AIOps trends to watch out for in 2022 and beyond

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Hello there! 

How’s it going? Hope 2022 began on a good note for you and your company!

If the past two years have shown us anything, it is that everything around us is unpredictable! 

However, the unexpected possibilities of tomorrow are the very reasons why enterprises have completely embraced technology today.

Let me explain what I mean, in the context of IT operations, for example.

As organizations become progressively digital, IT operations currently manage more broad and complex data than before. Today, traditional tools and methods may not be sufficient to help them adapt to the increasing workload. Hence, numerous enterprises are interested in embracing different AIOps trends available.

AIOps platforms unify Big Data and AI to discover patterns, recognize issues, and anticipate and forestall future issues from happening. Lately, AIOps has been a significant tool in assisting enterprises with scaling high volumes of data because of the remarkable shift to a remote workforce.

With 54% of enterprises around the world heading towards AI adoption, AIOps should be the next tech deployment. I’d like to share with you some of the AIOps trends enterprises should look out for this year, and in the near future.

Observability Platforms

Today, the AIOps landscape is exceptionally fragmented. However, software vendors and ancillary technology providers are making observability platforms that permit IT activities to get a comprehensive view of their enterprise’s operational data and systems. Technologies such as the cloud, DevOps, applications, microservices, containers and container orchestration are accelerating the speed of data as well as speeding up the way toward going from programming code to full production.

Cutting-edge observability platforms slice complexity down to a great extent. They select and present significant insights to users, while likewise proactively addressing possible issues. For instance, a front-end monitoring framework can discover JavaScript issues that may be going to overpower a framework. Performance issues can also be checked. For instance, potential out of memory issues could be mitigated well before they become risky. 

Deploying AI To Detect Problems For Remote Working

Remote work was the norm for the past two years and may continue for a while more. Before the Covid-19 pandemic, data was ordinarily gathered in quite specific areas because of collective working environments. The pandemic compelled organizations to maintain a remote workforce, and each remote user is an information generator, making data volumes soar.

Monitoring employee productivity and digital continuity is vital during these scenarios, yet stays challenging for ITOps teams to oversee. More intelligent algorithms are required to anticipate issues with employee productivity or customer experience utilizing the product remotely. This is where AI makes a difference.

With regards to AI, it is still valuable regardless of where users are working from. When an algorithm is programmed, its main job is to ingest the data, harness insight, and afterwards output the optimized value.

Hyperautomation

Hyperautomation, Gartner’s top technology trend for 2020, refers to “the combination of multiple machine learning, packaged software and automation tools to deliver work.” In simple words, hyper-automation involves the use of cutting-edge technologies to progressively automate business processes as well as augment human capabilities.

Hyperautomation permits organizations to make a digital twin, i.e., a digital copy of a living or non-living physical entity that permits enterprises to visualize how its functions, processes, and KPIs connect to deliver value for them. A digital twin gives real-time intelligence that can help a business acquire instant business intelligence swiftly.

Accelerated Incident Response

With AIOps, IT teams can perform root cause analysis quicker than ever. This is on the grounds that AIOps platforms automate analysis procedures for occasions, logs, and other metric information. It can likewise give relevant and real-time context to speed up triage. As advancements keep on progressing in AIOps, numerous platforms will endeavour to speed up their incident response and improve their respective algorithms.

AIOps platforms give an accelerated incident resolution by having all basic information in one spot. This incorporates incident context, causing alarms, triage data, sending alerts, etc. This makes it simpler to track incidents and analyze them as needed.

Better Integration of Security and IT Operations 

As enterprise IT environments keep developing, the requirement for cutting-edge security platforms will inevitably follow. Significant data sets utilized in security platforms, including product security and cybersecurity, are practically the same as IT operation data sets. Security algorithms analyze metrics and logs that course through infrastructure to show historical behavioural patterns and alert anomalies. Utilizing AI, this process can be additionally automated towards impending bad actors in real-time.

Despite the business issue, the hidden data needed to assemble this intelligence is still logs, metrics, and exchanges within a framework. Only one difference is the issue that IT security teams are attempting to address. Security teams wish to know whether a hacker is attempting to get to the system, while ITOps teams are more keen on utilizing applications that will protect their users and give a better customer experience. This year and in the future, ITOps and security teams will probably work together more closely to identify issues in the infrastructure performance as well as forestall cybersecurity threats in real-time.

Virtualized Operations and Service Management

This trend is mainly in the context of remote working, when, due to the pandemic or other reasons, employees are compelled to work from home, and cut down on superfluous travel. 

Later on, the majority of people in an AIOps team will try to address an episode while working on a virtual Network Operations Center from different locations across the globe. Teams of experts could be quickly deployed to deal with a specific issue or a host of issues. 

I strongly believe AIOps delivers long-term benefits for businesses. However, automation will play a crucial role in transforming operations management. 

As the amount of data grows exponentially, the adoption of AIOps is bound to increase across various industries. It will ensure enhanced performance, better savings and a larger bottom line. 

Watch out for these trends in 2022, and the next few years. If you’d like to know more or discuss your automation plans, drop me a line at hello@digitalleaf.io

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