Six Essential Opportunities to Leverage in the New Year

At a time when IT systems are becoming more complex by the week, CIOs and their teams need all the help they can get. Third-party vendors, work at home, and other factors are ramping up cybersecurity concerns – while hardware and software maintenance demands more and more time and energy.

AIOps has arrived at this crucial moment like a fleet of superheroes – with the potential to transform and improve so many processes that IT and technology leads may not know where to start. Generative AIOps platforms deliver a quantum leap in capabilities, allowing tech teams to manage systems proactively rather than reactively. And machine learning (ML) and analytics can help CIOs take system management to a new level. But how can we get our heads around all the potential that AI may offer?

Here are six ways that AIOps can and should empower operations teams in 2024 – and beyond.

Accelerating Digital Transformation

Digital transformation is the process of replacing traditional, stodgy systems with modern digital technologies, like cloud, mobile, IoT, and AI. The pandemic sped up the transformation process – corporations accelerated the digitization of their customer interactions and internal operations by three to four years — and the share of digital or digitally enabled products in their portfolios raced ahead by seven years.

In the DevOps process, tremendous progress has been made in the development part of the equation — code writing. However, operations have had trouble keeping pace. New software solutions broke applications into smaller components, so organizations have more items to manage. In response, the number of monitoring tools grew, and management took more time.

Generative AI has been gradually addressing these issues. Previously, information was stored in a siloed manner, available only to select applications. Increasingly, AI breaks down barriers and delivers high levels of automation, enabling companies to deploy more complicated applications while not increasing operations’ workloads. Such capabilities will become even more prevalent in 2024.

Taking Machine Learning to the Next Level

Leveraging machine learning (ML) for business in 2024 will continue to be essential for staying competitive and making informed decisions. ML is evolving rapidly – so staying up to date is no easy task.

ML is already helping AI programmers take on a recurring challenge – understanding and accounting for all of the possible infrastructure iterations and including them in their code. Earlier software was not smart enough to draw its own connections, but the latest generation of AI solutions features ML algorithms that continuously learn and autonomously adapt to the business infrastructure. Moving into 2024, operations will spend less time programming and more on proactive management.

As ML models become more complex, it’s crucial to understand why a model makes certain predictions. Invest in interpretability techniques to make your models more transparent and trustworthy. Keep up-to-date with the latest developments and be ready to adapt your strategy as new technologies and techniques emerge.

Accelerating Response and Recovery

Infrastructure monitoring teams have been under constant stress. With millions of transactions occurring among larger, more dispersed applications, recognizing what is happening becomes difficult. In fact, so many alerts are generated that tech teams often feel overwhelmed.

New AI solutions aggregate operational data across information silos. Consequently, IT operations gain clear visibility into how their systems are running. AIOps solutions constantly monitor IT systems and applications and search for deviations from normal behavior. When an incident occurs or is imminent, they detect the issue and trigger alerts to notify support teams, allowing them to respond to problems faster.

Increasingly, AIOps not only correlate data from various sources but also identify the root cause of incidents. This change accelerates the troubleshooting process and reduces the mean time to resolution (MTTR).

Ensuring Resolution Consistency

In the past, companies relied on systems technicians to determine what was working and what was not. They implemented fixes in a subjective and sometimes inconsistent manner.

AIOps generates best practices that guide technicians, so they attack problems reliably. Many of the new solutions integrate with predefined incident response playbooks that outline step-by-step procedures for handling various types of incidents. These playbooks ensure that the same set of actions is taken each time a specific incident occurs. The changes enforce standardized procedures, reduce the likelihood of human error, and ensure correct and consistent sequencing.

Also, increasingly, AIOps categorizes and prioritizes incidents based on their severity and potential impact. This information helps incident response teams focus their best efforts on the most critical issues. Businesses are now putting such processes in place and should realize a host of benefits starting next year.

Explore Our eBook on 2024 AIOps Trends

Going beyond System “Monitoring”

Monitoring is a reactive posture. A company waits for its infrastructure to reach a problem point before taking steps to alleviate it. Many times, performance loads tick up slowly, so manual analysis does not pick up on the trend, and problems arise.

IT teams want to be proactive, and new tools enable that change. AI models identify unusual behavior based on benchmarks that reflect current performance. For instance, when resources are being consumed faster than expected, infrastructure teams respond by dedicating more resources and spinning up new instances in anticipation of stressed load capacity.

Even more help is coming. Predictive analytics are becoming more common in AI-driven operations. Here, algorithms identify patterns and trends within performance data to predict potential issues before they impact the system. By foreseeing problems and bottlenecks, organizations take preventive actions, minimize disruptions, and improve overall system performance.

Boosting Business Performance and Productivity

The process of automating infrastructure management chores has been ongoing. The emerging solutions take it to higher levels. In the past, technicians lacked real-time visibility into system performance. AIOps uses machine learning to learn from historical data and determine the best course of action to resolve specific issues automatically.

In cases where incidents are recurring and well understood, AIOps automates predefined remediation actions. For example, restarting a service, reallocating resources, or running diagnostic scripts can be executed automatically, reducing the need for manual intervention.

One of the most immediate benefits of new tools is that IT operations teams no longer need to go digging for the proverbial needle in a haystack during troubleshooting. As something is breaking, IT staff are notified, and corrective actions are recommended, so restorative steps are quickly taken.

Also, AIOps automatically escalate incidents to higher-level support teams based on predefined criteria. This ability ensures that critical incidents receive attention from the appropriate personnel. This process accelerates incident resolution by providing IT teams with actionable insights and reducing the time spent on manual input and troubleshooting.

A Banner Year Ahead

Operations teams have been searching for solutions to their headaches – complex systems, antiquated processes, and multiplying risk factors. AIOps is delivering the relief that CIOs and their key players have been looking for – allowing more consistent responses, accelerated resolutions, and automated functions. All of these benefits will pick up pace in 2024, bringing unprecedented advantages to those who understand what is available and how to get on board.

Be sure you are ready to cash in these benefits with a thorough understanding of AIOps and the value it can deliver!

Need Help Bringing the AIOps Difference to Your Work?

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