
Ixia has achieved the Federal Information Processing Standard (FIPS) Publication 140-2 accreditation for its industry leading Vision ONE and Vision 7300 network packet brokers (NPB) solutions.
This accreditation signifies that these Ixia products meet the stringent security requirements of all US government agencies.
The FIPS PUB 140-2 covers security requirements in 11 areas related to the design and implementation of a cryptographic module. This standard specifies the security requirements that will be satisfied by a cryptographic module utilized within a security system protecting sensitive but unclassified information.
“Ixia works diligently to ensure that our products meet the stringent security requirements of federal agencies, while meeting the dynamic needs of our customers and partners, “stated Recep Ozdag, VP of Product Management at Ixia. “This accreditation serves as a meaningful demonstration of Ixia’s ongoing commitment to the network visibility and federal markets.”
The following Ixia Network Visibility Solutions have received FIPS accreditation:
- Ixia’s Vision ONE network packet broker enables organizations to maintain security as well as identify and resolve performance problems across physical and virtual infrastructures from a single platform. Whether fighting against threats hidden in encrypted traffic, or feeding the right data to the right forensic solution, Vision ONE boosts network protection without negatively impacting performance.
- Ixia’s Vision 7300, enables centralized control of a network monitoring system in a single, simple, rack-mountable unit. It combines disparate solutions into a smaller data center footprint, saving power and rack space while improving return on investment. This unprecedented visibility protects tool investments and scales with the network as monitoring needs grow, new applications debut, and security threats emerge.
The Latest
While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...
Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...
As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...
Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...
AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...
Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...
A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...
IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...
A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...
According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...