For far too long, data has been kept prisoner within record-keeping systems. These archaic systems separate data by business line, business function, and data type or initial usage due to the platform’s rigidity, application, or workload options.

This system, in any capacity, is disjointed and difficult. How could you expect to have a cohesive flow of data without a cohesive strategy?

As a result, fragmented representations of segmented data are challenging to access as a whole and unable to obtain genuine analytical insight.

Furthermore, the challenges get exacerbated if firms seek to alter, grow, iterate methods, innovate, or disrupt markets. The reality that insights are only as good as access to supporting data – again too fragmented to deliver full value – renders attempts at data science, machine learning, and deep learning meaningless.

Organizations have attempted to facilitate innovation, fend off disruptors, and manage the velocity, volume, and variety of digital data beyond the human scale, resulting in an exponential surge in interest and implementation of AIOps.

So what is AIOps?

Defining AIOps

AIOps is short for Artificial Intelligence for IT Operations. It pertains to multi-layered technology platforms that use Analytics and Machine Learning (ML) to automate and improve IT operations. Big data gets used by AIOps systems, which collect data from a range of IT operations tools and devices to automatically detect and respond to issues in real-time while also giving traditional historical analytics.

Big data and machine learning are the two major components of AIOps. To aggregate observational data, such as that found in monitoring systems and task logs, and engagement data, which you can usually find in the ticket, incident, and event recording, inside a big data platform, as it requires a shift away from siloed, compartmentalized IT data.

The pooled IT data then can be used to develop a comprehensive analytics and machine learning approach by AIOps. Automation-driven insights that lead to ongoing improvements and repairs are the desired outcome. For this reason, AIOps can work as a continuous integration and deployment (CI/CD) for core IT functions.

The Benefits of AIOps

AIOps holds great potential in today’s IT landscape. Among the plethora of benefits, the most notable are the following:

Drive Down Costs while Quickly Resolving Issues

IT becomes a business as firms digitize their operations. Technology’s “consumerization” has altered user expectations across the board. Reactions to IT events, whether real or perceived, must happen quickly, especially when a problem affects the user experience.

There are many areas where AIOps will transform today’s IT operations, but this post will make the business sit up and take notice of the IT department: downtime.

Downtime, whether planned or unplanned, adds to operational expenses, including missed money or revenue, customer dissatisfaction, market share loss, and possibly brand damage, among other things.

The following is a frequent occurrence: When IT Operations receives notification that there is a problem, it can take about 5 hours and 17 steps spanning four distinct technologies to diagnose the issue, with approximately ten personnel participating in the resolution.

According to one downtime industry assessment, the average incident costs $260k per hour, and there have been others that cost much, much more.

AIOps monitors all of these siloed data channels in real-time, searching for relevant signals in both structured and unstructured data. Moreover, AIOps synthesizes a comprehensive incident report by grouping occurrences together based on geographical and temporal reasoning and resemblance to previous situations.

Finally, with AIOps, this same workflow can take less than 15 minutes, with practically all of the work taking place within ChatOps. IT Operations do not have to move from tool to tool, wasting time with context switching, and they do not have to be in the same incident room. As a result, costs get lowered drastically. Instead of 10 people working on this for hours, one or two IT professionals can reliably execute their jobs with the data they want, given by AIOps algorithms.

Scale IT to Support Changing Business Goals and Employee Needs

Traditional ways to control IT complexity – offline, manual activities requiring human intervention — do not work in dynamic, elastic contexts. It is no longer possible to track and manage this complexity by manual, human monitoring. For years, ITOps has exceeded the human scale, and the situation is only getting worse.

It is important to recognize that just because ITOps management exceeds the human scale does not mean machines are taking over. Organizations will need big data, AI/ML, and automation to deal with the new reality. In this regard, humans do not get replaced; rather, AIOps aid them.

Deliver More Resilient and Compelling Remote Service Experiences

The amount of data that ITOps must store is growing at an exponential rate. The number of events and alerts generated by performance monitoring is increasing dramatically. With the introduction of IoT devices, APIs, mobile applications, and digital or machine users, service ticket numbers increase in a step-function fashion. It is simply too complicated for manual reporting and analysis at this point.

Big data permits the use of machine learning to examine large amounts of disparate data. This function is not possible before bringing the data together, and it is also not doable with manual human effort. ML automates manual analytics and allows for new analytics on fresh data, all at a scale and pace that would be impossible to achieve without AIOps.

Conclusion

You want to keep your IT operations functioning smoothly while also cutting expenses – two more crucial objectives than ever in the new normal. With Run2biz, you can begin your digital transformation journey right now.

Simon, a Predictive Analytics Artificial Intelligence system from Run2biz, provides active monitoring of numerous data sources, automatic topology verification, anomaly identification, and event evaluation. Simon makes it easier to identify and respond to IT issues, using predictive analysis and 100% automated risk mitigation activities.

Aside from an AIOPS/SIEM solution, Run2biz offers various other services to meet your company’s unique requirements. Find out more about what Run2biz can do for your business.