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cPacket Unveils High-Performance Packet Delivery

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

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...

cPacket Unveils High-Performance Packet Delivery

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

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...