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HPE Aruba Networking and HPE Juniper Networking Platforms Add AIOps

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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

HPE Aruba Networking and HPE Juniper Networking Platforms Add AIOps

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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...