The News: Juniper Networks announced its AI-Native Networking Platform, built to use AI with the goal of ensuring end-to-end operator and end-user experiences. Read the full press release on the Juniper website.
Juniper AI-Native Networking Platform: Ready to Transform AI
Analyst Take: Juniper Networks debuts its AI-Native Networking Platform, aimed at delivering exceptional user experiences and lowering operational costs across the digital ecosystem. Trained across seven years of insights and data science development, Juniper’s AI-Native Networking Platform was designed from inception to ensure that every connection is reliable, secure, and measurable for every device, user, application, and asset.
To fulfill that strategic objective, Juniper’s AI-Networking Platform combines all campus, branch, and data center networking solutions with a common AI engine and Marvis Virtual Network Assistant (VNA). The solution is developed to enable end-to-end AI for IT Operations (AIOps) to be used for deep insight, automated troubleshooting, and comprehensive network assurance, liberating IT teams and workforces from manual tasks by providing streamlined Day 0/1/2+ operations. This can result in up to 85% lower operational expenditures than traditional solutions, the elimination of up to 90% of network trouble tickets, 85% of IT onsite visits, and up to 50% reduction in network incident resolution times.
Juniper AI-Networking Platforms: What Is New and Different
The new AI-Native Networking Platform includes two new enhancements to Marvis with proactive recommendations and self-driving operations plus a conversation interface (using generative AI for some use cases). Specifically, Marvis Minis, an AI-Native Networking Digital Experience Twin, uses Mist AI to proactively simulate user connections to validate network configurations and detect problems without the immediate presence of users.
Plus, Juniper is debuting AI-Native VNA for the data center, delivering insight throughout the entire data center lifecycle across any vendor’s hardware. This includes issues with data center cabling, configuration and connectivity from any vendor’s hardware are surfaced in the Marvis Actions UI (from Juniper Apstra) with suggested proactive actions.
Integral to the new launch is that Juniper is expanding its AI Data Center solution. The new products and capabilities include Juniper Apstra updates that provide faster and more efficient processing of AI/ML traffic over Ethernet, new Express 5 silicon based PTX routers and line cards, and new QFX switch using Broadcom’s Tomahawk 5 silicon for 800GE.
The Juniper solution encompasses spine-leaf data center architecture with a foundation of QFX switches and PTX routers operated by Juniper Apstra, where I see it gaining more share by virtue of Apstra’s multi-vendor data center fabric management capabilities. Combined with Apstra’s intent-based operations, the Marvis VNA for data center is solidly positioned to decrease AI data center networking design, deployment, and troubleshooting.
Of key importance, Juniper’s new solution directly addresses unique AI/ML workload requirements and organization pain points within data center environments such as scaling massive flows alongside flow infrequency and low entropy. Plus, nodes transmit traffic simultaneously that rapidly saturate links as well as acute sensitivity to packet loss and jitter. As a result, job completion time (JCT) metrics are vital to understanding AI model performance and economics, especially as GPUs are limited in supply and expensive.
Juniper AI-optimized Ethernet Proposition Directly and Refreshingly Challenges NVIDIA InfiniBand
Specifically, Juniper’s AI data center proposition unites operation-first principles, such as intent-base networking that prioritizes reliability and speed with open, AI-optimized Ethernet networking and AI Juniper Validated Designs (JVDs) which focus on streamlining Ai model deployment and stability. I find that this approach sharpens Juniper’s AI-optimized Ethernet solutions that are aimed at attaining InfiniBand performance without its steep costs. As background, NVIDIA’s 2019 acquisition of Mellanox locked down the last independent supplier of InfiniBand products, giving NVIDIA a commanding position across channels and in driving InifiniBand technological development. For example, Juniper spotlights RoCEv2 can offer 33% lower total cost of ownership (TCO) in relation to NVIDIA InfiniBand implementations.
Fundamentally, I find it refreshing that Juniper is taking a bold stance on why its AI-optimized Ethernet portfolio using RoCEv2 capabilities offers a clear alternative to NVIDIA InfiniBand technology across intensive AI/ML workload environments including especially data centers. The portfolio development and marketing initiative aligns with the Ultra Ethernet Consortium (UEC) mission of delivering an Ethernet-based open, full-communications stack architecture to fulfill the swiftly expanding network demands of AI/ML as well as HPC workloads at scale.
The $14 Billion HPE Deal Dimension
From my view, the AI-Native Networking Platform launch further validates HPE’s decision to acquire Juniper at $14 billion. Juniper, renowned for its AI-native networks, brings expertise and innovation. I expect Juniper’s strength in AI, and its Mist AI and Cloud platform, can appreciably bolster HPE’s capabilities, enabling it to offer more comprehensive and efficient networking solutions. Combining Juniper’s innovative technology, such as AI-Native Networking Platform, with HPE’s existing services is expected to create a new networking competitive force, transforming HPE’s networking business and doubling its size.
Juniper’s new platform aligns with what I see as organizations swiftly expanding their examination of AI hosting models that reinforce emerging AI policies such as built-in risk management and responsible AI as well as protecting all-valuable intellectual property (IP) from public cloud exposure. As such, Juniper AI-Native Networking Platform is lined up to play a starring role in the emerging AI data center model and its integral part in ensuring secure and responsible AI hosting models.
Key Takeaway: Juniper AI-Native Networking Platform Takes AIOps to the Next Level
I believe that Juniper’s AI-Native Networking Platform provides the comprehensive AIOps capabilities key to improving network performance throughout the end user, applications, and network domain continuum by minimizing the potential for network outages and application downtime. By expanding its portfolio’s AIOps and VNA capabilities with integrated digital experience twinning in tandem with new additions to its AI Data Center solutions, Juniper enables organizations to unleash the potential of AI-driven innovation.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Juniper Apstra: Enhancements Power Private Data Center Breakthroughs
HPE’s Game-Changing $14 Billion Acquisition of Juniper
5G Factor: HPE Juniper Deal – The 5G Ecosystem Impact
Author Information
Ron is an experienced, customer-focused research expert and analyst, with over 20 years of experience in the digital and IT transformation markets, working with businesses to drive consistent revenue and sales growth.
He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including a wide range of topics across software and services, infrastructure, 5G communications, Internet of Things (IoT), Artificial Intelligence (AI), analytics, security, cloud computing, revenue management, and regulatory issues.
Prior to his work with The Futurum Group, Ron worked with GlobalData Technology creating syndicated and custom research across a wide variety of technical fields. His work with Current Analysis focused on the broadband and service provider infrastructure markets.
Ron holds a Master of Arts in Public Policy from University of Nevada — Las Vegas and a Bachelor of Arts in political science/government from William and Mary.
