The benefits of AIOps in business


Faced with the growing complexity of enterprise systems, driven by multicloud and working in hybrid environments, IT professionals must now exploit the massive amounts of data at their fingertips. Applying Machine Learning (ML) to this data gave rise to AIOps. Just as AIOps has evolved to meet the needs of IT operations teams, so have they evolved to meet the needs of their business.

Automation, a necessity to simplify processes

Automation is most effective when applied within tightly defined, manual, and repetitive processes and workloads. Thus, AIOps reduces the time that highly qualified engineers spend on these tasks, and allows them to focus on activities with greater added value for the organization. With these smart initiatives, IT solves complex challenges and can cope with the exponential growth of data, automating the entire process of operating IT in hybrid environments and creating an accurate inventory allowing machines to correlate the data points independently.

As such, they can apply it to ML to identify patterns in four key areas: event noise reduction, predictive alerts, probable cause analysis, and capability analysis.

Event noise reduction and predictive alerts

IT teams often struggle to manage the amount of false events and alerts emanating from the various monitoring tools installed in their environment. This is one of the main challenges they face. While alerts can sometimes be useful, more often than not they clutter up inboxes and are ultimately just false alerts.

AIOps reduces the noise of these events in an environment by learning how it behaves day after day. This knowledge is then used to determine the nature and relevance of a specific alert. The IT teams are then only alerted if the behavior of the environment reveals a degradation of an application, a service, or a system shutdown. This allows them to set priorities and improve efficiency.

This also applies to predictive alerts, where AIOps automatically identifies seemingly innocuous events for further evaluation. This proactive approach makes it possible in particular to analyze the data, identify the problem in a few minutes, even a few seconds, instead of several hours and therefore reduces the risk of service interruptions.

Behavior learning and advanced analytics also enable AIOps to help manage capacity and identify when and what resources are being used. They also determine which ones are needed to support the applications and services most requested by customers. Planning for future needs is therefore enabled, and provides IT teams with the information needed to adapt resources, which helps to reduce costs and ensure optimal operation of applications. AIOps therefore reduces the time spent by teams on these tasks in favor of initiatives with greater added value.

Adoption and integration into DevOps frameworks

AIOps is increasingly integrated into DevOps frameworks, especially for ingesting and analyzing logs and identifying risks in code. Going forward, its use in DevOps will no longer be focused on pre-production but on metrics such as user engagement, quality, and business relevance. All of which supports the idea that DevOps teams that leverage AIOps platforms to monitor and support applications accelerate and streamline development.

Digital transformation translates into a shift from centralized IT to applications and developers, an increased pace of innovation and deployment, and the acquisition of new digital users. But these new technologies and new users are pushing traditional performance and service management strategies and tools to the breaking point.

Therefore, AIOps is the best strategy for the IT operations team to manage these digital transformation issues. The platform transforms IT operations so that automated, AI-powered analytics are applied to a wide range of ingested data in a modern, open observability platform. Thus, the teams focus on the search for operational excellence and help the company evolve towards the Autonomous Digital Enterprise (ADE) model.

With these automation capabilities and the resulting time savings, AIOps enables ITOps to intelligently orchestrate infrastructure, applications, and services across hybrid cloud ecosystems to make them coincide with business. and meet customer needs, on demand. Business leaders must realize that the transformation of the IT environment must be holistic to ensure the establishment of an intelligent enterprise capable of meeting the needs of a rapidly evolving digital market.





Source link -97