What is AIOps?

AIOps, or artificial intelligence for IT operations, refers to use of artificial intelligence, such as machine learning (ML) and generative AI (GenAI), to automate the identification and resolution of common IT issues or improve operational efficiency.

Within the networking space, AIOps is used to address changing user and IoT requirements for today’s modern and complex campus, branch, and WFH networks. AIOps combines the automation of management tasks and the oversight of network experts to improve efficiency.

The visibility and automation provided by networking AIOps gives IT organizations the insights needed to speed up design/configuration tasks as well as predict, quickly respond to, or even prevent network outages. For example, AIOps insights can be used for endpoint profiling for security purposes and the visibility needed to ensure the proper performance of local and cloud applications.

  • How does AIOps deliver insights in an enterprise network environment?
  • What are some networking AIOps use cases?
  • HPE and AIOps
How does AIOps deliver insights in an enterprise network environment?

How does AIOps deliver insights in an enterprise network environment?

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 can include the use of the following AI techniques:

  • Classification AI (including machine learning) – Algorithms with the ability to learn about and adapt to changes in the environment. These have the ability to change or create new algorithms to identify problems earlier and recommend effective solutions.
  • Generative AI (GenAI) – AI capable of generating text, images, video, or other data using generative models, often in response to prompts. Generative AI models, including large language models (LLMs) learn the patterns and structure of their input training data and then generate new data that has similar characteristics. An example of GenAI that uses LLMs is OpenAI’s ChatGPT.

Large network telemetry data lakes are often required to effectively train and tune AI models. 

What are some networking AIOps use cases?

What are some networking AIOps use cases?

AIOps helps address many of the most common challenges IT teams face today when it comes to operating their networks. These include:

  • Maintaining network configuration compliance - Static device settings do not keep up with changing business needs. AIOps continuously monitors network operations and recommends or automatically makes optimization changes.
  • Addressing changing business needs – Manually configuring Service Level Expectations (SLEs) is costly and time-consuming. With AIOps, important network thresholds are automatically defined, monitored, and adjusted based on environmental changes.
  • Resolving network issues quickly – In most IT organizations, help desk calls are the primary form of identifying problems, which is expensive and inefficient. The preemptive insights provided by AIOps help identify issues before they impact users or IoT devices for a reduction in help desk calls.
  • Replicating intermittent issues – Many IT teams spend hours or days tracking down intermittent problems because they are difficult to replicate. Automated, always-on monitoring via AIOps pinpoints persistent versus obvious problems, with built-in data capture.
  • Increasing network complexity - Troubleshooting and optimization tasks consume over 50% of IT’s time. AIOps solves this challenge by providing key insights such as the reasons for failures, root cause analysis, and repair recommendations.
  • Lacking resources and skills - Lack of resources and training are a constant point of contention in many IT organizations. AIOps-driven insights, such as GenAI-powered search features, are designed to assist and enhance the team’s knowledge base.
HPE and AIOps

HPE and AIOps

Maintaining a network today requires full-time visibility and automation. HPE Aruba Networking Central with AIOps can help:

  • Identify network, security and application performance issues before they affect your users and business.
  • Eliminate much of the manual troubleshooting tasks that keep IT teams buried in busy work.
  • Provide optimization tips as your network experiences changes, like an increase in IoT devices or more apps like Zoom or Teams.
  • Provide quick and easy answers to important questions, configuration and troubleshooting tips, and more through a GenAI-powered search interface.

The HPE Aruba Networking AIOps advantage starts with great AI. We collect dozens of terabytes of useful data per day, from tens of thousands of installations that range from small stores and offices to large campuses across all verticals and geographies to form our data lake. Our deep understanding of networking and security technology, and strong team of data scientists then deliver the insights needed to quickly preempt or resolve issues in a fraction of the time required in the past.

Related topics

Artificial Intelligence

AI Networking

Data lakes