Automatic z/OS Health Assessments to Avoid Service Disruptions

 

Even without the increasing complexity of the infrastructure, the growing multitude of available metrics, or the already critically low staffing levels, it would still take an army of experts to assess the health of the entire infrastructure every single day.

Under the best of circumstances, an experienced analyst knows the key metrics and areas to check for likely issues or has decades worth of SAS/MXG code to help with this endeavor. But that is neither scalable, nor transferrable to the next generation.

Machine intelligence designed correctly has a deep understanding of the system and can do all the computing, analyzing, normalizing, and prioritizing automatically. This enables experienced and novice performance analysts to efficiently and effectively resolve problems before they occur.

 

This video is an excerpt from the webinar, “RMF/SMF Analysis – Get Ahead of the Curve with Statistical Analysis.”

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