Juniper Networks announced its strong momentum and industry recognition in the data centre networking market. Juniper’s data centre networking innovation continues, with new capabilities announced that dramatically improve performance and economics for customers in the AI era.
“Juniper believes that our position in the latest Gartner reports underlines the strength of our core data center value proposition, which includes simplified AI-native operations, openness that avoids vendor lock-in, industry-leading performance and unparalleled reliability – all driving exceptional customer experiences,” said Praveen Jain, Senior Vice President & General Manager, Data Center & AI, Juniper Networks. “Our data center team is firing on all cylinders with innovation and execution that supports the business needs of a diverse range of enterprise, AI and cloud provider customers globally. .”
A leader in 2025 Gartner Magic Quadrant for data centre switching
This new report looks at the data center networking industry through a modern lens, including capabilities for handling new AI workloads. Gartner evaluates vendors based on capabilities such as fabric management, ease of administration, platform integration, among others. The Critical Capabilities for Data Center Switching report is a companion to the Magic Quadrant that evaluates and ranks vendors’ solutions based on overall features, technologies and capabilities. In this report, Juniper scored the highest in Enterprise Data Center Network Build-Out, second highest in AI Ethernet Fabric Build-Out, and second highest in SONiC-Based Data Center Network Build-out Use Cases.
Top spot in 800GbE OEM switching market in 2024
*According to 650 Group’s 2024 revenue shipment report published in March 2025, Juniper now commands a leading 44 percent share of the 800GbE OEM switch market, a critical enabler of the AI data center infrastructure. 800GbE is foundational to AI training, inference and storage clusters plus other high-performance computing (HPC) environments. Juniper was the first to ship 800GbE routing and switching platforms showing exceptional innovation and agility.
Disrupting networking for AI with data centre innovations
Juniper’s data center solution, which is a key part of the company’s Mist AI-Native networking platform, continues to stand out on various fronts including ease of operations, performance, reliability and openness. This includes unique AIOps features for enhanced insights into application behaviors, multivendor intent-based networking for simplified fabric management, and an AI assistant, Marvis, that proactively identifies issues with recommended actions for resolution.
Juniper continues to introduce performance and power optimization capabilities specifically for AI workloads to reduce job completion times, decrease power consumption and increase ROI. For example, Juniper introduced innovative AI Load Balancing (AI-LB) techniques like Dynamic Load Balancing (DLB) and Global Load Balancing (GLB) to address the evolving networking needs of AI workloads. Juniper continues to innovate in this area with the introduction of RDMA-aware Load Balancing (RLB), which improves Ethernet network performance even further by uniquely pinning RDMA flows to deterministic paths to predictably load balance traffic across the network. By dramatically minimizing congestion, consistently achieving near theoretical maximum performance and delivering in-order packets, this eliminates the need for specialized SmartNICs and expensive scheduled fabric architectures.
Juniper also recently released LPO (Linear Pluggable Optics) for the Juniper Networks QFX Series platforms that reduce optics power consumption by as much as 50 percent, enabling greater GPU scale and ROI. Juniper’s investments in Co-Packaged Optics (CPO) will further increase bandwidth density and reduce power consumption in data centers, especially for critical applications like AI and HPC.
“The cost and scale of our AI services is governed by the performance and efficiency of our AI infrastructure. Juniper’s AI-LB (AI Load Balancing) solution is the right technology to get the greatest AI network fabric throughput and thereby get maximum GPU utilisation and performance from the AI infrastructure,” said Daniele Cesarini, Head of AI/HPC Architecture, CINECA.
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