IT infrastructure has become more complex and dispersed, leading to a flood of alerts in IT operations centers. As volumes increase, MSPs and enterprises can become overwhelmed and challenged with troubleshooting routine issues.
Enter artificial intelligence for IT operations (IAOps), which applies AI and machine learning software to solve the problem by automating and streamlining important parts of the management process.
The modern data center often resembles a NASA spaceship control room with large wall panels and teams of data center technicians typing on keyboards to understand how the IT infrastructure works and why. Such vital inferences have become harder to discern.
“Enterprises today deal with so much data: multi-layered systems, complex applications, microservices, cloud, software-defined network infrastructure, and IoT instrumentation,” said Sean McDermott, president and CEO of Windward Consulting Group. “Operations staff don’t have the ability to handle it like they did in the past, mostly with human decision-making. They need machines to help them crunch the numbers.”
Why AIOps is attracting interest
Organizations Use AIOps Platforms to Simplify and Improve Decision-Making by Contextualizing Large Amounts of Operational Data, According to Gartner market guide for AIOps platforms. Rather than endless streams of information flowing across the computer screen, AI tools combine data. For example, the tools can automatically bind the appropriate permissions to someone accessing the corporate network. These connections provide the necessary visibility into system usage and performance.
Organizations and distribution partners must sort the realized potential and hype of the AI market.
“AIOps is a noisy space, where some vendors affix the term to their products whether it seems appropriate or not,” McDermott said.
Although the potential is vast, actual AIOps implementations are currently quite limited.
“The AIOps industry is now in its infancy,” said Tanner Bechtel, global director of AIOps, automation and orchestration at service provider World Wide Technology (WWT). “Some companies have gone head first and done advanced work with it, but the system ecosystem is still under construction.”
Organizations must have a strong ecosystem to build an AI model as it is a complex process. According to Gartner, the model consists of five steps:
- Ingestion. Collect, index, and normalize event and telemetry data from multiple domains.
- Topology. Create software that visually displays activity within the IT infrastructure.
- Correlation. Connect events across domains and sources, ideally without too much human intervention.
- Acknowledgement. Understand the current state of enterprise infrastructure performance and how it is changing.
- Remediation. Train AI tools to take action or make recommendations when issues arise.
New possibilities for MSPs
AIOps provides opportunities for MSPs and channel partners to help large enterprises build their own AIOps solutions. In December 2017, WWT embarked on this path, according to Bechtel, who was hired to lead the initiative. Since then, the company has invested $500 million in its Advanced Technology Center, which includes development testing of the the expertise needed to deliver AIOps solutions.
Bechtel has seen customers’ understanding of the possibilities of AIOps evolve over this time. Initially, the channel partner spent most of their time educating potential customers.
“A few years ago, the room was full of doctors, and no one else really understood how AIOps worked,” Bechtel said.
Progress has been made, but it takes time for MSPs to educate many customers.
“We invest heavily in content creation, such as podcasts and written content, so clients understand how AIOps solutions can benefit them,” said McDermott of Windward Consulting Group.
Leading companies are slowly starting to look to partners to introduce AIOps into their management processes. Most of this work is in the testing and prototyping phase with some large-scale deployments in areas such as event correlation. The new solutions help companies sift through alerts and identify those that require immediate action.
AIOps has the potential to improve MSP operations in other ways. Third parties manage small and medium-sized business networks and may also use the tools in their own data centers to improve service performance and reduce costs.
A final use case is to use AIOps to provide new value-added services to their customers. This option is at an embryonic stage because the tools are large, complex and difficult to deploy. Few MSPs have large sums of money to invest so that they understand the technology well enough to deploy it for customers.
AIOps presents new obstacles
Partners also need preparation to deliver AIOps solutions. Partners must understand the AIOps challenges. System Monitoring is a complex domain, with a wide range of management tasks, including alerts, anomaly detection, event correlation, diagnostics, root cause analysis, and security. Typically, MSPs and enterprises already have a solution or tools to perform each management task, and legacy products often don’t easily integrate with other systems.
MSPs and enterprises want to break down management silos and examine their infrastructure at the highest possible level; however, the work of integration is complex and time-consuming.
Sean McDermottPresident and CEO, Windward Consulting Group
“We’re seeing progress on AIOps integration because vendors are sitting at the table, talking to each other, and connecting their systems,” Bechtel said.
Suppliers provide more complete building blocks, which simplifies the connection of the various components.
Another problem is that staff have to learn to work with the new tools. MSP staff often lack the expertise to collect data, interpret it, and train the data model.
Resistance is one more barrier.
“Humans don’t like change, and AIOps changes a lot of things: new interfaces, new business processes, new ways of working,” McDermott said.
Despite the limitations, channel partners should monitor market developments.
At Gartner Market Guide for AIOps Platformsthe company said, “There is no future of IT operations without AIOps. This is due to rapidly growing data volumes and the rate of change (exemplified by application delivery rate and event-driven business models) that cannot wait for humans to derive insights from.”
AIOps is at an early stage of development, which creates many hurdles for channel partners. However, technology is one that MSPs need to watch out for as it is gradually becoming a key part of infrastructure management.