Five Reasons Why Your IT Team Needs AIOps

There’s been a great deal of discussion recently about AIOps, or Artificial Intelligence for IT Operations. The phrase was first used by industry research firm Gartner about five years ago. At its core, the term means the use of machine learning and artificial intelligence (AI) technology to help organizations improve the speed, efficiency and effectiveness of their IT work – and everything it entails. Patrick MeLampy, Juniper Fellow at Juniper Networks, makes his case for the AIOps way to succeed and shares five reasons why organizations today need AIOps.

The primary reason to move to an AIOps approach is to get a better handle on the sheer increase in devices, applications, bandwidth, cyberattacks, and people that has been driven by the cloud and the use of cloud applications to work and to live. Even before the pandemic and our increased reliance on the cloud to survive, the omnipresence of the cloud was never in doubt. With the growing reliance on AI and cloud technologies, comes the need for operations to step up and become AI-inclusive.  

Five Reasons for AIOps

Leveraging artificial intelligence (AI) in IT operations comes with multiple benefits for the whole organization and business at large. Today’s digital world demands reliance on artificial intelligence and machine learning to quickly troubleshoot issues. Here are five reasons why AIOps are the key to your continued operations and future success.

1. Managing Your Network Environment 

It is no longer humanly possible to depend on the traditional IT and network engineer approach of operating the network via a Command Line Interface (CLI), including the process of troubleshooting by sifting through log files. The process was already time-consuming and inefficient – and by adding an exponential amount of new devices and applications to the network, the job has become even more complex.

If the team is spending their time sifting through log files and notifications and trying to determine where problems are and how to solve them, they cannot spend time on items critical to the company’s bottom line. Mundane and repeatable tasks eat up the team’s days, making it difficult to truly provide value to customers and the organization as a whole.

For example, there could be an unknown Maximum Transmission Unit (MTU) mismatch. Say a company’s SD-WAN vendor runs a software update, just as they have hundreds of times before. But this most recent update changed the MTU size without notification. Suddenly, employees can no longer run the company’s app on their tablets. Why? Because the tablet application depended on a different size MTU to run, the app could no longer function following the update. Any IT team or network engineer would say that checking the MTU size would be far down the checklist, so the app would be inoperable until the usual suspects had been checked out. But with AI-powered intelligence rapidly reviewing a list of possibilities, an issue like this could be discovered instantaneously. 

With AIOps, it is immediately easier to uncover issues like wireless network interference, network misconfigurations, incorrect settings, missing Virtual LANs or even down bad cables. AIOps can find an issue and troubleshoot its way to identify the problem, where it is located, and how to fix it. In many cases, more advanced implementations can also empower the AI to repair the issue (if possible). With AIOps, the underlying data and detailed information of a problem or anomaly can be automatically gathered, instead of the traditional method of an IT manager having to recreate the issue (or walk around the property, looking for interference) to troubleshoot and fix the problem.

See More: What Is Artificial Intelligence (AI) as a Service? Definition, Architecture, and Trends

2. Improving the User Experience

Users today care about one thing – whether everything works as intended. They want their networks to provide a high level of service day and night. Data and applications must be readily available, and video calls should run smoothly. It is critically important that they receive the best possible user experience.

AIOps allows IT organizations to focus on delivering excellent user experience while also reducing operating costs. AIOps automates network operations – such as ticketing, reviewing log files and locating potential issues – and helps to bring newfound reliability to the network. Through machine learning algorithms and AI, an AIOps implementation can correlate previous issues with current problems to determine the root cause. This saves time and ensures that the team can locate and repair (or prevent) problems, maintaining a positive experience. 

For example, an organization’s employees may be experiencing periods of lag time and latency during certain hours of the day. Without AI, most IT teams would be blissfully unaware that there was an issue at all unless the employees raised a concern. By incorporating AI into the network, however, the IT team could have metrics on a consistent performance slowdown during certain times of the day and then proactively act to solve the issue and restore intended speeds.

In certain circumstances, AI can also help an organization learn about a new, never before seen network condition – and help them know how to resolve the issue. One key function of AIOps is to sift through data and correlate functions to predict problems that have yet to be noticed. In wireless networks, for example, there are a lot of unreported issues that cause poor user experiences. 

In another example, an organization believed they had a rock-solid network. When applying AI to their environment for the first time, there was an indicator that something was wrong in one of the branch offices. The AI indicated a bad cable connection or bad cable might be the cause. But there had never been any complaints or tickets about an issue that needed to be repaired. So, the IT team visited the branch, spoke with the local leader, and learned that employees there had been relying on Wi-Fi for about a year, as the hardwired connections had been slower. With help from AI, the problem was discovered and repaired.

AIOps can help a team find, understand and resolve these issues even before users bring it to IT’s attention. Once found, AIOps programs can either recommend a fix, or automatically remediate the issue, based on the IT team’s preference.

3. Choosing the Best Solution

To begin AIOps implementation, the first step is to research types of solutions and what they bring to the table. Ensure that the solution being considered truly provides the efficacy needed. Making a large investment in a solution that does not evolve or improve as it learns about the organization’s network means it will be unable to keep up with future additions, expansions or new technologies. Be sure the solution is built on a modern microservices cloud. Modern cloud architecture provides the required compute power to execute AI and machine learning. In addition, how does the solution access, use and update data? Quality is much more important than quantity, and we’ve all heard the statement “garbage in, garbage out.” This applies to AI engines as well. A properly designed and architected AIOps solution should also allow you to start small and build confidence and trust in its results.

An AIOps solution that’s architectured in the modern cloud should also be easily accessible as a service. It should provide varying degrees of integration with the organization’s existing operations, from providing guidance and information to becoming a fully self-driving solution. For example, an AI-powered virtual network assistant can suggest troubleshooting and remediation actions – and when the IT team is ready – evolve into a fully automated self-driving mode.

4. Setting Expectations and Preparing Your Team

Adopting AIOps is a paradigm shift, moving the organization from the traditional way of solving network problems to bringing an AI-based assistant into the fold. The networking industry has traditionally been built on outdated operations models that will not scale with today’s digital world, let alone being constructed to understand and drive better user experiences. This is a change in the way things are done – one clearly for the better – but one the whole team will need to be prepared for.

At the same time, AI has been tethered to an unrealistic set of expectations and results for a long time. Considering that AI has become such a buzzword, the reality of what AI is and what it is capable of is widely misunderstood. Outlining reasonable expectations for an AIOps implementation is a must, as this will make or break the situation. If the team and the executives above them do not understand and trust AI, then failure, or at the least, confusion, is guaranteed. Some solutions often attempt to “boil the ocean,” so it is important to ensure you choose a solution that contains the knowledge and data necessary to perform tasks within the limits of today’s AI. 

5. Empowering Teams

AIOps will help IT teams to shift their day-to-day jobs from manual, time-consuming, costly and unsustainable troubleshooting to driving new, innovative projects that provide value and meaning to the business. Less time will need to be devoted to “keeping the lights on,” meaning more time can be spent driving disruptive innovations. Accomplishing this will require reskilling towards AIOps-based tools and techniques, but the payoff will be lasting once begun.

See More: AIOps for FinTech : The Costs and Benefits of Adoption

With the increased availability and use of cloud-based applications, two other things have increased within every organization – the attack surface and the amount of work it takes operationally to maintain said applications and the overall network and technology environment. Both of these require constant attention by a skilled team that understands how they work, knows how to troubleshoot, and recognizes and fix any potential security issues.

Do you think AIOps is essential for success in today’s workplaces? Share with us on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We’d love to hear from you!