AIOps platforms enhance IT operations by combining big data, machine learning and visualization to create actionable insights. The top use cases for AIOps tools include intelligent alerting (69 percent), root cause analysis (61 percent), and anomaly detection (55 percent), according to one survey conducted for OpsRamp.
The survey found the three biggest advantages of using AIOps tools are productivity gains from the elimination of low-value, repetitive tasks across the incident lifecycle (85 percent), rapid issue remediation with faster root cause analysis (80 percent), and better infrastructure performance through reduction in incident and ticket volumes (77 percent).
With modern machine learning technologies, 40 percent of organizations fixed incidents 26 percent-50 percent faster, 37 percent reduced mean time to resolve by 51 percent to 75 percent while 10 percent brought down overall incident resolution times by more than 76 percent, OpsRamp says.
Compared to more traditional monitoring tools, AIOps seeks to reduce noise (false alarms or redundant events), capture anomalies on a dynamic basis, provide a better causality trail, to help identify incident causes, then extrapolate to future events and take actions to resolve problems, either automatically or with IT staff approval.
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