First is to improve application performance. If application X performs better than you’re able to sell more products and services. Analyzing performance datasets from SAN to OS to DB to middleware to CE allows the operations teams to better understand and resolve performance problems. The advancements in these tools finally make it possible to do this in real-time.

Second is to reduce the amount of time spent adjusting thresholds manually for performance metrics. The self-learning analytical tools improve the threshold management and the result is time saved.

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Although the “sexy” part of the real time analytics solution’s capabilities is the proactive/predictive stuff, there are other capabilities that can make a big impact for an Ops team. For example, simply understanding the normal behavior of your infrastructure can significantly improve the problem resolution process. It automates a lot of the manual work that goes into sifting through siloed monitoring alert storms trying to figure out which alerts are relevant to the current problem and which are not. It eliminates false positives related to normal behavior obscured by static thresholds and uncovers real problem precursor behavior. These solutions can also provide an understanding of how infrastructure components are related to user experience and business performance. This information can be used to build an adaptive Performance Management Database (PMDB) that helps identify performance relationships between IT infrastructure components much like a CMDB defines their physical relationships. You can get reports that show you the top infrastructure influencers of business performance and user experience key indicator (KI) breaches. Rather than using tribal knowledge to address problems, you have a map that indicates what to look for based on actual performance. Additionally, capturing models of the abnormal behaviors that lead to KI breaches provides a forensics capability that can pinpoint root cause of problems much more efficiently tha getting a representative of every silo on a bridge call. None of the things I’ve mentioned here are about prediction or proactive alerting, these capabilities are about providing the intelligence that fuels improved troubleshooting efforts. The focus in the press and analyst community on the nirvana of predictive alerting (and the challenges) sometimes diverts attention from other capabilities of real time analytics solutions that can provide tangible, measurable increases in efficiency to existing performance management processes through increased intelligence.