HPE Aruba Networking and HPE Juniper Networking Platforms Add AIOps

Learn more about HPE

HPE expanded its AI-native networking portfolio that leverages HPE Aruba Networking and HPE Juniper Networking for self-driving operations to maximize performance and scale for AI workloads. 

This expansion includes new AIOps capabilities and common hardware that deliver a consistent, self-driving experience across both HPE Aruba Networking Central and HPE Juniper Networking Mist operations platforms. Coupled with updates to HPE OpsRamp Software and new HPE Juniper Networking switching and routing introductions, HPE expands the role of the network as the critical foundation enabling AI and cloud performance, while simplifying IT operations across hybrid environments using agentic AI compatible with GreenLake Intelligence.

“In the era of AI, customers need networks that are purpose-built with AI and for AI to handle the rapid growth of connected devices, complex environments, and increasing security threats,” said Rami Rahim, EVP, president and GM, Networking, HPE. “By delivering autonomous, high-performing networks, HPE is poised to disrupt the networking industry with future-ready solutions that redefine user experiences and provide robust, secure connectivity across all environments.”

HPE has brought together the best of HPE Aruba Networking Central and HPE Juniper Networking Mist, leveraging a common agentic AI and microservices framework to provide investment protection, while integrating key AI for networks features for a consistent experience and introducing new AI for network capabilities across both domains:

  • HPE Juniper Networking Mist Large Experience Model (LEM), which uses billions of data points from apps such as Zoom and Teams, combined with synthetic data from digital twins to rapidly detect, fix, and predict video issues, will now be available in HPE Aruba Networking Central.
  • HPE Aruba Networking’s Agentic Mesh technology will be available for Mist, enhancing anomaly detection and root-cause analysis with advanced reasoning and autonomous or assistive actions.
  • Mist will adopt the organizational insight and global NOC views from HPE Aruba Networking Central, delivering a unified user experience across both platforms.
  • New WiFi-7 access point models that work across HPE Aruba Networking Central and HPE Juniper Networking Mist, ensuring buyer protection.

HPE Aruba Networking Central On-Premises 3.0 now provides customers with powerful insights and automation in a secure, on-premises environment by incorporating advanced generative and traditional AIOps capabilities, actionable AI alerts, proactive remediation, intelligent client insights, and simplified documentation search – all managed through a redesigned user interface.

HPE is advancing its hybrid cloud and Agentic AIOps strategy with advancements that showcase full-stack, multi-domain, multi-vendor intelligence anchored by a shared resource model that spans hardware to public cloud. With these enhancements to HPE OpsRamp Software and deeper integration with GreenLake, HPE now brings together telemetry from HPE Compute Ops Management, HPE Aruba Networking Central, and HPE Juniper Networking Apstra to give IT operations teams a single place to see, interpret, and act on everything in their environment, forming the foundation of a true hybrid command center.

New innovations connect management and intelligence across the full stack empowering IT teams to monitor, understand, and act instantly on their entire hybrid environment, including:

  • Integration of HPE Juniper Networking’s Apstra Data Center Director and Data Center Assurance software with OpsRamp, available through GreenLake, delivers full-stack observability, predictive assurance, and proactive issue resolution across compute, storage, networking, and cloud.
  • New Compute Ops Management innovations—including OpsRamp integration, Compute Copilot, and self-service root-cause analysis—to centralize visibility, speed troubleshooting, and elevate the operator experience.
  • Agentic Root Causing & Model Context Protocol (MCP) Support (limited availability) in both GreenLake and HPE OpsRamp Software allows customers to connect AI agents from third-party software for no-code integrations, and enriches those agents, helping GreenLake Intelligence eliminate blind spots in dynamic environments.
  • New GreenLake Intelligence capabilities provide faster insights and guided actions with new AI agents for HPE Sustainability Insight Center, the GreenLake Wellness Dashboard, and OpsRamp Agentic Root Causing, helping bridge data silos and enable agentic analytics across the full IT stack.

HPE OpsRamp support and integrations timeline:

  • Model Context Protocol: Available now for select customers with full availability early 2026
  • Compute Ops Management: Available December 2025
  • Storage manager: Available February 2026
  • Apstra Data Center Director: Available Q2 2026
     

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HPE Aruba Networking and HPE Juniper Networking Platforms Add AIOps

Learn more about HPE

HPE expanded its AI-native networking portfolio that leverages HPE Aruba Networking and HPE Juniper Networking for self-driving operations to maximize performance and scale for AI workloads. 

This expansion includes new AIOps capabilities and common hardware that deliver a consistent, self-driving experience across both HPE Aruba Networking Central and HPE Juniper Networking Mist operations platforms. Coupled with updates to HPE OpsRamp Software and new HPE Juniper Networking switching and routing introductions, HPE expands the role of the network as the critical foundation enabling AI and cloud performance, while simplifying IT operations across hybrid environments using agentic AI compatible with GreenLake Intelligence.

“In the era of AI, customers need networks that are purpose-built with AI and for AI to handle the rapid growth of connected devices, complex environments, and increasing security threats,” said Rami Rahim, EVP, president and GM, Networking, HPE. “By delivering autonomous, high-performing networks, HPE is poised to disrupt the networking industry with future-ready solutions that redefine user experiences and provide robust, secure connectivity across all environments.”

HPE has brought together the best of HPE Aruba Networking Central and HPE Juniper Networking Mist, leveraging a common agentic AI and microservices framework to provide investment protection, while integrating key AI for networks features for a consistent experience and introducing new AI for network capabilities across both domains:

  • HPE Juniper Networking Mist Large Experience Model (LEM), which uses billions of data points from apps such as Zoom and Teams, combined with synthetic data from digital twins to rapidly detect, fix, and predict video issues, will now be available in HPE Aruba Networking Central.
  • HPE Aruba Networking’s Agentic Mesh technology will be available for Mist, enhancing anomaly detection and root-cause analysis with advanced reasoning and autonomous or assistive actions.
  • Mist will adopt the organizational insight and global NOC views from HPE Aruba Networking Central, delivering a unified user experience across both platforms.
  • New WiFi-7 access point models that work across HPE Aruba Networking Central and HPE Juniper Networking Mist, ensuring buyer protection.

HPE Aruba Networking Central On-Premises 3.0 now provides customers with powerful insights and automation in a secure, on-premises environment by incorporating advanced generative and traditional AIOps capabilities, actionable AI alerts, proactive remediation, intelligent client insights, and simplified documentation search – all managed through a redesigned user interface.

HPE is advancing its hybrid cloud and Agentic AIOps strategy with advancements that showcase full-stack, multi-domain, multi-vendor intelligence anchored by a shared resource model that spans hardware to public cloud. With these enhancements to HPE OpsRamp Software and deeper integration with GreenLake, HPE now brings together telemetry from HPE Compute Ops Management, HPE Aruba Networking Central, and HPE Juniper Networking Apstra to give IT operations teams a single place to see, interpret, and act on everything in their environment, forming the foundation of a true hybrid command center.

New innovations connect management and intelligence across the full stack empowering IT teams to monitor, understand, and act instantly on their entire hybrid environment, including:

  • Integration of HPE Juniper Networking’s Apstra Data Center Director and Data Center Assurance software with OpsRamp, available through GreenLake, delivers full-stack observability, predictive assurance, and proactive issue resolution across compute, storage, networking, and cloud.
  • New Compute Ops Management innovations—including OpsRamp integration, Compute Copilot, and self-service root-cause analysis—to centralize visibility, speed troubleshooting, and elevate the operator experience.
  • Agentic Root Causing & Model Context Protocol (MCP) Support (limited availability) in both GreenLake and HPE OpsRamp Software allows customers to connect AI agents from third-party software for no-code integrations, and enriches those agents, helping GreenLake Intelligence eliminate blind spots in dynamic environments.
  • New GreenLake Intelligence capabilities provide faster insights and guided actions with new AI agents for HPE Sustainability Insight Center, the GreenLake Wellness Dashboard, and OpsRamp Agentic Root Causing, helping bridge data silos and enable agentic analytics across the full IT stack.

HPE OpsRamp support and integrations timeline:

  • Model Context Protocol: Available now for select customers with full availability early 2026
  • Compute Ops Management: Available December 2025
  • Storage manager: Available February 2026
  • Apstra Data Center Director: Available Q2 2026
     

The Latest

Implementing AI Isn't the Hard Part Anymore - Adoption Is

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

The Incident Load Is Rising, but Recovery Times Aren't Moving

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

Your AI Pipeline May Have a Document Observability Problem

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

The SIEM Isn't the Problem. Your Telemetry Architecture Is

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

As AI Scales Across Enterprises, Breaking Points Emerge

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

Preparing Network Infrastructure for AI Starts with the Basics

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

The Network Data Problem Slowing Down Enterprise AIOps

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

The Governance Gap Behind AI's Infrastructure Problem

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

MEAN TIME TO INSIGHT Podcast - Episode 27: Observability Unification

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ...