Mainframe Blog AIOps Blog

Put Machine Learning to Work in Your Mainframe

Alan Warhurst
2 minute read
Alan Warhurst
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As modern IT environments grow more complex, that complexity is also extending to the mainframe. Systems of engagement and systems of record are working more closely together, which can complicate the delivery of 24 x 7 availability to internal and external customers.

Always on isn’t optional

Getting ahead of issues before they become problems is now a make-or-break determinant for business success, so it’s fantastic timing that artificial intelligence (AI) and machine learning (ML) are making inroads into IT operations management (ITOM) with AIOps, a blended artificial intelligence for operations approach that combines applied data science, domain expertise, and multivariate analysis into one comprehensive solution that:

  • Reduces noise and false positives
  • Detects performance degradations and service disruptions
  • Delivers actionable insights that accelerate troubleshooting and guide resolution
  • Allows mainframe teams—at any level of expertise—to identify and solve emerging problems even before they impact customers

And that “before” is key—you don’t want to be the cautionary tale who only finds out your systems are hiccupping after unhappy customers start lighting up social media with screengrabs of timeout errors. If your teams could proactively head issues off at the pass, they could instead focus on more strategic projects like planning for the future.

BMC AMI Ops Insight

You can put advanced ML technology to work for your mainframe with BMC AMI Ops Insight. The solution predicts issues before they become problems that degrade systems and trigger outages. Actionable insights speed up mean-time-to-repair (MTTR) with faster troubleshooting, resolution, and restoration by providing granular details about the issue and its severity, location, point of origin, and current state. The mainframe team yields value on two fronts—actual problems are identified with less noise and fewer false positives, and staff at all levels are empowered to confidently make business-critical decisions by understanding which metrics to watch and how they correlate.

Conclusion

In a business climate where time is money, and downtime can dent your profits and reputation, every moment counts. By applying AI and ML to ITOM, issues can be identified before they become those very expensive problems—and you keep your employees and customers happy across the board. To learn more about using these technologies to deliver more strategic value to your business, see our whitepaper, Making Machine Learning Work for Your Mainframe.

Making Machine Learning Work for Your Mainframe

Machine learning is transforming mainframe operations. By getting actionable insights to solve emerging problems before they impact service, even less-experienced team members can keep the complex mainframe environment running at its best.


These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

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About the author

Alan Warhurst

Alan Warhurst

Alan Warhurst has been in the IT industry for 20 years and at BMC since 2014. He is currently a Senior Manager Product Management in the ZSO organization responsible for the Storage Management products as well as future strategy and direction. He also has special responsibility for the Mainframe Executive Council and BMC's Annual Mainframe Survey.

Alan previously spent many years working in the logistics industry in a variety of roles, including System’s Programmer, Data Center Manager, Head of Application Platform Support and Infrastructure Architect.