Hewlett Packard Enterprise (HPE) added agentic AI management capabilities to its Greenlake platform in an attempt to better coordinate data flows between a user’s preferred hybrid IT environment and feeding that AI-modeled data into agents that can support system processes.

The Greenlake Intelligence platform basically acts as a planning agent that can intake insight from across the Greenlake platform of services – networking, servers, storage, software – or even third-party sources and parse out the relevant information to AI agents. These agents can then feed their insight through a model context protocol (MCP) to help manage various HPE services like its AI Essentials, HPE Virtualization, or Aruba network management.

Varma Kunaparaju, SVP and GM of HPE’s OpsRamp Software and Cloud Platforms, explained during a press briefing that the platform is targeted at “embedding intelligence directly into the operational stack so that the IT teams can act with speed and confidence.”

That intelligence comes from what Kunaparaju said were about 20 trillion metrics from across the globe that HPE collects, adding that the “intelligence only comes from raw data that we collect, and we basically analyze the data using all the advances that took place in the genAI and, more importantly, customizable foundational models that we fine-tuned for being able to deliver the outcomes.”

“Ultimately, the goal here is being able to reason and understand the multivendor, multicloud, full-stack context to be able to deliver that intelligence that is needed,” Kunaparaju said. “The unique, highly differentiated HPE IP in this area is not only being able to deliver this across HPE stacks but being able to address the other vendors and multcloud estates of every enterprise application.”

More intelligence for Aruba

HPE is also infusing its Aruba Networking Central platform with those agentic AI updates. This allows the Aruba platform to provide root-cause analysis for network or security issues and help guide or automate remediation for those issues.

David Hughes, SVP and chief product officer for HPE Aruba Networking, noted that the Aruba service has been collecting telemetry data for more than a decade, with the current deployment across more than six million network devices representing more than three billion unique client endpoints.

“All of this data is anonymized and fed into a large data lake against which we can run all different kinds of data science, data analysis, and AI techniques,” Hughes explained. However, this wealth of data eventually overwhelmed legacy technology’s ability to cope with and parse out that data into useful information. “Some of these limitations can be very well addressed with agentic AI.”

Hughes said that the Greenlake Intelligence integration into Aruba Networking Central allows for an “autonomous supervisory AI module talk to many different specialized sub-agents.” This, unlike traditional genAI, “can actually work its way down that list, take those actions, collect that data, analyze the overall result, come up with a root cause, and from there figure out a proposed recommendation.”

“It's like having a teammate that can work while you're asleep, work on problems, and when you arrive in the morning, have those proposed answers there, complete with chain of thought logic explaining how they got to their conclusions,” Hughes added.

Agentic AI gaining network support

This agentic AI integration move is similar to what other vendors are starting to do across the networking space.

Cisco, for instance, recently pointed toward OpenAI’s latest Codex AI coding agent as the agentic future of AI and that more robust networks and control will be needed to support increased agentic AI-driven traffic.

“We envision a future where billions of AI agents are working together harmoniously on our behalf, around the globe and around the clock,” Cisco Chief Product Officer Jeetu Patel wrote in a recent blog post, adding that this will shine a brighter focus on network constraints. “None of this will work without ultra-fast, low-latency, energy-efficient, and highly secure networks.”

Patel’s words were conveniently echoed by Cisco CEO Chuck Robbins, who during the vendor’s most recent earnings call explained that Cisco’s evolving AI-related revenues showed “the growing importance of our technology to web-scale customers for their AI training use cases.”

“With agentic AI, the network is fundamentally constrained and will require ultrafast, low-latency, energy-efficient networks, which we can deliver,” Robbins added.

HPE’s Greenlake Intelligence and updated Aruba Networking Central platforms are set to launch during the third quarter of this year.