Aruba, a Hewlett Packard Enterprise company, has announced new Aruba ESP (Edge Services Platform) AIOps capabilities that allow IT professionals to greatly reduce the time spent on manual tasks such as network troubleshooting, performance tuning, and Zero Trust/SASE security enforcement.
Part of Aruba's growing family of AIOps solutions, the new capabilities supplement overtaxed IT teams as they grapple with increasing network complexity and the rapid growth of IoT. For the first time, AIOps can be utilised for not just network troubleshooting but also performance optimisation and critical security controls.
As organisations pursue digital transformation initiatives, network modernisation is critical for achieving new business outcomes. However, with the growth of hybrid work, new user engagement models, and widening skills gaps, IT teams must find ways to achieve greater efficiencies. Yesterdays time-intensive manual processes are simply inadequate for todays quickly changing business environment. Powerful analytics, AI-based insights, and automation supplement not replace networking teams by reducing manual tasks so they can focus on more strategic and higher-value projects.
In development since 2013, Aruba AIOps capabilities leverage Arubas industry-leading data lake, which continuously and anonymously collects and analyses device, user, and location data from over 120,000 Aruba Central customers, from more than 2 million network devices and 200 million clients per day. The unmatched reliability of Arubas AI is directly related to the high volume and wide variety of network and client data, the constant training of models, and the unique ability to provide insights that tackle both network and security concerns.
This allows network teams from every industry and size to trust that Aruba AIOps will automate mundane tasks, shrink the time needed to find and fix problems, increase security controls, and help ensure that all network users have the best possible experience.
"Our customers tell us that its incredibly hard to find technical staff and they need to do more with less," says Pat Devlin, Director of Aruba, South Pacific.
"When applying machine learning and AI to the network, you want your models to make accurate predictions, but accurate predications rely on a very large and diverse data lake. Aruba's vast data lake consists of deployments in every vertical, more than 100,000 customer configurations, more than 2 million devices under cloud management, and more than 200 million connected devices.
"This data lake provides the richness and diversity needed to train our machine learning models to solve everyday network issues.
"When we talk about AIOps, were showcasing how we can solve real problems in real-time, and were helping customers manage networks better with fewer people and less specialist expertise," says Devlin.
"We are delighted to see our offering of AIOps solutions continue to develop and grow as network modernisation solutions move to the forefront of business agendas."
The new AI-powered IT efficiency features include:
Aruba Client Insights: Automatically identifies each endpoint connecting to the network with up to 99% accuracy, which is especially important as increasing numbers of IoT devices are added to networks, sometimes without approval from IT. This allows organisations to better understand whats on their networks, automate access privileges, and monitor the behaviour of each clients traffic flows to more rapidly spot attacks and take action.
AI-powered Firmware Recommender: Provides IT teams with the best version of firmware to run for the wireless access points in their environments regardless of model numbers. This greatly reduces support calls and guesswork that network admins face and helps ensure new features and fixes are implemented more quick
Automated Infrastructure Predictions: Leverages Arubas AI Assist feature and Aruba Support outreach to recognise possible hardware and software infrastructure issues for pre-emptive engagement that can consist of firmware upgrades or recommended hardware replacement.
"With hybrid work and new customer engagement models, network complexity is unavoidable as organisations modernise their network infrastructure to successfully support corporate initiatives," says Bob Laliberte, principal analyst at Enterprise Strategy Group.
"When a network vendor demonstrates reliable, real-world AI solutions, NetOps teams are increasingly adopting and trusting the actions of machine learning and other automation technologies.
"In fact, ESG research highlights that almost a quarter (21%) of organisations are comfortable with software that automatically detects, analyses, recommends, and makes network changes, and 59% report being comfortable with technology that alerts and provides recommendations, which are then manually executed.
"We expect these percentages to climb as more organisations gain experience with and recognise the benefits AI delivers."