AI networking platform boosts observability and AIOps
Juniper Networks has announced key innovations in the Mist™ AI-native networking platform, which brings expanded insights to wired, wireless, and WAN customers and partners.
Enhanced Marvis Minis extends digital experience twinning across the global WAN, reaching into both public and private cloud environments and applications. A new Marvis Actions self-driving dashboard simplifies network operations by seamlessly identifying and resolving network issues and continuously optimising network experience and performance without manual operator intervention. An enhanced Marvis mobile client expands Mist’s industry-leading AI-native Operations (AIOps) to end-user devices.
“The Mist AI-native networking platform was purpose-built to converge AI and networking for exceptional operator and end-user experiences,” said Sudheer Matta, Senior Vice President of Products, Campus and Branch at Juniper Networks. “These enhancements shift the paradigm from traditional observability to an AI-native model for truly understanding user experience that’s actionable at scale. We think of the new Marvis Minis as a million Minis—digital experience twins working in unison to proactively identify, learn and act before issues impact the user. With Marvis Minis, Juniper continues to deliver state-of-the-art automation, insight and assurance—setting the stage for a foundational shift to agentic AI in the networking industry.”
The Marvis Minis digital experience twinning capabilities now proactively analyse user experiences end-to-end, from client to cloud to baseline, pinpointing precisely where application performance may be suffering. Marvis Minis now offers new service level expectations (SLEs) that deliver increased visibility into application performance across various levels, such as at the site, across sites, and regions within an ISP, making troubleshooting faster and more efficient. With end-to-end monitoring, Marvis Minis identifies and resolves issues before they impact the end-user experience. Unlike traditional observability tools that require agents, sensors, or customer-side deployment, Marvis Minis provides a fully seamless experience powered by AI.
Ideal for self-driving networks, Marvis AI Assistant proactively resolves network issues like VLAN misconfigurations and network loops, optimises Radio Resource Management (RRM) and automates routine tasks such as policy updates and firmware compliance, increasing overall efficiency. The new Marvis Actions dashboard view fully controls when and how these self-driving network operations are enabled. It also provides a detailed history of all proactive actions, whether fully self-driving or assisted, along with insights into how Marvis AI Assistant identified and resolved each issue, empowering customers to manage their network on their terms.
Marvis Client, an enhanced Marvis AI Assistant extension, utilises client-side telemetry from Android®, Windows®, and macOS® devices to provide deeper insights into user experiences. Rich data such as device type, operating system, radio hardware, firmware, and connectivity metrics are transmitted in near real-time to the Mist cloud, where Marvis AI Assistant processes it to generate actionable insights. When these insights are further complemented by data collected from Juniper Access Points, routers, switches, and firewalls, IT teams can proactively address performance issues, improve troubleshooting, and enable a consistently high-quality user experience. All of this is achieved without additional software or hardware sensors, thereby minimising cost and complexity while maximising value.
To overcome the increased complexity of highly distributed networks, organisations must adopt self-driving networks and agentic AI technologies. These advances will enhance operational efficiency, improve customer experiences, and provide better business insights. It all starts with a comprehensive, granular understanding of the network, users, and applications environment,” said Bob Laliberte, Principal Analyst at CUBE Research. “By leveraging an innovative and established AI-native networking platform, Juniper continues to raise the bar for end-to-end visibility and proactive control in modern network environments.
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