3 reasons your business needs an open AIOps integration platform

By Murilo G. de Aguiar and Sander Plug

When looking around at the current artificial intelligence (AI) landscape, it’s easy to draw comparisons to automobile styles. 

Front and center is generative AI, akin to a flashy European sportscar that grabs attention and captures imagination. Sedans represent classical AI, a reliable technology with many past, present and future applications. Machine learning is like a truck, a versatile workhorse that moves heavy loads behind the scenes.

Then there’s AIOps, the functional yet fashionable sport utility vehicle of AI. Like an actual SUV that blends key features of each automobile style, AIOps uses classical AI, generative AI and machine learning to improve IT operations.

The AIOps market has accelerated dramatically in recent years and is expected to surpass US $64 billion by 2028.¹ However, rapid market expansion has created customer confusion and other challenges.

AIOps open integration platforms—AI- and machine learning-powered platforms that combine multiple AIOps solutions on a single pane of glass—now seem poised to cut through some of the noise. With greater adoption, open integration platforms may help companies achieve better operational performance and maximize their investments in previous AIOps solutions.

AIOps and the need for a better approach

AIOps is an umbrella term for solutions that enable visibility and automation and help engineers aggregate and interpret data from numerous sources. IT teams use this information for advanced analytics and real-time, predictive insights.²

In many cases, companies buy one-off AIOps applications to address specific needs like database or storage management rather than developing a strategy to deliver end-to-end value across their IT estate. The resulting technology sprawl disrupts operations and can take months to realize expected business value.

Some organizations also become locked into long-term contracts with select vendors when purchasing numerous AIOps solutions from different companies. Vendor lock-in can hinder deployment and lead to increased costs and technical challenges over time.

Open integration addresses these issues by uniting disparate AIOps solutions on a vendor- and technology-neutral platform. Engineers can use the aggregated insights to:

• Identify patterns and trends that isolated AIOps can’t due to limited coverage
• Detect, correlate and correct root causes faster than with niche AIOps solutions
• Automate workflows and orchestration to help reduce labor costs and overall IT expenses
• Analyze security incidents and provide pattern-based predictions, anomaly detection and remediation

Each platform’s data model enables integration, events processing, reasoning and continuous learning, providing faster time to value time from the various niche AIOps solutions.

Ultimately, reducing costs and streamlining operations through automation helps organizations improve the speed of execution and overall quality of services they provide customers.

Practical applications of integrated AIOps

The underlying premise of AIOps is to streamline operational processes, allowing IT teams to focus on mission-critical tasks. True to this ideal, consolidating previously siloed AIOps tools and integrating them onto an open AIOps platform has been shown to:

1. Improve observability and real-time visibility. Integrating multiple AIOps and data sources onto a single platform amplifies IT observability, enabling tech teams to spot issues, optimize performance and cut costs.

For example, one US-based financial services company³ with a significant mainframe footprint couldn’t gain complete visibility into its IT operations because siloed AIOps applications were scattered across the IT estate. With limited visibility, the organization couldn’t process data in real time, making it harder to manage systems and address issues without disrupting operations. Manual processes also exposed the company to additional regulatory risks. 

After consolidating data from multiple applications onto an integrated AIOps platform, engineers achieved data observability across the organization’s IT environment. The IT team used these enhanced insights to increase mainframe automation levels to more than 99%, improving their daily batch processing while reinforcing adherence to regulatory and compliance mandates.

2. Enhance efficiency. Incident response and resolution in IT operations can be slow and inefficient. Open AIOps integration platforms use autonomic responses to quickly solve these issues with no human intervention and limited to no impact.

Consider the European insurance multinational³ we recently helped that had an IT system consisting of more than 10,000 devices. The company was dealing with over 200,000 incidents each year, mainly because engineers didn’t have easy access to data or centralized visibility.

After moving its IT estate to an integrated AIOps platform, the company could access data from multiple sources and tap into AI-based recommendations. Within 12 months, incidents declined by 75%, including a 50% reduction in P1 incidents. Meanwhile, compliance adherence increased from 85% to 97%.

3. Accelerate decision-making. When making business decisions, access to data in real time—or as close to it as possible—delivers better outcomes. Integrated AIOps helps to eliminate roadblocks that can impede real-time data delivery, allowing engineers to make informed decisions more quickly.  

For instance, an advertising multinational in the UK³ relied on SMEs to manually capture and consolidate operations data. Not only were the results slow, but they often had errors, lacked a holistic view and had no governance.  

Following an extensive operations review, we worked with the company to deploy an integrated AIOps platform to automate and transform their IT operating model. Since launching the platform, the organization has increased automation coverage across its IT estate to more than 92%. Incidents and outages have decreased by 33% and more than 95%, respectively.  

Countering an integrated AIOps argument

Critics of AIOps open platforms may argue that deploying another technology platform to reduce costs and shrink your IT footprint is counterintuitive. 

The numbers tell another story. 

Generally, engineers need to monitor more than a dozen dashboards using siloed AIOps solutions to manage an IT estate, which is labor-intensive and time-consuming. Integrating existing AIOps solutions onto an open platform automates numerous processes and reduces the number of dashboards and IT personnel needed to operate the systems. Correlating the data across IT domains to generate actionable insights becomes critical to accelerate the time to value rather than consuming dashboards to interpret data and make decisions.

For large organizations spending roughly 2% of their annual revenue on IT costs, reducing AIOps-related expenses by just a fraction can substantially lower IT expenditures. Using this example, a US $5 billion company could potentially save several million dollars annually. 

Redefining the IT management landscape

Moving forward, AIOps will continue to reshape how organizations manage their IT operations. We also believe AIOps open integration platforms will inspire new use cases, maximize previous investments, and pave the way for more business value while redefining applications like the ones above.

Murilo de Aguiar is vice president, distinguished engineer of Observability, AIOps and Automation.
Sander Plug is vice president, distinguished engineer of Integrated AIOps Center of Excellence (CoE).

¹ Definitive guide to AIOps in 2024, United States Artificial Intelligence Institute, October 2023
² Navigating AIOps challenges: Strategies and use cases for CIOs, CIO Influence, December 2023
³ The performance data and client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions.