
cPacket Networks announced a new addition to its cStor series packet capture appliances in support of the latest data center consolidation, 100Gbps migration, and cyber security requirements.
The new cStor 100 appliance raises the bar for the industry by setting the new standard for capturing, storing, and analyzing the network packet data at up to 100Gbps speed with advanced analytics. The cStor family already supports capture at 40, 25, 15, and 10Gbps as well as a virtual/cloud version up to 10Gbps.
“Many of our existing customers are consolidating their data centers as they move a part of their workloads into the cloud. They want to upgrade their data center infrastructure to 100Gbps to meet current and future business requirements. cPacket’s being early to 100Gbps observability helps our customers go through this change uneventfully.” said Brendan O’Flaherty, CEO of cPacket Networks.
Network speeds have been steadily increasing driven by high-performance workloads. Digital transformation and remote work due to Covid-19 have only accelerated these trends. The new cStor 100 appliance provides organizations with the deep, comprehensive, and actionable insights they need to align with the industry trends around digital transformation, cloud migration, and remote work.
“While most of the industry is still hovering around or below 40Gbps capture rates, you can find a few products that claim higher performance. What is really lacking is a well-rounded solution that can capture at 100Gbps speed while delivering impactful analytics and supporting simultaneous data search,” said Nadeem Zahid, VP of Product Management at cPacket Networks. “You can fill the storage really fast and accumulate lots of data at 100Gbps. Finding the right packets fast in the case of root-cause analysis or a security breach makes a lot of difference for a business.”
The cStor 100 appliance provides 100Gbps burst with sustained 60Gbps capture-to-disk throughput along with 288TB of on-board storage (extensible up to 2PB) so organizations can capture, store, replay, and analyze high speed network traffic as the ultimate source of truth for troubleshooting issues, security forensics, incident response, and compliance – as packets do not lie.
- Built for high-performance, low-latency networks, and intensive workloads. The cStor 100 appliance provides flow analytics, TCP stateful analysis, RTP analysis, VPN analysis, market data gap detection, one-way latency, and other value-added analytics at high-speeds for mission-critical environments and network operation centers.
- Effective incident response through Network Detection and Response The cStor 100 appliance is an effective security forensics tool for providing before, during, and after packet data in correlation with security incidents. By integrating with threat detection and mitigation solutions such as Vectra, Corelight, Palo Alto Networks, and Fortinet, the cStor 100 appliance extends the life, effectiveness, and return-on-investment for the security tools.
- Added security and privacy with Self-Encrypting Drives. Separate versions of the cStor 100 appliance with self-encrypting drives (SED) are available to meet additional security and privacy requirements for the public, government, financial, healthcare, and other sensitive deployments.
All new products are now available from cPacket directly or its channel partners.
The Latest
AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...
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 ...