We implemented an algorithm that should work well with gRPC and existing HTTP servers, but we wanted to make sure we have an escape path in case something goes wrong. However, since HTTP/2 PING frames are used to determine the round-trip time of the HTTP/2 connection, we had to be very careful to avoid triggering the server’s PING flood protection mechanisms.
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This turned out to work well, lifting download speeds close to their theoretical maximum. None of these seemed to be satisfactory, so we decided to implement an automatic window sizing algorithm similar to the one in TCP or QUIC ( dotnet/runtime#54755). We considered “cheap” options to solve this, such as defining a large fixed-size window – which could result in unnecessarily high memory footprint -, or to ask the user to manually configure the receive window based on empirical observations. The root cause of the issue turned out to be the fixed-size HTTP/2 receive window, with it’s 64KB size being too small to keep the network busy when WINDOW_UPDATE frames are received with a high delay, meaning that HTTP/2’s own flow control mechanism was stalling the network link. Amongst other things, this was heavily impacting gRPC streaming scenarios. To give an example: in one of our benchmarks curl was able to reach the maximum 10 Mbit/s rate of a specific cross-atlantic link, while SocketsHttpHandler speed topped at 2.5 Mbit/s. On links with a high bandwidth-delay product, some users reported 5x-10x differences compared to other implementations which were able to utilize the link’s physical bandwidth. With the emerging popularity of HTTP/2 and gRPC, our customers discovered that SocketsHttpHandler‘s HTTP/2 download speed wasn’t on par with other implementations when connected to geographically distant servers with significant network delay. In this post, I am pleased to talk about the changes in. NET we like to publish a blog post highlighting some of the changes and improvements for networking.