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by trishume 1252 days ago
I agree most HTTP server benchmarks are highly misleading in that way, and mention in my post how disappointed I am at the lack of good benchmarks. I also agree that typical HTTP servers would fall over at much lower new connection loads.

I'm talking about a hypothetical HTTPS server that used optimized kernel-bypass networking. Here's a kernel-bypass HTTP server benchmarked doing 50k new connections per core second while re-using nginx code: https://github.com/F-Stack/f-stack. But I don't know of anyone who's done something similar with HTTPS support.
3 comments
jck 1251 days ago
I once built a quick and dirty load testing tool for a public facing service we built. The tool was pretty simple - something like https://github.com/bojand/ghz but with traffic and data patterns closer to what we expected to see in the real world. We used argo-workflows to generate scale.

One thing which we noticed was that there was a considerable difference in performance characteristics based on how we parallelized the load testing tool (multiple threads, multiple processes, multiple kubernetes pods, pods forced to be distributed across nodes).

I think that when you run non-distrubuted load tests you benefit from bunch of cool things which happen with http2 and Linux (multiplexing, resource sharing etc) which might make applications seem much faster than they would be in the real world.

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lossolo 1252 days ago
TLS handling would dominate your performance, kernel bypassing would not help here unless you would also do TLS NIC offloading, you still need to process new TLS sessions from OP example and they would dominate your http processing time (excluding application business logic processing).
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sayrer 1252 days ago
Userspace networking is pretty common. The chair of the IETF even wrote one: https://github.com/NTAP/quant

"Quant uses the warpcore zero-copy userspace UDP/IP stack, which in addition to running on on top of the standard Socket API has support for the netmap fast packet I/O framework, as well as the Particle and RIOT IoT stacks. Quant hence supports traditional POSIX platforms (Linux, MacOS, FreeBSD, etc.) as well as embedded systems."

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