend less time mining data, reduce troubleshooting costs and improve compliance with service-level agreements — all of which contribute to a rapid return on investment.
“Prelert Anomaly Detective is like a machine intelligence assistant, using advanced machine learning analytics to analyze the massive amounts of IT operations management data produced by today’s online applications and services,” said Mark Jaffe, CEO of Prelert. “We’ve packaged the power of big data analytics, normally focused on solving business problems, in easy-to-use machine intelligence solutions that are greatly needed in the real world of IT operations.”
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