Redefining AIOps IT Workflows with Legacy System Visibility

Key Takeaways:

1. Centralized visibility of data is key. Modern IT environments require comprehensive data for successful AIOps, that includes incorporating data from legacy systems like IBM i and IBM Z into ITOps platforms.
2. Predictive of AIOps capabilities will revolutionize IT operations. The shift from reactive to proactive IT operations is driven by AI-powered analysis, automation and insights.
3. Scalable solutions are key for future-ready IT operations. Scalability ensures you can adapt to evolving demands without disruptions to your operations.

As technology continues its rapid ongoing evolution, IT environments have become increasingly complex – which leaves businesses needing to adapt at unprecedented speeds. While challenging, this digital transformation also presents plenty of opportunities, particularly when it comes to the effective management of IT operations (ITOps).

Artificial intelligence (AI) has emerged as a game-changer, helping organizations streamline operations, address incidents proactively, and achieve greater observability across their infrastructure. Let’s explores how to harness the power of AI to modernize IT operations within your business.

Understanding AI Operations (AIOps) in IT Environments

What is AIOps?

AIOps, or artificial intelligence for IT operations, combines AI technologies like machine learning, natural language processing, and predictive analytics, with traditional IT operations. It facilitates:

• proactive monitoring
• efficient troubleshooting
• automated system remediation

The ultimate goal is to transition from reactive responses to a self-healing IT environment.

AIOps presents enormous promise, but many organizations face hurdles in its implementation:

1. Complex ecosystems made of multiple, fragmented systems that lack interoperability. Acquisitions, mergers, and legacy infrastructures exacerbate this complexity.
2. Tool overload can lead to inefficiencies and data silos. Studies show that many organizations use over 20 tools for observability and monitoring.
3. Legacy systems operate in isolation. For platforms like IBM i and IBM Z, which remain critical to many enterprises, this isolation makes real-time monitoring and observability difficult.

To tackle these challenges, you need solutions that unify data, workflows, and tools across your IT landscape. AIOps helps you address these pain points by enabling predictive insights and actionable intelligence.

The Importance of System Integration

Data handling can lead to chaotic workflows, miscommunication, and delays in addressing critical incidents. If you rely on retrospective data, you’re creating a lag in decision-making, which simply isn’t good enough to stay ahead of security or operational disruptions.

The difficulties faced by IT teams often boil down to three key issues:

1. Data silos. Teams using disparate tools – like Datadog for observability and ServiceNow for incident management – rarely communicate effectively, which leads to knowledge gaps.
2. Manual workflows. Without native integration into observability tools, information delivery and reporting will be delayed.
3. No room to improve. These silos and manual workflows ultimately lead to poor MTTR (mean time to repair), inconsistencies, and disconnected systems.

Without addressing these issues through proactive, automated visibility into your systems, you find your ITOps teams stuck in a cycle of inefficiency. This results in issues like:

• ineffective monitoring
• systems not included in IT observability tooling
• CMDB inaccuracies
• incomplete service mapping

Precisely Ironstream, for example, offers robust capabilities that seamlessly connect your legacy systems, like IBM i and IBM Z, into modern AIOps platforms. With its ability to deliver near real-time machine log data, Ironstream ensures that these traditionally siloed systems are no longer blind spots in your IT landscape – delivering a significant boost to various key areas:

• Security: detect automation failures, change profile events, system value changes, and more – immediately. This empowers you to take a more proactive approach to protecting your systems.
• Operations: gain a stronger understanding of your organization’s serviceability, with a deeper understanding of factors like capacity, CPU utilization, job duration, and disk performance.
• Application data: view employee database use cases for your business within the context of your larger IT Ops workflow.

Having the ability to connect your IBM systems to ITOps platforms and AIOps use cases improves visibility and empowers your organization to make data-driven decisions that enhance performance, security, and agility.

How to plug-in IBM Systems into ITOps platforms and AIOps Use Cases

When you’re ready to begin incorporating your IBM i and IBM Z data into your ITOps platforms and adopt AIOps use cases, there are a few crucial best practices to keep in mind for success:

 1. Understand the data in your IBM i or IBM Z

First, it’s essential to map out and understand the types of data your systems generate, and the context of that data in relation to the system it’s in and to your business at large.

IBM systems contain, for example, rich datasets critical to operational, security, and compliance requirements. By identifying these critical data points and correlating them to broader business objectives, you’re laying the groundwork for meaningful AIOps-driven insights.

Key questions to ask:

• What are the most critical events or metrics we need to capture?
• How does this data align with our operational goals and compliance needs?
• Are we leveraging all available data sources, including legacy systems?

2. Know how you want IBM i or IBM Z to inform AIOps

Clearly defining what you need to monitor is a cornerstone of AIOps implementation. Whether it’s tracking system access patterns, monitoring application failures, or analyzing resource utilization, these objectives will shape your alerting and analytics framework.

Establishing these goals ensures that your AIOps tools are aligned with the specific needs of your organization.

Here’s what you need to ask yourself:

• What do I want/need to monitor? For example:
  • privileged users
  • access to failures
  • customer data
• What will my alert categories be? For example:
  • users
  • groups
  • data
• Do I understand the business priorities? For example:
  • departmental needs
  • company requirements
  • external regulations
• What’s the baseline for my company? For example:
  • HIPAA (Health Insurance Portability and Accountability Act)
  • NIST (National Institute of Standards and Technology)
  • PCI DSS (Payment Card Industry Data Security Standard)

3. Create a connection between IBM i or IBM Z and your ITOps platforms

To achieve the full benefits of AIOps, you need to create seamless connections between legacy systems like IBM i and Z and ITOps platforms. This ensures a real-time flow of actionable insights that can be used to:

• automate processes: replace manual workflows with intelligent, automated responses to incidents.
• unify data streams: break down silos by consolidating data from diverse sources into a single, actionable view.
• improve decision-making: provide your IT teams with real-time, comprehensive insights to make faster, more informed decisions.

Integrating IBM systems into an AIOps platform can enable real-time alerts for anomalies or critical system updates, ensuring faster remediation and reduced downtime. Without these integrations, businesses risk operating with blind spots that undermine efficiency and increase vulnerabilities.

By following these steps you’ll lay a strong foundation for AIOps implementation, and turn reactive IT operations into proactive, predictive systems.

Pioneering the future of IT operations

The ultimate goal of AIOps is to transform your IT operations into a proactive and predictive function that supports business growth.

To do that, you need to connect the right data to the right tools that help you unlock the full potential of your IT ecosystems. This requires not only advanced technologies like Precisely Ironstream, but also a commitment to breaking down silos and fostering collaboration across teams.

Through it all, it’s important to remember that these integrations are about enhancing visibility and enabling IT teams to deliver greater value through improved efficiency, reduced downtime, and enhanced decision-making.

The future of ITOps is agile, data-driven, and resilient, and AIOps is your key to achieving it.

Read our eBook, The Rise of Artificial Intelligence for IT Operations, for more on how incorporating machine learning processes into your analytic platform takes it beyond just tracking your key performance indicators and evaluating IT operations services – transforming it into a truly self-learning system.