Surgical Packet Capture Pinpoints Exact Source of Problems, Saving IT Organizations Massive Amounts of Time, Effort, and Cost
SEATTLE, WA — November 8, 2012 — ExtraHop Networks, the leading provider of network-based application performance management (APM) solutions, today announced a new policy-based, precision packet-capture method that renders traditional packet-capture methods obsolete. With the new solution, IT operations teams can identify root causes of errors and suspicious activity much faster with a concise and relevant packet capture of the exact offending application flow, while avoiding the storage requirements, complex identification, and high costs that characterize legacy packet capture techniques.
"Packet capture is a tried-and-true method of analyzing the root cause of network and application issues," said Will Cappelli, Gartner Research Vice President. "However, traditional packet-capture tools are simply too cumbersome and expensive to handle the growing volume and speed of data center networks. For packet capture to remain a viable solution for IT operations, performance monitoring vendors need to enable a new, different approach that is more precise and intelligent."
Although traditional packet capture products that store multiple terabytes of data are sometimes required for compliance, this legacy approach should not be used for diagnostics for the following reasons:
- Burdensome guesswork and wait-and-see delays. Legacy packet captures rely on educated guesses of where to look. IT teams often must wait for the problem to occur again before they can capture the packets needed to pinpoint the problem.
- Excessive storage demands. The alternative is to constantly store all packets, and at rates such as 10Gbps, this approach will fill more than 100TB of storage in one day—an extremely expensive proposition.
- Inefficient and personnel-intensive analysis. If the correct traffic can be captured, skilled network engineers must spend hours if not days digging through gigabytes of data to find the problem.
- Passive, real-time approach. The ExtraHop system passively processes application and network traffic in real-time, performing full-stream reassembly for millions of flows.
- Customizable for every environment with AI Triggers. Using Application Inspection Triggers (AI Triggers) technology, IT teams can set a policy for anomalous or suspicious events they would like to capture.
- Surgical precision for accurate analysis. When an event such as an application error, a malformed request, or suspicious file access occurs, ExtraHop automatically records the packets for the application and network flow that preceded and caused that event.
- Instant replay to save money and time. For the first time, IT operations teams have an exact replay of what caused a particular error or slowdown immediately after an event, saving considerable money and time.
To learn more about ExtraHop's new policy-based precision packet capture technology, please visit http://www.extrahop.com/products/features/packet-capture.
About ExtraHop Networks
ExtraHop Networks is the leading provider of network-based application performance management (APM) solutions. The ExtraHop Application Delivery Assurance system performs the fastest and deepest analysis in the industry, achieving real-time transaction monitoring at speeds up to a sustained 10Gbps in a single appliance and application-level visibility with no agents, configuration, or overhead. The ExtraHop system quickly auto-discovers and auto-classifies applications and devices, delivering immediate value out of the box. ExtraHop Networks provides award-winning solutions to companies across a wide range of industries, including ecommerce, communications, and financial services. The privately held company was founded in 2007 by Jesse Rothstein and Raja Mukerji, engineering veterans from F5 Networks and architects of the BIG-IP v9 product. Follow us on Twitter @ExtraHop. For more information, visit www.extrahop.com.
Press Contacts
Rachel Pepple
ExtraHop Networks
206-453-2290
pr@extrahop.com