Artificial Intelligence for IT operations (AIOps) is a new way to address changing user and IoT requirements for today’s modern and complex campus, branch and WFH networks. Visibility and automation provide IT organizations with the insights needed to improve efficiency and enhance user experiences.
AIOPs Explained
AIOps stands for artificial intelligence for IT operations and describes the use of big data, analytics, and machine learning that IT teams can use to predict, quickly respond to, or even prevent network outages.
“AIOps” was originally coined by Gartner in 2017 and refers to the way data and information from an application environment are managed.
AIOps combines the automation of management tasks and the oversight of network experts, with the expertise of skilled IT pros to improve efficiencies.
The use of AI/ML is used for network insights, endpoint profiling for security purposes and the visibility needed to ensure the proper performance of local and cloud applications.
How does AIOps work?
AIOps uses telemetry collected from each network and client device to create baselines that automatically help identify issues, determine root causes, and deliver optimization guidance in real-time.
AIOps includes the following:
Big data – Structured and unstructured data that is collected in large volumes.
Machine learning – Algorithms with the ability to learn about and adapt to changes in the environment. With the ability to then change or create new ones to identify problems earlier and recommend effective solutions.
What are AIOps use cases?
The following table describes common network challenges and how AIOps can solve them.
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