Juniper Networks Expands Mist AI Platform with Client-to-Cloud Insights and Self-Driving Network Capabilities The improvements aim to address the increasing complexity of modern networks by automating routine tasks, providing real-time visibility into application performance, and proactively resolving issues without manual intervention
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Juniper Networks has launched a series of enhancements to its Mist AI-native networking platform, aiming to provide deeper automation, observability, and operational efficiency across wired, wireless, and WAN environments. The updates include the expansion of its digital experience monitoring tool, Marvis Minis, across global cloud networks, a new self-driving dashboard via Marvis Actions, and client-side telemetry support through Marvis Client.
The improvements aim to address the increasing complexity of modern networks by automating routine tasks, providing real-time visibility into application performance, and proactively resolving issues without manual intervention.
"The Mist AI-native networking platform was purpose-built to converge AI and networking for exceptional operator and end user experiences. 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," said Sudheer Matta, Senior Vice President of Products for Campus and Branch at Juniper Networks.
The enhanced Marvis Minis feature now offers end-to-end visibility into network and application performance across client devices, ISPs, and both public and private cloud environments. The tool introduces new service level expectations (SLEs) that allow organisations to pinpoint performance issues by location or service layer. Unlike traditional observability systems, Marvis Minis does not require agents or external sensors, offering a native AI-powered monitoring solution.
"Through hourly synthetic tests on our network systems, we identify problems before customers arrive. The addition of client-to-cloud visibility gives us a unified view across devices, the network, and applications. Troubleshooting is only getting easier," Andy Lorenc, Network Engineer at Robert Half, a Juniper customer, noted.
Juniper has also launched a Marvis Actions dashboard that aligns with its long-standing vision of self-driving networks. The dashboard allows network operators to view and manage automated decisions made by the Marvis AI Assistant. These include resolving VLAN misconfigurations, optimising radio resources, automating policy updates, and ensuring firmware compliance.
The dashboard provides detailed insights into every automated or assisted action, empowering IT teams to monitor, approve, or modify automated interventions based on internal protocols.
Meanwhile, the Marvis Client extension enables telemetry collection from Android, Windows and macOS devices, feeding real-time data into the Mist cloud. Bob Laliberte, Principal Analyst at theCUBE Research, commented, "To overcome the increased complexity of highly distributed networks, organisations need to adopt self-driving networks and agentic AI technologies. Juniper continues to raise the bar for end-to-end visibility and proactive control in modern network environments."
