Self-Learning, Predictive IT Analytics for CA Introscope

CA Introscope leads the market in depth and breadth of the application performance data. With a thousand IT metrics per JVM, however, it can be difficult for resource constrained IT teams to process the resultant millions of data points.

Tools teams have to determine which metrics are important, define appropriate thresholds and alert rules and then develop dashboards that facilitate a proactive workflow. When a problem occurs, one metric without a threshold set can mean the difference between an Application Support team spending hours or days on resolution.

Prelert applies the industry's most advanced Artificial Intelligence algorithms to Introscope data to self-learn the behavior and metric relationships of complex application environments. Tools teams spend much less time in configuration. Application Support teams get an 'out-of-the-box' intuitive dashboard.

Prelert identifies and provides root cause analysis of application problems as they develop and often before users are impacted.

Prelert Self-Learns Application Behavior

• Analyzes Introscope data in real-time
• Auto baselines individual metrics
• Self-learns relationships between metrics
• Discovers patterns of activity that define application behavior
• Identifies and often predicts problems
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• Distills millions of data points that are 'coincidental' to those related to the problem
• Provides the 'root cause analysis' narrative and supportive detail

Prelert reduces MTTR as much as 90% by helping users identify the cause of problems as they develop. It eliminates the need to define thresholds and alert rules and significantly reduces the workload associated with defining and maintaining dashboards.

Users get a highly intuitive dashboard out-of-the-box that distills mountains of data to the information they need to support critical complex applications.

Best of all, it's easy to deploy, leverages and strengthens your CA Introscope and minimizes your configuration and maintenance workload going forward.