C10k problem

The C10k problem is the problem of optimising network sockets to handle a large number of clients at the same time.[1] The name C10k is a numeronym for concurrently handling ten thousand connections.[2] Note that concurrent connections are not the same as requests per second, though they are similar: handling many requests per second requires high throughput (processing them quickly), while a high number of concurrent connections requires efficient scheduling of connections. In other words, handling many requests per second is concerned with the speed of handling requests, whereas a system capable of handling a high number of concurrent connections does not necessarily have to be a fast system, only one where each request will deterministically return a response within a (not necessarily fixed) finite amount of time.

The problem of socket server optimisation has been studied because a number of factors must be considered to allow a web server to support many clients. This can involve a combination of operating system constraints and web server software limitations. According to the scope of services to be made available and the capabilities of the operating system as well as hardware considerations such as multi-processing capabilities, a multi-threading model or a single threading model can be preferred. Concurrently with this aspect, which involves considerations regarding memory management (usually operating system related), strategies implied relate to the very diverse aspects of the I/O management.[2]

History

The term was coined in 1999 by Dan Kegel,[3][4] citing the Simtel FTP host, cdrom.com, serving 10,000 clients at once over 1 gigabit per second Ethernet in that year.[1] The term has since been used for the general issue of large number of clients, with similar numeronyms for larger number of connections, most recently "C10M" in the 2010s.[5]

By the early 2010s millions of connections on a single commodity 1U server became possible: over 2 million connections (WhatsApp, 24 cores, using Erlang on FreeBSD),[6][7] 10–12 million connections (MigratoryData, 12 cores, using Java on Linux).[5][8]

Common applications of very high number of connections include pub/sub servers, chat, file servers, web servers, and software-defined networking.

gollark: I guess you could have language "devices" not map exactly to real ones.
gollark: Also, I think it should be designed to still work with just one machine connected, so the honeycomb thing is maybe not ideal.
gollark: I don't like the idea of specific worker bees, I think they should all be programmable with simple code somehow.
gollark: <@331320482047721472> HelloBoi
gollark: Maybe give each bee (?) a simple limited stack or TIS-100-style language to define tasks.

See also

References
  1. "The C10K problem". Archived from the original on 2013-07-18.
  2. Liu, D.; Deters, R. (2009). "The Reverse C10K Problem for Server-Side Mashups". Service-Oriented Computing – ICSOC 2008 Workshops. Lecture Notes in Computer Science. 5472. p. 166. doi:10.1007/978-3-642-01247-1_16. ISBN 978-3-642-01246-4.
  3. Andrew Alexeev (2012). "§14. nginx; §14.1. Why Is High Concurrency Important?". In Amy Brown; Greg Wilson (eds.). The Architecture of Open Source Applications, Volume II: Structure, Scale and a Few More Fearless Hacks. Lulu.com. ISBN 9781105571817. Around ten years ago, Daniel Kegel, a prominent software engineer, … Kegel's C10K manifest … solving the C10K problem of 10,000 simultaneous connections, nginx …
  4. Kegel, Dan (8 May 1999). "The C10K problem". Kegel com. Archived from the original (html) on 8 May 1999. Retrieved 18 June 2019. And computers are big, too. You can buy a 500MHz machine with 1 gigabyte of RAM and six 100Mbit/sec Ethernet card for $3000 or so. Let's see - at 10000 clients, that's 50KHz, 100Kbytes, and 60Kbits/sec per client. It shouldn't take any more horsepower than that to take four kilobytes from the disk and send them to the network once a second for each of ten thousand clients. (That works out to $0.30 per client, by the way. Those $100/client licensing fees some operating systems charge are starting to look a little heavy!) So hardware is no longer the bottleneck.
  5. How MigratoryData solved the C10M problem: 10 Million Concurrent Connections on a Single Commodity Server
  6. "1 million is so 2011". WhatsApp blog. 6 January 2012. Archived from the original (html) on 1 May 2014. Retrieved 25 July 2019. This time we also wanted to share some more technical details with you about hardware, OS and software: hw.machine: amd64 hw.model: Intel(R) Xeon(R) CPU X5675 @ 3.07GHz hw.ncpu: 24 hw.physmem: 103062118400 hw.usermem: 100556451840
  7. Reed, Rick (30 March 2012). "Scaling to Millions of Simultaneous Connections" (PDF). Erlang Factory. p. 7. Archived from the original (pdf) on 9 July 2012. Retrieved 25 July 2019.
  8. Scaling to 12 Million Concurrent Connections: How MigratoryData Did It
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