cPacket Networks introduces new packet delivery and capture platforms, designed to meet the evolving needs of AI-powered network observability and security monitoring, both on-premise and in hybrid cloud environments.
The cVu 32400AG strengthens cPacket's packet delivery offerings by addressing customers' growing requirements for peak performance, analytics and AI-powered network observability.
Mark Grodzinsky, Chief Product and Marketing Officer of cPacket, said, "Our zero-downtime enterprise customers require solutions that are not only powerful and efficient but also cost-effective and easy to manage. With our new packet delivery system, we're delivering on those promises, enabling customers to harness the full potential of their network infrastructure while reducing overhead and unlocking advanced capabilities like 400G."
The cVu 32400AG expands on the AG product line to include 400G support, allowing customers to enable packet brokering at line-rate with high port density in a small footprint. This is the first product in the cPacket portfolio to support 400G, helping to round out cPacket’s portfolio with network observability solutions that are both efficient and future-proof.
The cVu 32400AG offers advanced microburst detection capabilities and allows NetOps teams to detect and address network congestion issues in real-time, ensuring the reliability and performance of mission-critical applications. For instance, applications requiring high performance and low latency, such as high-frequency trading and AI processing, often encounter millisecond bursts that impact immediate operations and are critical considerations for future network capacity planning and AI compute efficiency.
In addition to new releases in the cVu family, cPacket has expanded its partnership with AWS to include the cStor-V platform on AWS Marketplace. The cStor-V virtual appliance runs as a native EC2 instance in AWS to deliver high-performance cloud packet capture and network analytics. It integrates seamlessly with native AWS VPC Traffic Mirroring services to easily point out-of-band, replicated packet streams to cStor-V for continuous and on-demand capture scenarios. cStor-V can also generate enterprise grade network analytics to quickly troubleshoot network issues, identify security incidents, and examine key protocol performance.
The Latest
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 ...
2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...
Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...