Keysight Technologies Introduces AresONE 1600GE Platform to Validate Next-Generation AI Data Center Fabrics
Keysight Technologies has unveiled a powerful new solution designed to help the technology industry prepare for the next wave of artificial intelligence infrastructure. The company announced the launch of the AresONE 1600GE, a scalable 1.6-terabit Ethernet AI workload emulation platform developed to validate next-generation AI fabrics built on emerging 224G SerDes electrical lanes.
The new system is designed to support network equipment manufacturers, semiconductor companies, hyperscale cloud providers, and AI data center operators as they build and test increasingly complex networking systems required to support advanced artificial intelligence workloads.
As AI models continue to grow in size and complexity, the networking infrastructure connecting GPUs, accelerators, and storage systems must evolve at an equally rapid pace. Keysight’s new platform aims to address this challenge by providing a realistic, large-scale testing environment that enables organizations to validate network fabrics before and after deployment.
Rising Demands of AI Networking
The explosive growth of artificial intelligence is driving dramatic changes across the data center ecosystem. Training large AI models requires massive clusters of GPUs and specialized accelerators that must communicate with each other at extremely high speeds.
In modern AI environments, thousands of compute nodes exchange large volumes of data simultaneously while executing distributed training tasks. The efficiency of these workloads depends heavily on the performance and reliability of the network fabric connecting the compute infrastructure.
To support these demands, the industry is rapidly transitioning toward higher-capacity Ethernet technologies such as 800-gigabit and 1.6-terabit networking. These high-speed links allow data centers to move larger datasets between compute resources while minimizing latency and congestion.
However, validating these high-speed networks before deployment is becoming increasingly complex. Engineers must ensure that hardware components, protocols, and application workloads interact seamlessly under real-world conditions.
Keysight’s AresONE 1600GE platform was created specifically to address this challenge by enabling large-scale emulation of AI workloads in controlled testing environments.
Transition to 224G SerDes and 1.6T Ethernet
One of the most important technological shifts currently underway in data center networking is the adoption of 224-gigabit serializer/deserializer (SerDes) electrical lanes. These ultra-high-speed signaling technologies enable the next generation of Ethernet standards, including 1.6T Ethernet connections.
The shift to higher data rates allows network designers to increase switch radix—the number of ports available on a network switch—by supporting flexible port configurations such as 800GE and 1600GE through fan-out architectures.
By increasing switch radix, data center architects can reduce the number of network tiers required in AI clusters. This leads to more efficient fabrics with lower latency, improved throughput, and simplified infrastructure designs.
However, transitioning to these new technologies introduces several technical challenges. Engineers must verify link stability across high-speed electrical lanes, analyze congestion patterns during traffic bursts, and evaluate how network protocols behave when processing large-scale AI workloads.
These tasks require sophisticated testing tools capable of replicating real AI compute workloads at extremely high speeds—something traditional network testing equipment may struggle to achieve.
AI Workload Emulation with Data Center Builder
To support realistic AI testing scenarios, the AresONE 1600GE platform integrates with the Keysight AI Data Center Builder, also known as KAI DC Builder.
This advanced software environment allows engineers to simulate real AI workloads running across large GPU clusters. By reproducing production-level data center conditions in the lab, the platform enables engineers to analyze network performance before deploying infrastructure in operational environments.
The AI Data Center Builder software supports a wide range of workload patterns commonly used in modern AI frameworks. This includes multiple full-stack RoCEv2 connections and collective communication patterns such as all-reduce, broadcast, and gather operations.
These communication patterns are critical for distributed AI training, where multiple compute nodes must coordinate and exchange large datasets while performing synchronized computations.
By emulating these interactions accurately, engineers can measure network performance indicators under conditions that closely resemble real data center operations.
Addressing AI Fabric Validation Challenges
Validating next-generation AI networks involves far more than simply verifying link connectivity. Engineers must evaluate a variety of performance metrics that determine whether a fabric can support large-scale AI workloads efficiently.
The AresONE 1600GE platform provides tools to evaluate network congestion behavior, latency, packet loss, and load balancing across distributed systems. It can also measure the impact of network performance on job completion times for AI training tasks.
One particularly important challenge in AI networking is managing microburst traffic events—sudden spikes in data transmission that can overwhelm network buffers and degrade performance. By simulating these traffic patterns, engineers can analyze how network hardware and congestion control mechanisms respond under stress.
The ability to reproduce these scenarios in a testing environment allows developers to identify potential bottlenecks and optimize network configurations before systems are deployed in production.
High-Density Hardware Architecture
The AresONE 1600GE platform features a high-density hardware architecture designed for modern data center environments. The rack-mount system includes four OSFP 1600 ports capable of supporting multiple flexible fan-out configurations.
These configurations allow engineers to simulate a wide range of network topologies using a single platform. The system supports configurations including:
- One 1600GE connection
- Two 800GE connections
- Four 400GE connections
- Eight 200GE connections
All of these configurations operate over 224G SerDes electrical lanes, enabling engineers to test link performance and traffic behavior across various network architectures.
This flexibility allows network designers to validate both individual links and large-scale traffic scenarios using the same testing infrastructure.
Full-Stack Network Validation
Another key advantage of the AresONE 1600GE platform is its ability to perform full-stack validation across multiple layers of the networking stack.
The system supports physical layer validation, allowing engineers to analyze optical and electrical link performance, forward error correction behavior, and signal integrity across high-speed connections.
Beyond the physical layer, the platform also enables detailed analysis of Layer 2 and Layer 3 protocols, traffic patterns, and control plane behavior.
By correlating data from multiple layers of the network stack, engineers gain deeper visibility into how physical hardware performance influences protocol behavior and application outcomes.
This holistic testing approach allows organizations to identify and resolve issues earlier in the development cycle, improving reliability and reducing deployment risks.
Scalable System Design for Data Centers
The AresONE 1600GE platform was designed with scalability and reliability in mind. The system incorporates high-performance processing capabilities and large memory resources to support automated and repeatable testing procedures.
These features allow engineering teams to run complex validation tests repeatedly across development cycles, ensuring consistent results as network hardware and software evolve.
The system’s architecture also allows it to integrate seamlessly into both laboratory environments and operational data centers. This flexibility ensures that organizations can use the same testing infrastructure throughout product development, validation, and deployment stages.
Integration with Network Testing Platforms
The platform also integrates with Keysight IxNetwork, enabling engineers to emulate large-scale Layer 2 and Layer 3 network protocols at full lane speeds.
Through this integration, engineering teams gain enhanced visibility into network behavior, allowing them to identify performance issues earlier in the development process.
The combination of hardware validation, AI workload emulation, and protocol testing within a single platform simplifies the testing workflow and accelerates product readiness.
Industry Outlook for AI Networking
Industry analysts expect the market for AI interconnect technologies to expand rapidly over the next decade. According to Alan Weckel, founder and technology analyst at 650 Group, the AI networking market is evolving quickly as the industry shifts from foundational model training to inference-focused and agent-driven AI systems.
He noted that the global market for AI interconnect networks—including scale-up, scale-out, scale-across, and front-end networking—could approach $200 billion by 2030. Much of this growth will be driven by widespread adoption of 800G and 1.6T Ethernet technologies.
The transition to 1.6T networking is expected to represent one of the fastest and largest technology cycles the networking industry has experienced.
Tools such as the AresONE 1600GE platform will play a critical role in helping companies prepare for this transition by enabling comprehensive validation of high-speed networking infrastructure.
Supporting the Future of AI Infrastructure
According to Ram Periakaruppan, vice president and general manager of network test and security solutions at Keysight, the rapid expansion of AI workloads is pushing data center technologies to new levels of complexity and performance.
He explained that hyperscalers and other organizations building AI infrastructure need reliable tools that allow them to validate networking systems under real-world conditions before deploying them at scale.
The AresONE 1600GE platform provides a practical and proven solution for evaluating next-generation network devices and infrastructure. By enabling comprehensive validation in controlled environments, the system helps organizations reduce deployment risks and accelerate the rollout of advanced AI networking technologies.
Preparing for the Next Generation of AI Data Centers
As artificial intelligence continues to reshape industries around the world, the data center infrastructure supporting these technologies must evolve rapidly to keep pace.
Networking technologies such as 1.6T Ethernet and 224G SerDes are expected to become foundational components of future AI clusters. However, successfully deploying these technologies requires rigorous testing and validation.
With the introduction of the AresONE 1600GE platform, Keysight is providing the industry with a powerful new tool for validating the next generation of AI networking infrastructure.
By combining high-density hardware, advanced workload emulation, and full-stack network validation capabilities, the platform enables engineers to test AI fabrics at unprecedented scale—helping accelerate the development of faster, more reliable AI data centers for the future.
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