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The C10K problem

It's time for web servers to handle ten thousand clients simultaneously, don't you think? After all, the web is a big place now.

And computers are big, too. You can buy a 1000MHz machine with 2 gigabytes of RAM and an 1000Mbit/sec Ethernet card for $1200 or so. Let's see - at 20000 clients, that's 50KHz, 100Kbytes, and 50Kbits/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 twenty thousand clients. (That works out to $0.08 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.

In 1999 one of the busiest ftp sites,, actually handled 10000 clients simultaneously through a Gigabit Ethernet pipe. As of 2001, that same speed is now being offered by several ISPs, who expect it to become increasingly popular with large business customers.

And the thin client model of computing appears to be coming back in style -- this time with the server out on the Internet, serving thousands of clients.

With that in mind, here are a few notes on how to configure operating systems and write code to support thousands of clients. The discussion centers around Unix-like operating systems, for obvious reasons.


In October 2003, Felix von Leitner put together an excellent web page and presentation about network scalability, complete with benchmarks comparing various networking system calls and operating systems. One of his observations is that the 2.6 Linux kernel really does beat the 2.4 kernel, but there are many, many good graphs that will give the OS developers food for thought for some time. (See also the Slashdot comments; it'll be interesting to see whether anyone does followup benchmarks improving on Felix's results.)

If you haven't read it already, go out and get a copy of Unix Network Programming : Networking Apis: Sockets and Xti (Volume 1) by the late W. Richard Stevens. It describes many of the I/O strategies and pitfalls related to writing high-performance servers. It even talks about the 'thundering herd' problem. And while you're at it, go read Jeff Darcy's notes on high-performance server design.

Prepackaged libraries are available that abstract some of the techniques presented below, insulating your code from the operating system and making it more portable.

Designers of networking software have many options. Here are a few:

The following five combinations seem to be popular:

  1. Serve many clients with each thread, and use nonblocking I/O and **level-triggered** readiness notification
  2. Serve many clients with each thread, and use nonblocking I/O and readiness **change** notification
  3. Serve many clients with each server thread, and use asynchronous I/O
  4. serve one client with each server thread, and use blocking I/O
  5. Build the server code into the kernel

... set nonblocking mode on all network handles, and use select() or poll() to tell which network handle has data waiting. This is the traditional favorite. With this scheme, the kernel tells you whether a file descriptor is ready, whether or not you've done anything with that file descriptor since the last time the kernel told you about it. (The name 'level triggered' comes from computer hardware design; it's the opposite of 'edge triggered'. Jonathon Lemon introduced the terms in his BSDCON 2000 paper on kqueue().)

Note: it's particularly important to remember that readiness notification from the kernel is only a hint; the file descriptor might not be ready anymore when you try to read from it. That's why it's important to use nonblocking mode when using readiness notification.

An important bottleneck in this method is that read() or sendfile() from disk blocks if the page is not in core at the moment; setting nonblocking mode on a disk file handle has no effect. Same thing goes for memory-mapped disk files. The first time a server needs disk I/O, its process blocks, all clients must wait, and that raw nonthreaded performance goes to waste.
This is what asynchronous I/O is for, but on systems that lack AIO, worker threads or processes that do the disk I/O can also get around this bottleneck. One approach is to use memory-mapped files, and if mincore() indicates I/O is needed, ask a worker to do the I/O, and continue handling network traffic. Jef Poskanzer mentions that Pai, Druschel, and Zwaenepoel's 1999 Flash web server uses this trick; they gave a talk at Usenix '99 on it. It looks like mincore() is available in BSD-derived Unixes like FreeBSD and Solaris, but is not part of the Single Unix Specification. It's available as part of Linux as of kernel 2.3.51, thanks to Chuck Lever.

But in November 2003 on the freebsd-hackers list, Vivek Pei et al reported very good results using system-wide profiling of their Flash web server to attack bottlenecks. One bottleneck they found was mincore (guess that wasn't such a good idea after all) Another was the fact that sendfile blocks on disk access; they improved performance by introducing a modified sendfile() that return something like EWOULDBLOCK when the disk page it's fetching is not yet in core. (Not sure how you tell the user the page is now resident... seems to me what's really needed here is aio_sendfile().) The end result of their optimizations is a SpecWeb99 score of about 800 on a 1GHZ/1GB FreeBSD box, which is better than anything on file at

There are several ways for a single thread to tell which of a set of nonblocking sockets are ready for I/O:

See Poller_select (cc, h) for an example of how to use select() interchangeably with other readiness notification schemes.
Some OS's (e.g. Solaris 8) speed up poll() et al by use of techniques like poll hinting, which was implemented and benchmarked by Niels Provos for Linux in 1999.
See Poller_poll (cc, h, benchmarks) for an example of how to use poll() interchangeably with other readiness notification schemes.
The idea behind /dev/poll is to take advantage of the fact that often poll() is called many times with the same arguments. With /dev/poll, you get an open handle to /dev/poll, and tell the OS just once what files you're interested in by writing to that handle; from then on, you just read the set of currently ready file descriptors from that handle.
It appeared quietly in Solaris 7 (see patchid 106541) but its first public appearance was in Solaris 8; according to Sun, at 750 clients, this has 10% of the overhead of poll().
Various implementations of /dev/poll were tried on Linux, but none of them perform as well as epoll, and were never really completed. /dev/poll use on Linux is not recommended.
See Poller_devpoll (cc, h benchmarks ) for an example of how to use /dev/poll interchangeably with many other readiness notification schemes. (Caution - the example is for Linux /dev/poll, might not work right on Solaris.)
See below. kqueue() can specify either edge triggering or level triggering.

Readiness change notification (or edge-triggered readiness notification) means you give the kernel a file descriptor, and later, when that descriptor transitions from not ready to ready, the kernel notifies you somehow. It then assumes you know the file descriptor is ready, and will not send any more readiness notifications of that type for that file descriptor until you do something that causes the file descriptor to no longer be ready (e.g. until you receive the EWOULDBLOCK error on a send, recv, or accept call, or a send or recv transfers less than the requested number of bytes).

When you use readiness change notification, you must be prepared for spurious events, since one common implementation is to signal readiness whenever any packets are received, regardless of whether the file descriptor was already ready.

This is the opposite of "level-triggered" readiness notification. It's a bit less forgiving of programming mistakes, since if you miss just one event, the connection that event was for gets stuck forever. Nevertheless, I have found that edge-triggered readiness notification made programming nonblocking clients with OpenSSL easier, so it's worth trying.

[[ [Banga, Mogul, Drusha '99]]] described this kind of scheme in 1999.

There are several APIs which let the application retrieve 'file descriptor became ready' notifications:

FreeBSD 4.3 and later, and NetBSD-current as of Oct 2002, support a generalized alternative to poll() called kqueue()/kevent(); it supports both edge-triggering and level-triggering. (See also Jonathan Lemon's page and his BSDCon 2000 paper on kqueue().)
Like /dev/poll, you allocate a listening object, but rather than opening the file /dev/poll, you call kqueue() to allocate one. To change the events you are listening for, or to get the list of current events, you call kevent() on the descriptor returned by kqueue(). It can listen not just for socket readiness, but also for plain file readiness, signals, and even for I/O completion.
Note: as of October 2000, the threading library on FreeBSD does not interact well with kqueue(); evidently, when kqueue() blocks, the entire process blocks, not just the calling thread.
See Poller_kqueue (cc, h, benchmarks) for an example of how to use kqueue() interchangeably with many other readiness notification schemes.
Examples and libraries using kqueue():
On 11 July 2001, Davide Libenzi proposed an alternative to realtime signals; his patch provides what he now calls /dev/epoll This is just like the realtime signal readiness notification, but it coalesces redundant events, and has a more efficient scheme for bulk event retrieval.
Epoll was merged into the 2.5 kernel tree as of 2.5.46 after its interface was changed from a special file in /dev to a system call, sys_epoll. A patch for the older version of epoll is available for the 2.4 kernel.
There was a lengthy debate about unifying epoll, aio, and other event sources on the linux-kernel mailing list around Halloween 2002. It may yet happen, but Davide is concentrating on firming up epoll in general first.
The 2.4 linux kernel can deliver socket readiness events via a particular realtime signal. Here's how to turn this behavior on:
/* Mask off SIGIO and the signal you want to use. */
sigaddset(&sigset, signum);
sigaddset(&sigset, SIGIO);
sigprocmask(SIG_BLOCK, &m_sigset, NULL);
/* For each file descriptor, invoke F_SETOWN, F_SETSIG, and set O_ASYNC. */
fcntl(fd, F_SETOWN, (int) getpid());
fcntl(fd, F_SETSIG, signum);
flags = fcntl(fd, F_GETFL);
fcntl(fd, F_SETFL, flags);
This sends that signal when a normal I/O function like read() or write() completes. To use this, write a normal poll() outer loop, and inside it, after you've handled all the fd's noticed by poll(), you loop calling sigwaitinfo().
If sigwaitinfo or sigtimedwait returns your realtime signal, siginfo.si_fd and siginfo.si_band give almost the same information as pollfd.fd and pollfd.revents would after a call to poll(), so you handle the i/o, and continue calling sigwaitinfo().
If sigwaitinfo returns a traditional SIGIO, the signal queue overflowed, so you flush the signal queue by temporarily changing the signal handler to SIG_DFL, and break back to the outer poll() loop.

See Poller_sigio (cc, h) for an example of how to use rtsignals interchangeably with many other readiness notification schemes.
See Zach Brown's phhttpd for example code that uses this feature directly. (Or don't; phhttpd is a bit hard to figure out...)
[Provos, Lever, and Tweedie 2000] describes a recent benchmark of phhttpd using a variant of sigtimedwait(), sigtimedwait4(), that lets you retrieve multiple signals with one call. Interestingly, the chief benefit of sigtimedwait4() for them seemed to be it allowed the app to gauge system overload (so it could behave appropriately). (Note that poll() provides the same measure of system overload.)
Vitaly Luban announced a patch implementing this scheme on 18 May 2001; his patch lives at (Note: as of Sept 2001, there may still be stability problems with this patch under heavy load. dkftpbench at about 4500 users may be able to trigger an oops.)
See Poller_sigfd (cc, h) for an example of how to use signal-per-fd interchangeably with many other readiness notification schemes.

This has not yet become popular in Unix, probably because few operating systems support asynchronous I/O, also possibly because it (like nonblocking I/O) requires rethinking your application. Under standard Unix, asynchronous I/O is provided by the aio_ interface (scroll down from that link to "Asynchronous input and output"), which associates a signal and value with each I/O operation. Signals and their values are queued and delivered efficiently to the user process. This is from the POSIX 1003.1b realtime extensions, and is also in the Single Unix Specification, version 2.

AIO is normally used with edge-triggered completion notification, i.e. a signal is queued when the operation is complete. (It can also be used with level triggered completion notification by calling aio_suspend(), though I suspect few people do this.)

glibc 2.1 and later provide a generic implementation written for standards compliance rather than performance.

Ben LaHaise's implementation for Linux AIO was merged into the main Linux kernel as of 2.5.32. It doesn't use kernel threads, and has a very efficient underlying api, but (as of 2.6.0-test2) doesn't yet support sockets. (There is also an AIO patch for the 2.4 kernels, but the 2.5/2.6 implementation is somewhat different.) More info:

Suparna also suggests having a look at the the DAFS API's approach to AIO.

Red Hat AS and Suse SLES both provide a high-performance implementation on the 2.4 kernel; it is related to, but not completely identical to, the 2.6 kernel implementation.

In 1999, SGI implemented high-speed AIO for Linux. As of version 1.1, it's said to work well with both disk I/O and sockets. It seems to use kernel threads. It is still useful for people who can't wait for Ben's AIO to support sockets.

The O'Reilly book POSIX.4: Programming for the Real World is said to include a good introduction to aio.

A tutorial for the earlier, nonstandard, aio implementation on Solaris is online at Sunsite. It's probably worth a look, but keep in mind you'll need to mentally convert "aioread" to "aio_read", etc.

Note that AIO doesn't provide a way to open files without blocking for disk I/O; if you care about the sleep caused by opening a disk file, Linus suggests you should simply do the open() in a different thread rather than wishing for an aio_open() system call.

Under Windows, asynchronous I/O is associated with the terms "Overlapped I/O" and IOCP or "I/O Completion Port". Microsoft's IOCP combines techniques from the prior art like asynchronous I/O (like aio_write) and queued completion notification (like when using the aio_sigevent field with aio_write) with a new idea of holding back some requests to try to keep the number of running threads associated with a single IOCP constant. For more information, see Inside I/O Completion Ports by Mark Russinovich at, Jeffrey Richter's book "Programming Server-Side Applications for Microsoft Windows 2000" (Amazon, MSPress), U.S. patent #06223207, or MSDN.

... and let read() and write() block. Has the disadvantage of using a whole stack frame for each client, which costs memory. Many OS's also have trouble handling more than a few hundred threads. If each thread gets a 2MB stack (not an uncommon default value), you run out of *virtual memory* at (2^30 / 2^21) = 512 threads on a 32 bit machine with 1GB user-accessible VM (like, say, Linux as normally shipped on x86). You can work around this by giving each thread a smaller stack, but since most thread libraries don't allow growing thread stacks once created, doing this means designing your program to minimize stack use. You can also work around this by moving to a 64 bit processor.

The thread support in Linux, FreeBSD, and Solaris is improving, and 64 bit processors are just around the corner even for mainstream users. Perhaps in the not-too-distant future, those who prefer using one thread per client will be able to use that paradigm even for 10000 clients. Nevertheless, at the current time, if you actually want to support that many clients, you're probably better off using some other paradigm.

For an unabashedly pro-thread viewpoint, see Why Events Are A Bad Idea (for High-concurrency Servers) by von Behren, Condit, and Brewer, UCB, presented at HotOS IX. Anyone from the anti-thread camp care to point out a paper that rebuts this one? :-)

LinuxTheads is the name for the standard Linux thread library. It is integrated into glibc since glibc2.0, and is mostly Posix-compliant, but with less than stellar performance and signal support.

NGPT is a project started by IBM to bring good Posix-compliant thread support to Linux. It's at stable version 2.2 now, and works well... but the NGPT team has announced that they are putting the NGPT codebase into support-only mode because they feel it's "the best way to support the community for the long term". The NGPT team will continue working to improve Linux thread support, but now focused on improving NPTL. (Kudos to the NGPT team for their good work and the graceful way they conceded to NPTL.)

NPTL is a project by Ulrich Drepper (the benevolent dict^H^H^H^Hmaintainer of glibc) and Ingo Molnar to bring world-class Posix threading support to Linux.

As of 5 October 2003, NPTL is now merged into the glibc cvs tree as an add-on directory (just like linuxthreads), so it will almost certainly be released along with the next release of glibc.

The first major distribution to include an early snapshot of NPTL was Red Hat 9. (This was a bit inconvenient for some users, but somebody had to break the ice...)

NPTL links:

Here's my try at describing the history of NPTL (see also Jerry Cooperstein's article):

In March 2002, Bill Abt of the NGPT team, the glibc maintainer Ulrich Drepper, and others met to figure out what to do about LinuxThreads. One idea that came out of the meeting was to improve mutex performance; Rusty Russell et al subsequently implemented fast userspace mutexes (futexes)), which are now used by both NGPT and NPTL. Most of the attendees figured NGPT should be merged into glibc.

Ulrich Drepper, though, didn't like NGPT, and figured he could do better. (For those who have ever tried to contribute a patch to glibc, this may not come as a big surprise :-) Over the next few months, Ulrich Drepper, Ingo Molnar, and others contributed glibc and kernel changes that make up something called the Native Posix Threads Library (NPTL). NPTL uses all the kernel enhancements designed for NGPT, and takes advantage of a few new ones. Ingo Molnar described the kernel enhancements as follows:

While NPTL uses the three kernel features introduced by NGPT: getpid() returns PID, CLONE_THREAD and futexes; NPTL also uses (and relies on) a much wider set of new kernel features, developed as part of this project.

Some of the items NGPT introduced into the kernel around 2.5.8 got modified, cleaned up and extended, such as thread group handling (CLONE_THREAD). [the CLONE_THREAD changes which impacted NGPT's compatibility got synced with the NGPT folks, to make sure NGPT does not break in any unacceptable way.]

The kernel features developed for and used by NPTL are described in the design whitepaper, ...

A short list: TLS support, various clone extensions (CLONE_SETTLS, CLONE_SETTID, CLONE_CLEARTID), POSIX thread-signal handling, sys_exit() extension (release TID futex upon VM-release), the sys_exit_group() system-call, sys_execve() enhancements and support for detached threads.

There was also work put into extending the PID space - eg. procfs crashed due to 64K PID assumptions, max_pid, and pid allocation scalability work. Plus a number of performance-only improvements were done as well.

In essence the new features are a no-compromises approach to 1:1 threading - the kernel now helps in everything where it can improve threading, and we precisely do the minimally necessary set of context switches and kernel calls for every basic threading primitive.

One big difference between the two is that NPTL is a 1:1 threading model, whereas NGPT is an M:N threading model (see below). In spite of this, Ulrich's initial benchmarks seem to show that NPTL is indeed much faster than NGPT. (The NGPT team is looking forward to seeing Ulrich's benchmark code to verify the result.)

FreeBSD supports both LinuxThreads and a userspace threading library. Also, a new M:N implementation called KSE is being worked on, and may be included with the upcoming FreeBSD 5.0. For one overview, see

On 25 Mar 2003, Jeff Roberson posted on freebsd-arch:

... Thanks to the foundation provided by Julian, David Xu, Mini, Dan Eischen, and everyone else who has participated with KSE and libpthread development Mini and I have developed a 1:1 threading implementation. This code works in parallel with KSE and does not break it in any way. It actually helps bring M:N threading closer by testing out shared bits. ...

According to a note from Noriyuki Soda:

Kernel supported M:N thread library based on the Scheduler Activations model is merged into NetBSD-current on Jan 18 2003.

For details, see An Implementation of Scheduler Activations on the NetBSD Operating System by Nathan J. Williams, Wasabi Systems, Inc., presented at FREENIX '02.

The thread support in Solaris is evolving... from Solaris 2 to Solaris 8, the default threading library used an M:N model, but Solaris 9 defaults to 1:1 model thread support. See Sun's multithreaded programming guide and Sun's note about Java and Solaris threading.

As is well known, Java up to JDK1.3.x did not support any method of handling network connections other than one thread per client. Volanomark is a good microbenchmark which measures throughput in messsages per second at various numbers of simultaneous connections. As of May 2003, JDK 1.3 implementations from various vendors are in fact able to handle ten thousand simultaneous connections -- albeit with significant performance degradation. See Table 4 for an idea of which JVMs can handle 10000 connections, and how performance suffers as the number of connections increases.

There is a choice when implementing a threading library: you can either put all the threading support in the kernel (this is called the 1:1 threading model), or you can move a fair bit of it into userspace (this is called the M:N threading model). At one point, M:N was thought to be higher performance, but it's so complex that it's hard to get right, and most people are moving away from it.

Novell and Microsoft are both said to have done this at various times, at least one NFS implementation does this, khttpd does this for Linux and static web pages, and "TUX" (Threaded linUX webserver) is a blindingly fast and flexible kernel-space HTTP server by Ingo Molnar for Linux. Ingo's September 1, 2000 announcement says an alpha version of TUX can be downloaded from, and explains how to join a mailing list for more info.
The linux-kernel list has been discussing the pros and cons of this approach, and the consensus seems to be instead of moving web servers into the kernel, the kernel should have the smallest possible hooks added to improve web server performance. That way, other kinds of servers can benefit. See e.g. Zach Brown's remarks about userland vs. kernel http servers. It appears that the 2.4 linux kernel provides sufficient power to user programs, as the X15 server runs about as fast as Tux, but doesn't use any kernel modifications.

Richard Gooch has written a paper discussing I/O options.

In 2001, Tim Brecht and MMichal Ostrowski measured various strategies for simple select-based servers. Their data is worth a look.

In 2003, Tim Brecht posted source code for userver, a small web server put together from several servers written by Abhishek Chandra, David Mosberger, David Pariag, and Michal Ostrowski. It can use select(), poll(), epoll(), or sigio.

Back in March 1999, Dean Gaudet posted:

I keep getting asked "why don't you guys use a select/event based model like Zeus? It's clearly the fastest." ...

His reasons boiled down to "it's really hard, and the payoff isn't clear". Within a few months, though, it became clear that people were willing to work on it.

Mark Russinovich wrote an editorial and an article discussing I/O strategy issues in the 2.2 Linux kernel. Worth reading, even he seems misinformed on some points. In particular, he seems to think that Linux 2.2's asynchronous I/O (see F_SETSIG above) doesn't notify the user process when data is ready, only when new connections arrive. This seems like a bizarre misunderstanding. See also comments on an earlier draft, Ingo Molnar's rebuttal of 30 April 1999, Russinovich's comments of 2 May 1999, a rebuttal from Alan Cox, and various posts to linux-kernel. I suspect he was trying to say that Linux doesn't support asynchronous disk I/O, which used to be true, but now that SGI has implemented KAIO, it's not so true anymore.

See these pages at and MSDN for information on "completion ports", which he said were unique to NT; in a nutshell, win32's "overlapped I/O" turned out to be too low level to be convenient, and a "completion port" is a wrapper that provides a queue of completion events, plus scheduling magic that tries to keep the number of running threads constant by allowing more threads to pick up completion events if other threads that had picked up completion events from this port are sleeping (perhaps doing blocking I/O).

See also OS/400's support for I/O completion ports.

was an interesting discussion on linux-kernel in September 1999 titled "> 15,000 Simultaneous Connections" (and the second week of the thread). Highlights:

Interesting reading!

increases the system limit on open files, and ulimit -n 32768 increases the current process' limit.
On 2.2.x kernels,
echo 32768 > /proc/sys/fs/file-max
echo 65536 > /proc/sys/fs/inode-max
increases the system limit on open files, and ulimit -n 32768 increases the current process' limit.
I verified that a process on Red Hat 6.0 (2.2.5 or so plus patches) can open at least 31000 file descriptors this way. Another fellow has verified that a process on 2.2.12 can open at least 90000 file descriptors this way (with appropriate limits). The upper bound seems to be available memory.
Stephen C. Tweedie posted about how to set ulimit limits globally or per-user at boot time using initscript and pam_limit.
In older 2.2 kernels, though, the number of open files per process is still limited to 1024, even with the above changes.
See also Oskar's 1998 post, which talks about the per-process and system-wide limits on file descriptors in the 2.0.36 kernel.

On any architecture, you may need to reduce the amount of stack space allocated for each thread to avoid running out of virtual memory. You can set this at runtime with pthread_attr_init() if you're using pthreads.

See also Volano's detailed instructions for raising file, thread, and FD_SET limits in the 2.2 kernel. Wow. This document steps you through a lot of stuff that would be hard to figure out yourself, but is somewhat dated.

Up through JDK 1.3, Java's standard networking libraries mostly offered the one-thread-per-client model. There was a way to do nonblocking reads, but no way to do nonblocking writes.

In May 2001, JDK 1.4 introduced the package java.nio to provide full support for nonblocking I/O (and some other goodies). See the release notes for some caveats. Try it out and give Sun feedback!

HP's java also includes a Thread Polling API.

In 2000, Matt Welsh implemented nonblocking sockets for Java; his performance benchmarks show that they have advantages over blocking sockets in servers handling many (up to 10000) connections. His class library is called java-nbio; it's part of the Sandstorm project. Benchmarks showing performance with 10000 connections are available.

See also Dean Gaudet's essay on the subject of Java, network I/O, and threads, and the paper by Matt Welsh on events vs. worker threads.

Before NIO, there were several proposals for improving Java's networking APIs:

According to a note from Noriyuki Soda:
Sending side zero-copy is supported since NetBSD-1.6 release by specifying "SOSEND_LOAN" kernel option. This option is now default on NetBSD-current (you can disable this feature by specifying "SOSEND_NO_LOAN" in the kernel option on NetBSD_current). With this feature, zero-copy is automatically enabled, if data more than 4096 bytes are specified as data to be sent.
A zero-copy implementation of sendfile() is on its way for the 2.4 kernel. See LWN Jan 25 2001.
One developer using sendfile() with Freebsd reports that using POLLWRBAND instead of POLLOUT makes a big difference.
Solaris 8 (as of the July 2001 update) has a new system call 'sendfilev'. A copy of the man page is here.. The Solaris 8 7/01 release notes also mention it. I suspect that this will be most useful when sending to a socket in blocking mode; it'd be a bit of a pain to use with a nonblocking socket.
See LWN Jan 25 2001 for a summary of some very interesting discussions on linux-kernel about TCP_CORK and a possible alternative MSG_MORE.
"I've compared the raw performance of a select-based server with a multiple-process server on both FreeBSD and Solaris/x86. On microbenchmarks, there's only a marginal difference in performance stemming from the software architecture. The big performance win for select-based servers stems from doing application-level caching. While multiple-process servers can do it at a higher cost, it's harder to get the same benefits on real workloads (vs microbenchmarks). I'll be presenting those measurements as part of a paper that'll appear at the next Usenix conference. If you've got postscript, the paper is available at"

For Linux, it looks like kernel bottlenecks are being fixed constantly. See Linux Weekly News, Kernel Traffic, the Linux-Kernel mailing list, and my Mindcraft Redux page.

In March 1999, Microsoft sponsored a benchmark comparing NT to Linux at serving large numbers of http and smb clients, in which they failed to see good results from Linux. See also my article on Mindcraft's April 1999 Benchmarks for more info.

See also The Linux Scalability Project. They're doing interesting work, including Niels Provos' hinting poll patch, and some work on the thundering herd problem.

See also Mike Jagdis' work on improving select() and poll(); here's Mike's post about it.

Mohit Aron ( writes that rate-based clocking in TCP can improve HTTP response time over 'slow' connections by 80%.

Two tests in particular are simple, interesting, and hard:

  1. raw connections per second (how many 512 byte files per second can you serve?)
  2. total transfer rate on large files with many slow clients (how many 28.8k modem clients can simultaneously download from your server before performance goes to pot?)

Jef Poskanzer has published benchmarks comparing many web servers. See for his results.

I also have a few old notes about comparing thttpd to Apache that may be of interest to beginners.

Chuck Lever keeps reminding us about Banga and Druschel's paper on web server benchmarking. It's worth a read.

IBM has an excellent paper titled Java server benchmarks [Baylor et al, 2000]. It's worth a read.


$Log: c10k.html,v $
Revision 1.207 2003/11/03 08:09:39 dank
Link to Linus's message deprecating the idea of aio_open

Revision 1.206 2003/11/03 07:44:34 dank
link to userver

Revision 1.205 2003/11/03 06:55:26 dank
Link to Vivek Pei's new Flash paper, mention great specweb99 score

Copyright 1999-2003 Dan Kegel
Last updated: 2 Nov 2003
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