Juniper unveils Mist AI updates to boost network automation
Juniper Networks has announced updates to its Mist AI-native networking platform, which include new automated network issue resolution, expanded monitoring across environments, and improved device-side telemetry capabilities.
The new features introduced in the Mist platform focus on providing greater visibility and control for enterprises managing increasingly complex networks. The enhancements are designed to deliver expanded insights and assurance to users across wired, wireless, and wide area network (WAN) environments.
A key component of the upgrade is the Marvis Minis digital experience monitoring, which now offers end-to-end analysis from client to cloud. Marvis Minis enables users to baseline and pinpoint where application performance may be suffering, with no requirement for additional agents or sensors. The latest version delivers new service level expectations (SLEs), supporting increased visibility into application performance at the site, across sites, in different regions, and within individual internet service providers.
"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, Products, Campus and Branch, 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."
Marvis Minis is engineered to provide comprehensive monitoring and swift identification of performance problems, aiming to resolve issues before they impact end user experience. The platform extension is intended to make troubleshooting network and application issues faster and more efficient in both public and private cloud environments.
Andy Lorenc, Network Engineer at Robert Half, commented on their experience with Marvis Minis, stating: "Marvis Minis has been a game changer for us by providing precise, proactive alerts about site issues. Through hourly synthetic tests on our network systems, we identify problems before customers arrive, giving us enough time to address and resolve them. By pinpointing the exact areas causing issues, we spend much less time and effort troubleshooting. That's why we're so excited about the addition of client-to-cloud and the fact that we now have complete real-time visibility and a unified view across devices, the network, and applications. Troubleshooting is only getting easier—another significant benefit of having Marvis Minis fully integrated into Mist and a part of our existing Marvis subscription with ever expanding features and toolsets that bring more value to existing investment."
Alongside these monitoring capabilities, a new Marvis Actions dashboard has been introduced. This visual dashboard focuses on self-driving network operations and allows IT teams to manage and maintain full control over when and how automated tasks are enabled. The dashboard also provides users with a history of all proactive actions taken, whether autonomous or assisted, along with information on how each issue was identified and resolved by Marvis AI Assistant.
Complementing these updates, the Marvis Client now brings device-side telemetry from Android, Windows, and macOS devices. The system collects data on device type, operating system, radio hardware, firmware, and connectivity metrics, which is then processed by the Mist cloud for actionable insights. This approach is achieved without requiring additional agents or hardware sensors, reducing complexity and associated costs for network operators.
The ability of Marvis Client to capture and transmit telemetry in near real-time is designed to provide IT departments with a clearer understanding of user experiences and to aid in identifying and resolving issues affecting user performance. When combined with data from Juniper access points, routers, switches, and firewalls, IT teams can address problems promptly and consistently, contributing to the maintenance of high-quality user experiences.
The updated platform fits into a broader industry trend towards more automated, AI-driven network operations, as organisations seek to adapt to environments with rising complexity and distributed assets.
Bob Laliberte, Principal Analyst at theCUBE Research, commented on the developments. "To overcome the increased complexity of highly distributed networks, organizations need to adopt self-driving networks and agentic AI technologies. These advances will enable increased operational efficiency, enhanced customer experiences and better business insights. It all starts with a comprehensive, granular understanding of the network, users and applications environment. 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."
