Juniper Networks added capabilities to its AI-Native Networking Platform and enhancements to its Marvis platform, an AI-driven virtual networking assistant offering advanced analytics, automation and troubleshooting capabilities.

Marvis now has the capability to detect misconfigured switch ports, which can disrupt network operations, and to identify wireless access point (AP) loops, a common source of interference and network issues.

It continuously monitors for security risks and automates tasks, while the cloud-based Mist platform provides scalability and a single point of control for managing the whole network, from data center to cloud.

Juniper also introduced features to detect unreachable APs, aiding in troubleshooting during ISP outages or other connectivity issues.

For wireless customers, Juniper introduces the AI-Native Dynamic Spectrum Capture feature, providing extended visibility into RF spectrum to expedite problem detection and root cause identification for wireless interference issues.

Marvis Minis, the company’s twinning solution for wireless, now extends issue identification to the wired network, diagnosing authentication issues and prescribing solutions preemptively.

Customizable Service Level Expectations (SLEs) improve user experiences by monitoring key wireless, wired, WAN and application metrics in real-time.

On the troubleshooting front, Juniper introduced AI-Native Dynamic Spectrum Capture to address wireless interference, providing additional visibility into RF spectrum.

Wired Dynamic Packet Capture expands real-time issue detection to wired networks, automating root cause identification without onsite visits.

To prevent non-compliant usage, Juniper integrated its Mist Access Assurance service with a host of UEM/MDM solutions.

Cloud-Native eduroam Support extends seamless onboarding to more than 10,000 eduroam-connected locations worldwide, offering various authentication methods for different types of clients.

Sudheer Matta, group vice president for products campus and branch, Juniper Networks, explained AI-Native is built on a modern, microservices-based, elastic cloud providing the compute requirements to run the AI.

The company utilizes AI to shift network management from reactive troubleshooting to proactive issue prevention.

“This focus extends beyond basic functionality to optimizing user experience for critical applications,” he said.

The AI technology also automates tedious tasks, like manual configurations, freeing IT staff for strategic initiatives and reducing operational costs— helping reduce trouble tickets and expenses.

Marvis Application Experience Insights, for example, determines application performance through the integration of the Shapley data science model with Juniper’s continuous user experience learning to support Zoom and Microsoft Teams.

This approach enables accurate root cause analysis of potential user experience issues, whether in the WAN, wireless, or a client.

“Intuitive visualizations that list AP, client and feature ranking distributions make it easier to proactively address the issues to ensure that collaboration applications are performing optimally, which we expect to deliver exceptional user experiences,” Matta said.

He added the company’s virtual network assistant (VNA) “changes the operational paradigm”, helping IT teams move away from tedious Command Line Interface (CLI) duties, log files and even dashboards.

“IT networking teams simply converse with the network using natural human language,” he said. “The result is the right real-time response, whether troubleshooting a network issue or proactively surfacing issues, all aimed at delivering an optimal end-user experience.”

Matta noted today’s organizations constantly struggle with complex network challenges like the need to reduce network operation costs, scaling for growth, ever-increasing security threats, and lack of visibility across their network.

“Traditional networks struggle to keep pace and are reactive,” he said.

By leveraging AI, Juniper’s networking automation features can both tighten security and optimize IT operations costs for organizations.

“Juniper, leveraging Mist AI, can autonomously detect and respond to security threats,” Matta said. “This reduces the window of vulnerability and simplifies policy management.”

He explained automation also extends to troubleshooting and configuration tasks, freeing up IT staff and minimizing human error.

Matta pointed out the significant increase in remote work has impacted networking needs and monitoring, and noted IT teams, traditionally focused on on-premises security, now struggle with securing a wider range of connections.

“AI-Native proactive monitoring solutions allow adaptability, extending beyond company walls to encompass employee home networks and the cloud applications they rely on,” he said.

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