Most IT organizations are rich with operational data – collected from networks, servers, applications, storage, databases and more. However, a lot of this data sits unused because there’s simply too much of it to analyze. Just as difficult as finding the needle in the haystack, finding IT problems remains as a challenge for IT staffs.
Prelert recently announced a solution that helps IT staffs find the IT operations “needles in the haystack”, which it calls Anomaly Detective for Splunk environments. By applying Big Data analytics to IT operations data, Anomaly Detective first learns what is normal behavior so it can identify abnormal behavior when and where it happens.
Anomaly Detective for Splunk environments
Prelert’s app for Splunk environments leverages the wealth of IT data that Splunk collects from various data sources. Prelert applies advanced analytics to the data to determine “normal behavior” patterns so it can identify behavioral changes that may point to operational and security issues. The key to Prelert’s approach is using machine intelligence to sift and filter through mounds of IT data to identify abnormal behavior or anomalies, so it can predict potential operational problems. Then IT staffs can focus on investigating and resolving the predicted problems before they escalate into bigger issues.
Click here to read more: Prelert’s IT Operational Analytics for Splunk
Authors: Audrey Rasmussen and Rich Ptak