How Cisco uses Zebrium ML to Analyze Logs for Root Cause

In this detailed study of 192 actual customer Service Requests, Zebrium’s machine learning was able to correctly identify the root cause in 95.8% of the cases. User feedback praised the quality of the root cause reports and experienced significant time savings compared to manual log analysis.

The Cisco Technical Assistance Center (TAC) has over 11,000 engineers handling 2.2 million Service Requests (analogous to incidents or support cases) a year. Although 44% of them are resolved in one day or less, many take longer because they involve log analysis to determine the root cause. This not only impacts the time a case remains open, but at Cisco’s scale, translates to thousands of hours spent each month analyzing logs.

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