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What is a CRPA (Controlled Reception Pattern Antenna)?

What is LEO (Low Earth Orbit)?

The Telco “Quantum Readiness” Gameplan: Is Quantum About to Have its AI Moment?

The Future of Gaming: Eliminating Lag with Edge Computing

Rethinking the Lab – An Evolution: Case Studies in Lab Automation Success

Expand Wi-Fi Device Testing, Automate Manual Effort with Octobox STA Software

Decoding 3GPP’s First Official 6G Workshop

Embracing Failure: Why CNF Resiliency is the Backbone of Reliable 5G Networks

Controlled Reception Pattern Antennas: The next frontier in GNSS resilience?

What it Takes to Test and Assure Telco AI Infrastructure

Reduce Enterprise Risk with Operational Network Resilience Testing 

Three Prerequisites for Rethinking Your Test Strategy

The Enduring Importance of Pentesting 

OFC 2025 Shows Off Solutions to Meet AI Challenges

Continuous Improvement with Spirent

Ensuring Network Security Efficacy Against DDoS Attacks

Holistic Visibility, Automated Testing: VisionWorks Helps Service Providers Meet Diverse Business Challenges 

Managing Key Aspects of Technical Debt by Rethinking Validation

How Test and Assurance Empower Telecom’s Sovereign AI Success 

Unlocking the Value of 5G Fixed Wireless Access: The Key to Quality and Testing

Spirent testing strategy for-financial enterprises

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Automation Strategies to Avoid Finance’s Next Major Meltdown

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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

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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

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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