HPE Juniper Unveils Agentic AI Innovations for Self-Driving Network Operations

HPE Juniper rolls out agentic AI to simplify IT operations and improve user experience - SiliconANGLE

HPE Juniper rolls out agentic AI to simplify IT operations and improve user experience Artificial intelligence is at the heart of almost every part of an organization's strategy, and that includes information technology operations. However, many organizations aren't seeing clear business results. In fact, a recent MIT Study found that 95% of generative AI projects are failing. One of the big reasons for failure is that AI is being deployed in silos resulting in partial insights into the broader ecosystem. In IT, technology teams have dealt with a patchwork of tools and dashboard and relied on "swivel chair" management. This obviously won't work with AIOps as the AI engine needs to understand the end-to-end environment. Further, the holy grail of AIOps is autonomous self-driving operations, which alleviate IT from mundane tasks that take time and money. Juniper Networks Inc.'s Mist platform, introduced over a decade ago, was purpose-built with AI in mind, leveraging automation and insight to optimize user experiences. Built into Mist is the Marvis AI engine and Assistant, which uses high quality data, advanced AI and machine learning data science, and a conversational interface to simplify deployment and troubleshooting. Now under Hewlett Packard Enterprise Co., Mist today has been brought together with Aruba Networks to form what they are calling the "secure AI-native network," which is a blend of leading AIOPs, product breadth and security to solve real customer and partner needs. Ultimately the company has a vision of using the platform to bring all HPE Networking products under common cloud management and AI engine with centralized operations. HPE Networking is framing agentic AI as a catalyst for self-driving networks, complementing the journey the company has been on for some time. In addition to previous agentic capabilities, which includes reenforced learning, open APIs and autonomous tools that proactively monitor and fix issues across multiple domains, the company has made additional enhancements to the Mist platform. They further shift networking from a reactive role, where issues are fixed after they happen, to a proactive role, where issues are anticipated and fixed automatically. "One thing that we added is the ability to choose specific areas for self-driving mode that don't require human intervention," said Jeff Aaron, vice president of product and solution marketing at HPE. "If a switch port is stuck or an AP is running non-compliant software, for example, you can tell Marvis to go fix it on its own. We provide reporting to show which features were fixed autonomously, how they were fixed, and why the decision was made so IT still has complete visibility into what is happening." In addition, Marvis got a back-end upgrade, leveraging more generative AI capabilities and agentic workflows for even better real-time troubleshooting. The assistant has always used natural language processing and understanding to understand simple language queries and provide insightful answers on par with human experts. Recently, gen AI has been introduced to Marvis' robust data science toolbox for even more human-like interactions. Agentic workflows enable better correlation across domains for faster and more accurate troubleshooting. For example, an office outage can easily be pinpointed to a wide-area network capacity issue with recommended fixes based on feedback from wired, wireless, WAN and other agents. Furthermore, Marvis' AIOps capabilities have been expanded further into the data center through tighter integration with Juniper Apstra's contextual graph database. This allows Marvis to analyze infrastructure configurations and provide answers to data center-related inquiries using the same Marvis conversational interface employed elsewhere in the network. Aaron noted that in the past, Marvis had to launch Apstra via application programming interfaces to make data center changes, but now more can be done right form within the Mist cloud. This upgrade brings the data center closer to parity with wireless networking when it comes to self-driving, where Marvis has had more mature capabilities. Finally, HPE Networks also expanded their ability to proactively predict and prevent video issues using what it calls a large experience model or LEM. This pulls in billions of data points from Zoom and Microsoft Teams clients and correlates it with networking data to identify the root cause of video issues. The LEM framework has now been augmented with data from Marvis digital experience twins, or Minis, which probe the wired, wireless, WAN and data center networks autonomously when users aren't even present to provide even richer data for predictive and proactive troubleshooting. The secure, AI-native network with the latest Marvis updates builds on the benefits customers are already seeing with Mist. The impact shows up in different ways across industries. ServiceNow reported a 90% reduction in network trouble tickets, while Blue Diamond Growers cut the time spent managing networks by 80%. Gap achieved 85% fewer truck rolls, and Bethesda Medical reported 85% faster upgrades. HPE Juniper is further along in real-world use cases than most of its competitors. While many competitors are showing conceptual use cases, HPE Juniper already has many of its AI-native features available, supported by a long history with Mist and deeper AI maturity. In fact, Mist came to market using AI to troubleshoot Wi-Fi, which I consider one of the toughest network technologies to support. Mist's value was always measured by its ability to cut down on network trouble tickets, which resonated with IT teams. That message still matters, but now the emphasis is on broader business outcomes. The unified HPE Juniper platform is relevant to both IT and business leaders who want to see measurable results from their investments. "The benefits of the platform are better operational experiences," Aaron said. "That leads to better end-user benefits across our joint customers. In theory, the end user shouldn't even know the network exists -- it just does what it needs to do. Ultimately, it's about better business outcomes. You can drive more agility with less business risk, and you can get greater productivity." On a grander scale, the race to AI-native networking is heating up. Most vendors will have solid AI and automation stories within a year. The differentiator will be whether they can deliver true end-to-end, cross-network capabilities. Historically, network teams treated the campus, WAN, wireless network and data center as separate entities, but in reality, it's one network and a vendors AI engine needs to span from the data center out to the cloud to automate IT operations. Though there are always challenges, Aaron noted that both HPE and Juniper have a strong track record of integrating solutions, with Aruba and Mist being two respective examples. This latest announcement shows that innovation isn't slowing down post-acquisition, with more development promised on both Aruba and Mist products as they collectively journey to a common goal of AI-native self-driving.

Hewlett Packard Enterprise Company Accelerates Self-Driving Network Operations with New Mist Agentic AI-Native Innovations

Hewlett Packard Enterprise Company announced major innovations to its HPE Juniper Networking portfolio, advancing its AI-native Mist platform to deliver agentic AIOps through more autonomous, intelligent and proactive network operations. New enhancements include agentic AI-powered troubleshooting, expanded visibility and control of self-driving actions, a generalized Large Experience Model (LEM) and new AIOps features for data centers--designed to reduce IT complexity and assure exceptional user experiences from client to cloud. These new capabilities bolster GreenLake Intelligence, HPE's next-generation approach to autonomous IT and agentic AIOps, which deploys specialized AI agents within a multi-layered IT architecture. This enables real-time problem-solving, proactive optimization and smarter decision-making across networking, storage and compute. The agentic AI capabilities within Juniper Mist shift IT from reactive to proactive management, laying the groundwork for significant improvements in performance and efficiency. Now enhanced with Marvis Minis--twins that simulate user experiences--LEM can predict future application experiences without real-time data from the applications themselves. This is fed into the Marvis AI engine where self-driving actions can be taken to optimize future performance, prior to users even being present. AI for Data Center Operations. The Marvis AI Assistant for Data Center integrates with Apstra's contextual graph database to deliver intelligent insights and lay the groundwork for autonomous service provisioning. Marvis Minis also extends to the data center for continuous service validation and application assuranceinent to data center networks. HPE is uniquely positioned to unlock exceptional customer value by applying AIOps and agentic AI across multi-vendor full stacks, integrating outcomes from networking, compute, storage, virtualization, containerization, and applications. The latest Marvis data center capabilities complement HPE OpsRamp, an AIOps-powered IT operations management (ITOM) platform designed to simplify and automate the management of hybrid, multi-cloud, and on-premises IT environments with full-stack observability and advanced agentic workflows tailored for the modern data center. These innovations build on HPE's decade-long leadership in AI for networking, helping enterprises, cloud providers and telcos drive greater efficiency, reliability and user satisfaction.