AIOps for beginners: Keeping IT smart with AI

Businesses that want to monitor their IT assets better use artificial intelligence to automate fixes and stay ahead of performance problems.

The use of AI-powered IT operations technology to autonomously monitor and manage the IT portfolio is an emerging IT trend that is starting to pay off for cloud platforms, managed service providers, and businesses undergoing digital transformations.

AIOps, a new approach, assists businesses in preventing possible outages and performance problems before they have a detrimental impact on operations, clients, and revenue. However, the more sophisticated installations are starting to leverage AI systems to react to events with intelligent, automated mitigation rather than only identifying or predicting problems before they happen.

What is AIOps?

To help enterprises manage infrastructure, networks, and applications intelligently for performance, resilience, capacity, uptime, and, in certain circumstances, security, AIOps uses artificial intelligence for IT operations. AIOps enables enterprises to monitor IT better assets and foresee bad incidents and repercussions by transferring traditional, threshold-based alerts and manual processes to systems that use AI and machine learning.

AIOps in action

Your IT portfolio may already be utilizing AIOps without your knowledge. Advanced CRM and ERP solutions sometimes include intelligent management. Monitoring and management solutions powered by machine learning are also used by the majority of the major cloud platforms.

However, relying on built-in features within point solutions has drawbacks. According to a poll by AIOps Exchange, 65 percent of IT businesses still rely on monitoring techniques that are either rules-based, isolated or don't address the demands of their entire IT infrastructure. Furthermore, 42% of IT businesses employ more than ten distinct monitoring solutions for their IT infrastructures, according to a recent BigPanda report.

AIOps adoption is still in its early stages.

According to Gartner, 40 percent of businesses will utilize AIOps for application and infrastructure monitoring by 2023. However, it appears that AIOps adoption is still in its infancy. AIOps has only been adopted by 5% of businesses, according to a 2019 report.

Customers still have difficulty understanding exactly what companies offer since, according to the Loom Systems survey, 59 percent of businesses are still in the exploratory phase. Additionally, several suppliers specialize in just one area of AIOps, such as network performance monitoring and diagnostics, infrastructure management, or application performance monitoring. The market is beginning to consolidate, though, as technology advances.

According to IDC, the AIOps market, also known as IT operations analytics, will increase from $2.9 billion in 2018 to $4.5 billion in 2023, with AIOps as a service accounting for most of the growth. And while AIOps is sometimes bundled with business software platforms or cloud services, bigger companies are starting to allocate money to it independently.

AIOps pay off

Businesses that use AIOps are starting to realize how important it is to move away from systems that perform analysis and forecasting in favor of those that make decisions independently. present automation

Greater AIOps integration is also necessary for automation. A software, networking, or hardware issue could cause a performance issue with an application. The root cause in a multi-cloud system may originate from one cloud, another cloud, or a confluence of variables. Identifying and addressing the fundamental causes of issues can be difficult if your AIOps infrastructure is scattered.

Companies who have implemented AIOps are seeing that their investments are paying off in the meantime. According to a study by Enterprise Management Associates, 81 percent of AIOps users report a favorable return on investment in 81 percent of cases. 42% of respondents claimed that the benefits of AIOps "dramatically" outweigh the expenses. According to this study, cross-domain application infrastructure and performance, capacity management and infrastructure optimization, DevOps and agile, customer and end-user experience management, business alignment, cost management, and change management are the six most typical use cases for AIOps.