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Blog - The GPS Week Number Rollover problem

What is Galileo? An Introduction to Europe's Answer to GPS

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Guy Buesnel

gnss gps hero

Blog - Staying ahead with the latest ICDs

Blog - BeiDou Phase-3 signals are now supported on Spirent’s GNSS RF Constellation Simulators

Blog - Commercial CubeSat missions: why GNSS testing with a simulator is essential

Rahul Gupta

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Mia Swain

CPhys, FRIN,  Product Manager – GNSS Vulnerabilities 

Blog - What’s the Difference Between GNSS and GPS?

Will Thornton

VP and Client Partner Executive for AT&T

Tobin Krueger

What is Galileo

Space Science Technologist

Talini Pinto Jayawardena

GNSS与GPS有何区别？

Commercial CubeSat missions: why GNSS testing with a simulator is essential

Breaching the Sensitive Security Discussion At AT&T Business Summit

BeiDou Phase-3 signals are now supported on Spirent’s GNSS RF Constellation Simulators

Staying ahead with the latest ICDs

The GPS Week Number Rollover problem

How to Ensure Your GNSS-Reliant Device Complies with ETSI EN 303 413

What is Galileo? An Introduction to Europe’s Answer to GPS

How To Use GNSS Simulators To Test RTK Positioning Systems

How Leap Seconds Can Interfere with GNSS Receivers

Spirent testing strategy for-financial enterprises

Grid lines

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Look-Before-You-Leap-blog-hero-1240x600

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Aniket Khosla profile

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Automation Strategies to Avoid Finance’s Next Major Meltdown

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Stephen Douglas

思博伦5G战略总监

VP, Wireline Product Management

Aniket Khosla 

我们正处于几十年来高速以太网（HSE）最令人兴奋且影响最为深远的时期之一。新的年度影响力报告分享了塑造数据中心网络和高速以太网市场的最新趋势、需求和发展。

报告：追踪转型中的AI驱动高速以太网市场

Telecom is eager to explore every aspect of AI-powered innovation and transformation. Stakeholders are seeking a competitive edge, new revenues, more efficient network operations, and reduced costs.

Status check on how AI is powering network testing and assurance. Learn about testing’s role across the AI lifecycle, and the path appearing toward AI autonomous networking. 

How AI Is Powering Network Testing and Assurance

Status Check: The Latest on How AI Is Powering Network Testing and Assurance

AI and automation are already reducing RAN energy consumption and providing partial autonomy for network operations. Even bigger impacts are on the horizon.

Early Telecom AI Progress Points to Real Results 

Early Telecom AI Progress Points to Real Performance Results 

The rapid evolving growth of AI is impacting hyperscaler data centers, as high volumes of traffic and intensive processing requirements push the limits of current networks. Data center architectures and the high-speed networks they rely on must be reevaluated, along with their testing strategies, to ensure reliable performance now and into the future.

The rapid growth of AI is impacting data center architectures and the high-speed networks they rely on They must be reevaluated, along with the testing strategies to ensure reliable performance into the future.

The Challenge of Evolving AI Workloads in Data Centers 

Large enterprises face challenges related to complexity, cost, productivity, and regulatory compliance. Many recognize the critical need to modernize their test labs to automate manual processes, incorporate historical analysis, and facilitate regression testing. The latest transformation strategies provide opportunities to streamline operations, reducing lab testing timelines from months to hours

Large enterprises face challenges related to complexity, cost, productivity, and regulatory compliance.

How Modern Test Labs Cut Cost and Complexity

Grid Lines

AI is transforming data centers, driving demand for high-speed Ethernet and scalable infrastructure. This blog explores how operators are adopting 800G Ethernet and sustainable practices to meet AI’s intensive requirements. Learn why efficiency and resource optimization are essential for monetizing AI infrastructure investments.

AI is transforming data centers, driving demand for high-speed Ethernet and scalable infrastructure. This blog explores how operators are adopting 800G Ethernet and sustainable practices to meet AI’s intensive requirements. 

AI Data Center Testing Emerges as Top Priority

Look Before You Leap: AI Data Center Testing Emerges as Top Priority

Financial institutions rely on their digital infrastructure for conducting financial transactions and providing services to their customers; it's important to ensure their networks are secure, reliable, and perform as planned to their specific needs.

Validating Network Security and Performance for Financial Institutions

Financial enterprises are pushed to test more complex systems, faster than ever, while facing multiple regulatory compliance requirements that must be fulfilled multiple times per year. For many, their current state of testing simply can’t keep up. To address these challenges, a test lab modernization and automation strategy is key to addressing objectives and requirements in the financial sector.

A test lab modernization and automation strategy is key to addressing complex objectives and requirements in the financial sector.

Test Lab Modernization Trends for Financial Enterprises

In the dynamic realm of data centers, AI is setting new benchmarks. A discussion with Aniket Khosla, VP of Wireline Product Management at Spirent, highlighted how AI is revolutionizing data center networking.

AI’s Transformative Impact on Data Center Networking

Innovative testing approaches in preparation for the AI revolution

The growing number of regulatory compliance requirements mandate BFSI institutions conduct annual – some biannual – operational resilience testing to ensure ICT systems can withstand cyberattacks and disruptions. Traditional manual testing can’t do the job anymore.

The growing number of regulatory compliance requirements mandate BFSI institutions conduct annual – some biannual – operational resilience testing to ensure ICT systems can withstand cyberattacks and disruptions. 

Automation Strategies to Avoid Finance’s Major Meltdown

Test, assurance, and automation thought leadership from our in-house experts.

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