What Is The Value Of Mainframe Operational Data?

In this whitepaper, we unpack the importance of logs analysis. Learn about the types of information mainframe managers can gain from analyzing mainframe logs and how this information can be used to manage resources, control the budget, and inform future z/OS optimization efforts. 

Mainframe Storage Analytics Has Never Been Easier

Performance bottlenecks, system configuration issues, and chargeback information — all of this and more can be understood at a greater efficiency through storage analytics software.

Why Is Collecting Mainframe Data So Hard?

All too often businesses overlook the value of SMF records, because they simply don’t know how to collect them in an efficient, affordable way. Important mainframe optimization opportunities pass them by as they struggle to analyze SMF records.

Leverage Machine Learning For Mainframe Operations

Accessible, affordable, automatic, and, best of all, actionable — machine learning helps IT teams gather and analyze mainframe performance data and turn this insight into optimization opportunities.

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Leverage Storage Analytics To Improve Mainframe Performance

Whether you’re a storage expert who feels overwhelmed by high volume and complexity, or a mainframe manager looking to gain a competitive edge, storage data offers new ways to understand a mainframe system. Performance bottlenecks, optimization opportunities, system configuration issues, and chargeback information — all of this information and more can be uncovered through storage analytics.

Streamline ITOA With Machine Learning

Machine learning can learn your mainframe environment faster than any one human ever could. By running behind the scenes, machine learning refines its insights with every data point and contextualizes raw figures into actionable improvements.

What is the ZETALY difference?

Analyzing mainframe logs for ITOA purposes is not new but doing it simply is and that’s where the ZETALY difference lies.

Improve Mainframe Optimization Through Automated Logs Collection

Relevant, specific, and up-to-date data — these are the three criteria necessary for performing mainframe optimization. And yet, what seems fundamental in theory is actually nearly impossible to gather in practice. Why is it so hard to collect actionable mainframe data?