How AIOps is transforming mainframe performance

It’s an open secret that an organisation’s IT infrastructure can make or break critical business operations. This is especially true for mainframes, which continue to play a central role across countless sectors – finance, healthcare and manufacturing, to name a few.

 

Ensuring these systems operate at peak performance is paramount. Yet, as environments become more complex, the demand for solutions that proactively manage and optimise mainframes has never been greater. Fortunately, that’s where the power of artificial intelligence (AI) can come into play.

 

By leveraging advanced analytics and AI for IT operations (AIOps), organisations can identify potential risks and opportunities, and make better, more informed decisions to keep their mainframes running smoothly.

 

The evolving challenges of mainframe management

 

Mainframes, while often perceived as “legacy” systems, remain indispensable to the modern enterprise. Consider this: 45 of the top 50 banks and 67 Fortune 100 companies use a mainframe as their core platform.  

 

Simply put, these systems are responsible for processing vast amounts of data and supporting critical applications that demand both stability and innovation. However, managing these complex environments has its obstacles: 

• Disparate tools can hinder performance analysis, preventing teams from efficiently sharing data and responding to alerts 
• Preventable incidents can go undetected without comprehensive observability, resulting in costly business disruptions
• A mainframe skills gap, compounded by burnout and employee turnover, can challenge organisations to keep teams staffed with the requisite expertise

On the bright side, the skills gap is steadily closing. According to a study by the Futurum Group, 91 per cent of surveyed companies plan to hire new mainframe talent in the coming years, further emphasising the technology’s lasting significance. Per the same research, universities report a growing pipeline of mainframe professionals.

 

Yet the other challenges are no less relevant. In this context, organisations must look beyond traditional methods of monitoring and troubleshooting to more intelligent, AI-powered solutions that can help them optimise performance, address costs and improve system resilience.

 

At IBM, we provide a robust framework to meet these demands. By integrating observability, machine learning and intelligent automation, the IBM Z AIOps portfolio can empower businesses to not only address issues but also uplift mainframe performance for continuous optimisation.

 

Enhancing mainframe efficiency with the power of AI

 

In April 2024, we announced the addition of IBM Z® IntelliMagic Vision for z/OS® into our AIOps portfolio. As a comprehensive platform, it offers AI-driven performance analysis and monitoring capabilities specifically designed for mainframe environments.

 

At its core, IntelliMagic Vision aims to provide proactive end-to-end visibility into z/OS operations. This helps teams identify potential issues to address them before they impact service levels or put critical processes at risk. With built-in anomaly detection and intelligent insights, the solution helps organisations to evolve from reactive to proactive performance management.

 

Furthermore, the platform’s interactive and intuitive interface allows users to drill down into critical metrics, designed to make it easier for both seasoned professionals and newer team members to understand and act on key performance indicators. The result? It’s built for less downtime, enhanced risk management and stronger business continuity.

 

Cutting-edge capabilities

 

IBM Z IntelliMagic Vision for z/OS continues to evolve, with new features designed to empower organisations to further optimise their mainframe environments. Some of our most recent updates include:

 

Performance analysis by business application

 

This feature helps organisations track resource consumption across different applications, providing crucial insights into cost drivers and operational efficiency. By mapping workloads based on attributes such as job names, service classes and transactions, teams can now easily monitor CPU usage at a more granular level.

 

This capability proves invaluable for upper management reporting and cost allocation, as it allows organisations to track who is consuming resources and how these resources are being used. Furthermore, it provides the ability to compare performance before and after an application change, offering critical data on the impact of modernisation efforts.

 

Information Management System (IMS) support

 

As of now, IntelliMagic Vision offers support for IMS transactions. IMS is integral to many business-critical operations, and having access to proactive visibility into its performance is essential for ensuring smooth operations. Crucially, this capability allows organisations to monitor key metrics such as CPU usage, response time and transaction volumes.

 

With this feature, businesses can quickly identify bottlenecks or performance issues within IMS workloads, built to accelerate root cause analysis and enable faster remediation. This visibility positions teams to address issues likely to impact service levels while quickly answering analytical questions.

 

A vision for the future

 

IntelliMagic Vision for z/OS plays an essential role in the IBM Z AIOps framework by helping organisations detect, decide and act with complete clarity. Through intelligent automation and unprecedented visibility, mainframe analysts can optimise system performance and mitigate the challenges of the modern IT landscape.

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For more information, explore how IBM Z IntelliMagic Vision for z/OS can transform your organisation’s mainframe analysis today