HPE announced new self-driving network capabilities enabling fully autonomous, agentic AIOps networking.
With the introduction of new self-driving actions across HPE Mist and HPE Aruba Central, HPE delivers on its vision of secure, AI-native, fully autonomous networking by enabling networks that can detect, diagnose, and resolve issues in real time without human intervention. Central to this approach is a differentiated architecture powered by microservices, autonomous agents, and an advanced agentic mesh, designed to move beyond insight-driven operations to true autonomy, and proactively resolve issues before they impact revenue, operations, or brand reputation.
“The self-driving network is no longer aspirational; it’s operational,” said Rami Rahim, EVP, president and GM, Networking, HPE. “The network HPE now delivers represents a pivotal shift for our customers, and marks a breakaway moment for them to capture the benefits of the next frontier of autonomous actions. This fundamentally changes the role of networking from a system that informs to one that takes action on behalf of the business, freeing customer networking teams to focus on innovation instead of operations.”
HPE is expanding the capabilities of its self‑driving network with new autonomous actions, driven by autonomous agents and powered by agentic AI across its HPE Mist and HPE Aruba Central platforms, further reducing the need for manual intervention. New agents announced today now deliver capacity and radio optimization, self-securing actions, and user roaming issue resolution.
Together, these capabilities enable networks to proactively improve user experience and prevent issues before they disrupt business operations. New self‑driving actions designed to optimize and secure end user experiences include:
- Dynamic Capacity Optimization: Autonomously identifies capacity bottlenecks and dynamically tunes RF parameters, including band selection, channel bandwidth, and power levels, beyond predefined operational ranges by leveraging learned utilization patterns. This delivers optimized end-user capacity, coverage, and roaming experiences for wireless users.
- Autonomous Missing VLAN Remediation: A trusted self-driving action that autonomously fixes VLAN configuration errors in the access layer to prevent blackholing of client traffic. This is an evolution from driver-assisted VLAN remediation, assuring even faster problem resolution for better user experiences.
- Rogue DHCP Protection: Autonomously detects and remediates unauthorized DHCP servers to mitigate potential external security risks and prevent end user connectivity disruptions.
- Real-time Dynamic Frequency Selection (DFS): Self-driving complements AI-driven Radio Resource Management (RRM) to adaptively learn and proactively avoid association issues on frequently impacted channels to mitigate wireless client disruptions.
- Client Roaming Optimization: Ensure smooth, uninterrupted roaming for users by analyzing client connectivity metrics, including location, leading to self-driving actions. User Experience Latency Metrics: Accelerate root‑cause identification by measuring Wi‑Fi performance at “first connect” and providing clear, end‑to‑end visibility into latency from the user’s device to the cloud.
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