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Juniper Networks Adds Capabilities to Mist AI-Native Networking Platform

Juniper Networks announced key innovations in the Mist™ AI-native networking platform that bring expanded insight and assurance 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 optimizing network experience and performance, without manual operator intervention, and an enhanced Marvis mobile client expands Mist’s AI-native Operations (AIOps) to end user devices. 

With these latest innovations in Mist, Juniper continues to lead the industry in AIOps from client-to-cloud, giving operators superior visibility and control of user experiences.

“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.”

Client-to-cloud experience twinning: With this enhancement, Marvis Minis digital experience twinning capabilities now proactively analyze user experiences end-to-end, from client-to-cloud to baseline and pinpoint exactly where application performance may be suffering. Marvis Minis now offers new service level expectations (SLEs) to deliver increased visibility into application performance across various levels, such as at site, across sites, regions, within an ISP, making troubleshooting faster and more efficient. With end-to-end monitoring, Marvis Minis now provides a comprehensive solution for identifying and resolving issues before they impact end user experience. Unlike traditional observability tools that require agents, sensors or customer-side deployment, Marvis Minis offers a fully seamless experience powered by AI.

Marvis Actions dashboard: Aligned with Juniper’s vision of self-driving networks, Marvis AI Assistant proactively resolves network issues like VLAN misconfigurations and network loops, optimizes Radio Resource Management (RRM) and automates routine tasks such as policy updates firmware compliance, increasing overall efficiency. The new Marvis Actions dashboard view gives full control over 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: Marvis Client, an enhanced Marvis AI Assistant extension, uses 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 (AP), 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 the need for additional software or hardware sensors, thereby minimizing cost and complexity and maximizing value.

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Juniper Networks Adds Capabilities to Mist AI-Native Networking Platform

Juniper Networks announced key innovations in the Mist™ AI-native networking platform that bring expanded insight and assurance 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 optimizing network experience and performance, without manual operator intervention, and an enhanced Marvis mobile client expands Mist’s AI-native Operations (AIOps) to end user devices. 

With these latest innovations in Mist, Juniper continues to lead the industry in AIOps from client-to-cloud, giving operators superior visibility and control of user experiences.

“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.”

Client-to-cloud experience twinning: With this enhancement, Marvis Minis digital experience twinning capabilities now proactively analyze user experiences end-to-end, from client-to-cloud to baseline and pinpoint exactly where application performance may be suffering. Marvis Minis now offers new service level expectations (SLEs) to deliver increased visibility into application performance across various levels, such as at site, across sites, regions, within an ISP, making troubleshooting faster and more efficient. With end-to-end monitoring, Marvis Minis now provides a comprehensive solution for identifying and resolving issues before they impact end user experience. Unlike traditional observability tools that require agents, sensors or customer-side deployment, Marvis Minis offers a fully seamless experience powered by AI.

Marvis Actions dashboard: Aligned with Juniper’s vision of self-driving networks, Marvis AI Assistant proactively resolves network issues like VLAN misconfigurations and network loops, optimizes Radio Resource Management (RRM) and automates routine tasks such as policy updates firmware compliance, increasing overall efficiency. The new Marvis Actions dashboard view gives full control over 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: Marvis Client, an enhanced Marvis AI Assistant extension, uses 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 (AP), 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 the need for additional software or hardware sensors, thereby minimizing cost and complexity and maximizing value.

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The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...

Almost half (48%) of employees admit they resent their jobs but stay anyway, according to research from Ivanti ... This has obvious consequences across the business, but we're overlooking the massive impact of resenteeism and presenteeism on IT. For IT professionals tasked with managing the backbone of modern business operations, these numbers spell big trouble ...

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...