HPE Unveils Agentic AI-Native Innovations for Proactive Self-Driving Network Operations

HPE Advances Self-Driving Network Operations with Agentic AI Innovations

HPE has taken a significant step forward with its Juniper Networking portfolio by enhancing its AI-native Mist platform to enable more autonomous and intelligent network management. The latest updates introduce agentic AI-powered troubleshooting, broader control of self-driving actions, a new Large Experience Model (LEM), and advanced AIOps features specifically for data centers.

These improvements are part of GreenLake Intelligence, HPE’s approach to autonomous IT and agentic AIOps. By embedding specialized AI agents across networking, storage, and computing layers, HPE provides real-time problem-solving and optimization. This shift moves IT teams from reactive firefighting to proactive, efficient management.

Agentic AI Drives Smarter Network Operations

HPE Juniper Networking has led the move to cloud- and AI-native self-driving operations, focusing on delivering seamless user experiences from client devices to the cloud. The Marvis AI engine collects telemetry data across wired, wireless, WAN, and data center environments, automating workflows to simplify operations and reduce costs.

Marvis AI also learns continuously by analyzing support tickets, improving its troubleshooting capabilities. Its fully API-driven design integrates smoothly with tools like Zoom, Teams, and ServiceNow, helping operations teams quickly identify and resolve root causes.

Key Enhancements to the Mist Platform

• Enhanced Conversational AI: Marvis AI now features improved conversational abilities, enabling real-time troubleshooting with agentic AI-powered insights. Self-driving agents collaborate across various network domains to provide customized guidance.
• Expanded Self-Driving Actions: The Marvis Actions dashboard supports autonomous fixes for more network issues, such as misconfigured ports, capacity bottlenecks, and non-compliant hardware—all while keeping IT in control.
• Generalized Large Experience Model (LEM): Unique to HPE Juniper Networking, LEM analyzes billions of data points from collaboration apps like Zoom and Teams. With Marvis Minis—digital twins simulating user experiences—it can predict application performance issues before they occur, enabling proactive optimization.
• AI for Data Center Operations: The Marvis AI Assistant for Data Center leverages Apstra’s graph database to provide intelligent insights and supports autonomous service provisioning. Marvis Minis extend continuous service validation to data center networks, ensuring consistent application performance.

Bringing It All Together for Operations Teams

HPE’s agentic AI capabilities extend across multi-vendor environments, integrating networking, compute, storage, virtualization, and applications. The data center features complement HPE OpsRamp, an AIOps platform designed to simplify hybrid and multi-cloud IT management with full-stack observability and automated workflows.

Operations teams face distributed and complex networks that are crucial to business success. According to industry analyst Bob Laliberte, HPE’s AI-driven approach enables predictive intervention, allowing teams to resolve issues before users experience any impact.

These advancements build on HPE’s decade of leadership in AI for networking, helping enterprises, cloud providers, and telcos improve efficiency, reliability, and user satisfaction at scale.

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