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Boosting IT Operations Management with AI
Artificial intelligence is changing the business landscape, offering all departments, from sales to finance, the opportunity to have access to accurate insights both in real-time and regarding the future. So far, AI is an industry that grows almost exponentially in revenue from $ 10.1 billion in 2018 to an estimated $ 126 billion by 2025, according to Statista.

Paradoxically, the IT organizations have not yet taken full advantage of all the possibilities AI and ML have to offer for their processes. In the last five years, a new discipline has emerged, called AIOps, which is an umbrella term for all tools based on AI, which help IT personnel in the management of their daily operations. This is the next generation in IT analytics, including automation, visualization, correlation, and dependency mapping.

This new branch’s market potential, which is derived from DevOps, is estimated at $2.2billion in 2017 and is expected to reach $9.9 billion by 2023. This is due to this technology’s excellent opportunities, which can improve efficiency, cut costs, and give organizations the chance to be more innovative and predictable.

For now, AIOps will not replace IT operations or wipe out jobs but offer excellent support to replace manual work, which leads to more time for creation and dealing with innovation instead of firefighting operations

Critical Challenges of IT operations

Most of the time, IT operations are regarded as an annex. It needs to keep the boat floating and respond to arising problems. However, the IT team members are usually highly skilled specialists that could play a strategic role in the company’s growth if they had the opportunity to focus on that instead of the continuously patching of problems. The focus needs to shift from a reactive approach to proactive management.

By putting a lot of the daily grinding on a smart autopilot, that means a lot more time to find ways to cut costs, improve security, and operate more efficiently overall.  Currently, IT operations face several different challenges.

High expectations from end-users

Since technology is evolving exponentially, users are becoming more demanding with the service level they expect and the number of errors they are ready to tolerate. Time to market for digital products is also getting shorter, which only means less room for incidents and rework. Users expect flawless performance and 24/7 service options as standard offers.

A broad array of services

Since cloud and modern systems are open to add-ons and modular enhancements, there is a booming market for new services. These offer numerous innovation and efficiency opportunities but also bring complexity and failure risks. When troubleshooting services with add-ons, finding the root cause can become exponentially tricky.

Countless alerts

Most IT environments have hundreds of systems, which each generate logs, warnings, and alerts. To handle all these information streams by hand, filtering the noise’s real notifications is almost a full-time job. The solution is not to mute them but to automatically filter them to fight alert fatigue.

Monitoring a diverse IT ecosystem

As organizations use more and more interconnected systems from different providers, there arises a need for operation centralization and a dashboard highlighting all important alerts. IT departments need to coordinate the influxes of information and the streams of outputs, and most of the time, they also need to coordinate with external entities.

Considering these constraints, together with budgetary limitations, it becomes clear that IT operations could use a way to become more predictive, use automation, and finally take a proactive approach instead of a reactive one.

Introducing AIOps as a solution

AIOps can help solve all the previously discussed challenges. This is a general term to designate all AI and ML solutions designed to monitor and enhance IT operations. AIOps became more visible after 2017 when Gartner published a whitepaper on it, growing in popularity.

The main applications of an AIOps solution include:

  • application performance monitoring (APM),
  • information technology infrastructure management (ITIM),
  • network performance monitoring and diagnostics (NPMD),
  • information technology event correlation and analysis (ITEC&A).

Since AIOPs can help a lot with time-saving automation, this is one of the main features requested by clients, and it allows them to pick the low-hanging fruit of this technology. This trend will continue to develop in the next few years, offering IT departments sustainable assistance in their daily operations.

When it comes to ways AIOps can help enhance IT operations, there are at least three significant improvements.

Make processes visible

When installing an AIOps system, it drills down into data up to an atomic level, offering IT specialists the opportunity to see how each process performs and identify potential bottlenecks or other causes for interruptions. When Your company has an overview of the system, it is easier to identify potential risks and hedge them before becoming real threats.

Make data-based changes

Like every business decision, it is best to make IT operations changes based on data and facts instead of hunches. An AIOps system can analyze historical data, triage the alerts, and perform automated root cause analysis efficiently. Having such information leads to better predictions and faster problem solving, and also anticipating potential future issues.

Automate responses and execute

Even if the system identifies possible threats and improvements, if the final decision needs to be approved by a member of the IT team, it is still inefficient and adds to the alert fatigue. The significant improvement of using AIOps compared to previous generations of IT operations management systems is the ability to automate responses and configurations to match the system’s state. For example, such a system could dynamically allocate more bandwidth or other resources in case of high traffic.

Protect IT systems from fraud

When hackers try to attack a system, their patterns in data usage are different from those of normal operations. An AIOps platform can detect abnormal behavior and take the necessary actions to block it.

Currently, AIOps is just starting to enter the corporate world, but we can expect it to become standard technology in just a few years.



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