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Keysight AI Data Center Test Platform Introduced

Keysight Technologies introduced the Keysight AI Data Center Test Platform, designed to accelerate innovation in AI / ML network validation and optimization.

The solution significantly improves benchmarking of new AI infrastructures with unprecedented scale and efficiency.

To overcome this challenge and accelerate the design and testing of AI / ML infrastructure, the Keysight AI Data Center Test Platform delivers highly tunable AI workload emulation, pre-packaged benchmarking apps, and dataset analysis tools to significantly improve performance of the AI / ML cluster network fabric.

To accelerate AI / ML network design, Keysight’s solution for data centers:

- Emulates high-scale AI workloads with measurable fidelity – Offers deep insights into collective communication performance

- Simplifies the benchmarking process – Provides validation of AI network fabric with pre-packaged benchmark applications, built through partnerships with the largest AI operators and AI infrastructure vendors

- Executes defined AI / ML behavioral models – Enables sharing between users and customers to help reproduce experiments

- Offers a choice of test engines – Choose between AI workload emulation on Keysight hardware load appliances and software endpoints or real AI accelerators to compare benchmarking results

The Keysight platform enables large scale validation and experimentation with fabric design in a realistic and cost-effective way. This solution complements testing AI / ML workloads using GPUs, providing AI operators with a more scalable, robust, and integrated AI test platform.

Ram Periakaruppan, VP and GM, Network Test & Security Solutions, Keysight, said: “As a leader in testing ultra-high-speed 800G Ethernet networks, Keysight continues to lead the way in innovation, having formed close partnerships with hyperscalers to co-design this groundbreaking new AI test platform that realistically benchmarks and emulates high-scale AI workloads unlike other test tools available today.”

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Keysight AI Data Center Test Platform Introduced

Keysight Technologies introduced the Keysight AI Data Center Test Platform, designed to accelerate innovation in AI / ML network validation and optimization.

The solution significantly improves benchmarking of new AI infrastructures with unprecedented scale and efficiency.

To overcome this challenge and accelerate the design and testing of AI / ML infrastructure, the Keysight AI Data Center Test Platform delivers highly tunable AI workload emulation, pre-packaged benchmarking apps, and dataset analysis tools to significantly improve performance of the AI / ML cluster network fabric.

To accelerate AI / ML network design, Keysight’s solution for data centers:

- Emulates high-scale AI workloads with measurable fidelity – Offers deep insights into collective communication performance

- Simplifies the benchmarking process – Provides validation of AI network fabric with pre-packaged benchmark applications, built through partnerships with the largest AI operators and AI infrastructure vendors

- Executes defined AI / ML behavioral models – Enables sharing between users and customers to help reproduce experiments

- Offers a choice of test engines – Choose between AI workload emulation on Keysight hardware load appliances and software endpoints or real AI accelerators to compare benchmarking results

The Keysight platform enables large scale validation and experimentation with fabric design in a realistic and cost-effective way. This solution complements testing AI / ML workloads using GPUs, providing AI operators with a more scalable, robust, and integrated AI test platform.

Ram Periakaruppan, VP and GM, Network Test & Security Solutions, Keysight, said: “As a leader in testing ultra-high-speed 800G Ethernet networks, Keysight continues to lead the way in innovation, having formed close partnerships with hyperscalers to co-design this groundbreaking new AI test platform that realistically benchmarks and emulates high-scale AI workloads unlike other test tools available today.”

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...