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Maintaining Valuable Mainframe Data made Easy With Splunk Ironstream

Earlier, IT management teams had to establish technologically advanced and costly software to run their mainframes better. For instance, as Mainframe operational is essential for IT teams, perhaps maybe more essential in terms of performance and operational data for the rest of the infrastructure and application. The Mainframe is commonly utilized by IT organizations to host the mission-critical and most vital applications.

But finally, new insights are changing the IT professionals’ way of operations, and this made possible with the introduction of the latest edition Syncsort’s Ironstream to Splunk platform.


In Splunk Cloud and Splunk Enterprise, Ironstream helps IT professionals and already joined customers to Syncsort to collect envision as well as report on log data of Mainframe. This rich machine data of mainframe source consist of z/OS log files, for example- WebSphere Log4j, various SMF records, Syslog, etc.


There are many positive effects to analyze the mainframe data amongst all other automation sources of data in Splunk software. With all the data in one spot now, one can significantly reduce the time for the resolution that was very stretched before, proactively track both distributed systems and Mainframe, optimize application execution and functionality with valuable information from the underlying network, and strengthen protection.

Ironstream’s mainframe data model makes it uncomplicated to work with multifaceted mainframe metrics in Splunk

In the comprehensive Splunk network view, highly valued mainframe data is often absent. But if you’re not a mainframe professional, it can be quite problematic to realize which data sources, fields, and complex calculations are required to get desired results within Splunk. Even those who were experienced with Mainframe and had extensive knowledge still had to struggle.

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But with Ironstream, now one can easily capture the needed components in real-time–and Ironstream’s latest Mainframe Data Model turning it much easier to deal with highly complicated mainframe measurements in Splunk.

Although, this on-demand new feature also helps to:

  • See classified mainframe indicators in ways that are easy to understand.
  • Provide results much faster –no data sources, fields, and computations need to be researched.
  • Widen exposure for more team members, and no specific mainframe experience is required.
  • Using Splunk, built-in software enables us to move on easily.
  • Altogether remove the mainframe blind spot and understand significant ROI early.

You can also begin to gain operational insight from end-to-end to crucial mainframe activities, failed transactions troubleshooting, monitoring transactions through the business network, knowing the structure of capacity planning, testing the user’s mainframe log-in to change control, or detecting security issues, just to list a few. So this is how Splunk brought easiness to maintain the valuable framework.

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