As part of its AI-Native Networking Platform, Juniper is extending its Marvis Minis to the wired network domain and increasing its ability to identify and remediate collaboration app performance issues.
Juniper Networks continues to expand its AI technology in an effort to ease network management tasks and simplify customers’ network operations.
The enhancements are intended to reinforce the vendor’s AI-Native Networking Platform, announced earlier this year, which brings Juniper’s wired, wireless data center, campus and branch networking products under one common management offering.
The platform works by gathering telemetry and user state data from Juniper’s routers, switches, access points, firewalls, and applications to offer actionable insights and automated workflows for proactive issue detection and resolution, Juniper says. At the core of the platform is the firm’s cloud-based, natural-language Mist AI and Marvis virtual network assistant (VNA) technology. Marvis can detect and describe countless network problems, including persistently failing wired or wireless clients, bad cables, access-point coverage issues, and problematic WAN links.
As part of its AI-Native rollout, the vendor introduced Marvis Minis for wireless deployments, which work by setting up a digital twin of a customer’s network environment to simulate and test user connections, validate network configurations, and find/detect problems without requiring any additional hardware, according to Juniper.
Minis simulate end user, device, and application traffic to learn the network configuration and proactively determine network issues. Data from Minis is continuously fed back into the Mist AI engine, providing an additional source of insight for the best AIOps responses, according to Juniper.
With this announcement, Juniper has now added Mini support for its wired world of switches and routers. In particular, Minis now can find problems such as switch authorization snags related to RADIUS server failures and offer prescriptive actions to fix these issues before complications arise.
“Marvis Minis for wired enables Marvis to make network operations proactive by diagnosing wired authentication issues without the need for users or devices to be connected. And just like Marvis Minis in wireless, it doesn’t require any additional network sensors or agents,” wrote Sudheer Matta, group vice president of products for Juniper’s AI-driven enterprise portfolio, in a blog about the new features.
“Minis simulates user experiences, identifying potential problems so IT can act before users encounter them and need to submit a trouble ticket. This proactive approach to troubleshooting not only saves users and IT valuable time and improves network performance, but it also leads to significant cost savings,” Matta stated.
Also for its wired customers, Juniper added support for dynamic packet capture (dCAP) to its Wired Assurance program to help customers more quickly detect issues and proactively capture packets in the cloud to help identify and fix the root cause of network problems. Wired Assurance is Juniper’s cloud-based management platform for managing enterprise campus wired networks and switches.
“With dPCAP, administrators can easily resolve intermittent issues that are otherwise almost impossible to diagnose and resolve,” Matta stated.
Marvis taps into collaboration app performance
In addition to improved wired management support, Juniper expanded its integration with Zoom and Microsoft Teams to feed new insights to its management platform and help IT teams resolve IT tickets faster. Last year, Juniper introduced a Zoom integration with Mist; with its new Marvis Application Experience Insights, Juniper is offering deeper AI-native support for both Zoom and Microsoft Teams.
The idea is to allow accurate root cause analysis of potential user experience issues, whether in the WAN, wireless, or a client, Matta stated. “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,” he wrote.
Accelerating network troubleshooting
To its core Marvis package, Juniper added the ability to detect misconfigured switch ports, which misdirect or cause problems within the network. In addition, Juniper added the ability to detect wireless access point (AP) loops where the wireless signals from two or more APs form a continuous loop, potentially causing interference and network problems, Matta stated. The package can now also detect APs that may be unreachable due to an ISP outage or other reason.
Also for its wireless customers, Juniper added an AI-Native Dynamic Spectrum Capture feature that offers extended visibility into RF spectrum to accelerate problem detection and more easily identify the root cause of wireless interference issues. These features enhance network troubleshooting by identifying and addressing more of the common issues that impact wireless connectivity and performance, Matta stated.
According to Matta, Juniper has also added customizable service level expectations (SLEs) that monitor the status of key wireless, wired, WAN and application metrics to assure the best user experiences.
“The existing wired SLEs for throughput, switch health and connection have been augmented with new SLEs that also cover switch bandwidth utilization, successful connections to RADIUS servers and switch capacity,” Matta stated. “These monitor and enforce key wired metrics in real-time to assure exceptional ongoing user experiences over a Juniper wired network.”
AI portfolio key draw for HPE
Juniper’s AI portfolio is among its crown jewels, particularly with respect to its pending $14 billion acquisition by HPE.
Public statements from HPE CEO Antonio Neri on the Juniper acquisition have often revolved around AI. When the deal was announced in January, he said: “This transaction will strengthen HPE’s position at the nexus of accelerating macro-AI trends, expand our total addressable market, and drive further innovation for customers as we help bridge the AI-native and cloud-native worlds.”
In a recent quarterly earnings call with Wall Street analysts, Neri added: “Combining our complementary portfolios will supercharge HPE’s edge-to-cloud strategy, accelerating our entire portfolio with AI enabled innovation.”
“The combination of HPE and Juniper will create a strong networking company that is well-positioned to compete in the expanding era of AI everywhere,” said Brandon Butler, research manager with IDC’s network infrastructure group, in a recent Network World story about the proposed acquisition. “There are two main aspects of the AI opportunity in networking this acquisition supports. The first is around building datacenter network infrastructure to support data intensive AI workloads. Juniper’s strength in datacenter and cloud networking will build on HPE’s broader edge-to-cloud portfolio.
“The second aspect of AI in networking is around AI Operations being used to enhance the management of the network. Here, Juniper’s Mist portfolio will complement the HPE Aruba networking division for AI-driven network management efficiencies across the campus, branch, datacenter, edge and cloud,” Butler said.
