26-04-2022 | ipoque | New Technologies
ipoque GmbH, a Rohde & Schwarz company, has launched R&SvPACE, its vector packet processing (VPP)-native deep packet inspection (DPI) engine explicitly designed to meet the IP traffic visibility needs in cloud computing environments. As a cloud-optimised module, it powers virtualised and cloud-native functions such as 5G user plane functions with real-time, deep traffic insights.
It combines traditional DPI techniques such as statistical/heuristical and behavioural analyses with metadata extraction and encrypted traffic intelligence (ETI) to accurately and reliably identify and classify protocols, applications, and services. Advanced ETI techniques comprise machine learning, deep learning, and high-dimensional data analysis. They allow traffic inspection in the cloud to be expanded to encrypted traffic, including using protocols and techniques such as TLS 1.3, TLS 1.3 0-RTT, ESNI, ECH, DoT and DoH. The solution can also handle obfuscated and anonymised traffic, for example, traffic provided via CDNs and VPNs and traffic masked by randomisation and domain fronting.
Constructed on the capabilities and comprehensive features of R&SPACE2, the SPP-based DPI engine by ipoque, it features an extensive, continually updated signature library and well-defined APIs for seamless integration. It also delivers support for first packet classification employing smart caching techniques. With VPP at its core, it pushes DPI processing speeds to the next level with an improved average clocks-per-packet ratio, leading to a speedup of up to three times. It also boasts a memory footprint of fewer than 400bytes per five-tuple connection and 700bytes per network endpoint. Also, it facilitates thread-safe endpoint access across multiple worker cores.
“The shift towards the cloud calls for packet processing technologies capable of delivering the speeds, latency and cost efficiency necessary to support growing traffic volumes and the breadth of applications hosted and delivered from the cloud. The adoption of VPP, which involves vector-based batch processing using a locally-stored vertex memory cache, significantly reduces CPU and energy consumption, allowing our DPI technology to deliver unrivalled performance and scalability in cloud and virtualised environments,” said Dr Martin Mieth, VP Engineering at ipoque.
VNF/CNF vendors deploying the solution benefit from the company's extensive experience and expertise in implementing DPI for various network types. By licensing the OEM DPI engine, vendors can greatly enhance their time-to-market, realise significant capex/opex savings, and futureproof their traffic detection capabilities. They can also capitalise on the continued advancements pioneered by the company in the DPI market while taking advantage of the superior support and service adapted to the customers’ exact needs.
