Finance Probe

High-rate network monitoring probe designed specifically to provide data analytics and microburst detection across the global exchange market.

Investing in the Future...

Prepare for ever-increasing data rates by investing in next-generation monitoring infrastructure. Finance Probe provides unsampled, line-rate monitoring of all traffic traversing your network at up to 400Gbps.



Flow analytics and Microburst Detection can be used to measure link capacity and overall network performance, minimising the risk of latency & packet loss, and ensuring high-quality service fulfilment continues to be met.





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1ms Microburst Detection

Standard network monitoring solutions track traffic rate in minute or second intervals. Microburst activity will typically last between 1-100 milliseconds, meaning they can remain undetected in higher granularity solutions.

Finance Probe provides millisecond resolution traffic monitoring at line-rate, enabling the detection of microburst activity in real-time across your entire network. While competitors can provide 10ms microburst detection, we can identify peaks within just 1ms.


Microbursts will be identified and alerted to the user; alerts will contain a nanosecond timestamp (utilising PTP time sourcing), severity score, and flow analytics from the millisecond(s) period of detection.


Implement user-defined microburst thresholds; configure and fine-tune thresholds by the number of packets or gigabits-per-second monitored per 1 millisecond interval.

Increase Capacity & Reduce Latency

When network infrastructure becomes overwhelmed and cannot process the amount of data it is receiving, latency and packet loss can occur. A millisecond difference in the success of a trading instruction can be worth millions to both the exchange and its customers.


Finance Probe boasts 4 x 100GbE to help organisations increase their network capacity without being concerned about their monitoring capability. Increase root cause analysis accuracy by correlating microburst and packet loss events using nano-second timestamping.


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