Many of the world's transactional workloads run on the mainframe. Organizations face a critical challenge: helping ensure the availability of workloads and an infrastructure that supports essential business applications. Many enterprises report two major challenges: an overwhelming volume of data to process and too many tools with disjointed user experiences.

The mainframe does not operate in isolation. You must navigate integration complexity between IBM Z and distributed cloud environments. This complexity often prevents end-to-end observability and makes it difficult to meet service-level goals.

This IBM Redbooks® publication addresses a common question: How can you simplify mainframe operations? To answer this question, this IBM Redbooks publication draws on Lean Thinking, which focuses on identifying waste (muda) and strain (muri) in any process. Waste includes manual data gathering, redundant steps, and fragmented tools. Strain refers to the difficulty of identifying root causes from large volumes of data.

By applying artificial intelligence (AI) and machine learning (ML) technologies to mainframe operations, you can improve efficiency (reduce muda) and effectiveness (reduce muri).

For example, AI-powered solutions detect operational anomalies, correlate them, and guide you with expert advice to take the next best action, without requiring you to sift through multiple tools and datasets. Proactive performance analysis replaces reactive troubleshooting, helping you address issues before they affect business. With enhanced visualization, open standards such as OpenTelemetry, and real-time system health insights, you gain actionable intelligence for both immediate decisions and long-term planning.

Generative AI-based assistants and agents streamline and automate tasks, transforming how you interact with the mainframe. Natural language interfaces simplify complex processes, making operations more intuitive and productive for users at all experience levels. This modernized approach improves efficiency and reliability across your environment. This IBM Redbooks publication provides best practices to help you simplify mainframe operations.

If you are a mainframe leader or CTO, this IBM Redbooks publication provides a comprehensive overview of the Artificial Intelligence for IT Operations (AIOps) landscape on the mainframe, required capabilities, and available solutions. You learn how these solutions work together to deliver secure, robust, efficient, and simplified operations, despite the challenges mainframe organizations face today. To explore these challenges and key capabilities, see Chapter 2, “Challenges” and Chapter 5, “Where to start” through Chapter 7, “Conclusion”.

If you are an IT operator or subject matter expert (SME), this IBM Redbooks publication helps you understand the diverse capabilities that are required in IT Operations (ITOps). You explore key operational areas and learn why each capability matters. Chapter 3, “Artificial Intelligence for IT Operations capabilities” and Chapter 4, “Simplifying mainframe operations” provide deeper insights into monitoring and observability, performance and capacity planning, automation, and how AI transforms your AIOps experience.

Chapter 1. Introduction

Chapter 2. Challenges

Chapter 3. Artificial Intelligence for IT Operations capabilities

Chapter 4. Simplifying mainframe operations

Chapter 5. Where to start

Chapter 6. Integration architecture

Chapter 7. Conclusion