I am examining an application where a JBOSS Application Server communicates with satellite JBOSS Application Servers (1 main server, hundreds of satellites).
When observing in the Windows Resource Monitor I can view the connections and see the latency by satellite - most are sub-second, but I see 10 over 1 second, of those 4 over 2 seconds and 1 over 4 seconds. This is a "moment in time" view, so as connections expire and rebuild when they need, the trend can shift. I do observe the same pair of systems have a ping latency matching seen on the connection list - so I suspect it's connection related (slow pipe, congestion, or anything in the line between points A and B).
My question is what should be a target latency, keeping in mind the satellites are VPN'd from various field sites. I use 2 seconds as a dividing line to when I need the network team to investigate, I'd like to survey what rule of thumb do you use in evaluating when the latency for a transient connection starts peaking - is it over a second? I do observe the same pair of systems have a ping latency matching seen on the connection list - so I know it's connection related.
Related
I want to understand how to determine whether my internet connection is a bottleneck or not during a jmeter stress test.
Here is a bit of background for my problem:
I made a stress test with a 2 hours duration, with 2000 threads ramped up over the whole 2 hours duration hoping to find the upper limit of the server, but I am thinking that maybe I hit some other limit and not the server's, as it's not shutting down, aka not responding with 4xx or 5xx error codes. I can only see in the report that the transactions per second go fairly quickly to 580, but they then will not go above.
When I run the stress test against one server endpoint and the load keeps increasing, I need to be connected to a VPN to have access to that endpoint.
Most of the stress test runs I tried, behave like this:
Although, the number of threads increases, like this:
And I only have Non-HTTP error response codes which are not reflected in the server logs, aka the server reports no 4xx or 5xx error codes:
The server will not go over 580 TPS, but it will not throw errors either:
As per this site, my internet connection (via cable or wifi, I see no major difference) has 1ms ping, 400-420 Mbps download capacity and around 250 Mbps upload capacity - granted, this is calculated with some server selected by them, located relatively near to my location.
How can I know how much of that "pipe" capacity is being used so that I can say with certainty that my internet connection is not a bottleneck?
Can the VPN be a bottleneck?
There are multiple options like:
Bytes Throughput Over Time chart which is a part of JMeter's HTML Reporting Dashboard
Bytes Throughput Over Time chart from JMeter Plugins project
JMeter PerfMon Plugin which provides complete Network IO metrics
Your operating system should provide built-in applications for network monitoring
According to this comment, there's a minimum of 4 connections per "running application process" on MongoDB Realm, three of these four are constant (monitoring connections) and the rest depends on the number of queries/writes. As I understand, each Realm synchronized is another connection.
A complex app can have multiple Realms synchronized, meaning it wouldn't be hard to have 10 open connections. Does this mean that even paying for the highest cluster tier (M700, $33.26/hr) the app couldn't have more than 12800 (128000 connections / 10 open connections per client) active users?
we're currently having issue in our production servers and would like to try to replicate the issue in our dev. I'm currently awaiting access to our Performance Monitoring Tool, and while waiting would like to play with it a little.
I'm thinking of, since I suspect a host throttling in prod, forcing hosts to throttle in dev and see if it will recreate the issue.
Is there a way to do this?
As others have mentioned, monitoring of the throttling counters and other counters like memory and WIP messages is a must to see what is going on in your production server. Also would recommend that set up a SCOM alert on throttling states of 3+ (publishing + delivery states), if you have SCOM.
Message throughput can grind to a halt on especially the memory (4, 5) and Queue Size (6) states. States 1+2 are generally short lived (e.g. arrival of a large batch of messages) and Biztalk recovers within a few seconds.
Simulating the memory state in your Dev environment should be straightforward by tweaking the throttling thresholds (obviously not something to be taken lightly in production!)
e.g. to trigger the Memory threshold states - AFAIK the lowest memory usage threshold you can set is 101MB. Running a load test in dev should then be able reproduce the throttle.
There is also apparantly a user-based throttling override to set states 10 and 11 although haven't actually tried this.
Some other experience on avoiding throttling:
(Caveat - I don't have an active BizTalk 2006/R2 setup - this is for 2009 / 2010)
If you do a lot of asynchronous processing (e.g. Queue receives), ensure that you have split functionality into separate Hosts for Receive, Processing and Send hosts. This way you can adjust the throttling for asynch Receive hosts to trigger much earlier than the processing and sending hosts - this should have the effect of constricting new incoming messages to the messagebox but allowing existing messages to complete processing.
On 64 bit hosts, the default 25% memory host usage throttling level is usually an unnecessary liability - we increased this using Yossi Dahan's recommendation of 50% on a 4GB server
Note that suspended messages count toward throttling state 6 - ensure that you have a strategy for dealing with suspended messages (and obviously ensure that the Sql Agent jobs are running!).
A bit of a long description below, but it is a quite tricky problem. I have tried to cover what we do know about the problem in order to narrow down the search. The question is more of an ongoing investigation than a single-question based one but I think it may help others as well. But please add information in comments or correct me if you think I am wrong about some assumptions below.
UPDATE 19/2, 2013: We have cleared some question marks in this and I have a theory of what the main problem is which I'll update below. Not ready to write a "solved" response to it yet though.
UPDATE 24/4, 2013: Things have been stable in production (though I believe it is temporary) for a while now and I think it is due to two reasons. 1) port increase, and 2) reduced number of outgoing (forwarded) requests. I'll continue this update futher down in the correct context.
We are currently doing an investigation in our production environment to determine why our IIS web server does not scale when too many outgoing asynchronous web service requests are being done (one incoming request may trigger multiple outgoing requests).
CPU is only at 20%, but we receive HTTP 503 errors on incoming requests and many outgoing web requests get the following exception: “SocketException: An operation on a socket could not be performed because the system lacked sufficient buffer space or because a queue was full” Clearly there is a scalability bottleneck somewhere and we need to find out what it is and if it is possible to solve it by configuration.
Application context:
We are running IIS v7.5 integrated managed pipeline using .NET 4.5 on Windows 2008 R2 64 bit operating system. We use only 1 worker process in IIS. Hardware varies slightly but the machine used for examining the error is an Intel Xeon 8 core (16 hyper threaded).
We use both asynchronous and synchronous web requests. Those that are asynchronous are using the new .NET async support to make each incoming request make multiple HTTP requests in the application to other servers on persisted TCP connections (keep-alive). Synchronous request execution time is low 0-32 ms (longer times occur due to thread context switching). For the asynchronous requests, execution time can be up to 120 ms before the requests are aborted.
Normally each server serves up to ~1000 incoming requests. Outgoing requests are ~300 requests/sec up to ~600 requests/sec when problem starts to arise. Problems only occurs when outgoing async. requests are enabled on the server and we go above a certain level of outgoing requests (~600 req./s).
Possible solutions to the problem:
Searching the Internet on this problem reveals a plethora of possible solutions candidates. Though, they are very much dependent upon versions of .NET, IIS and operating system so it takes time to find something in our context (anno 2013).
Below is a list of solution candidates and the conclusions we have come to so far with regards to our configuration context. I have categorised the detected problem areas, so far in the following main categories:
Some queue(s) fill up
Problems with TCP connections and ports (UPDATE 19/2, 2013: This is the problem)
Too slow allocation of resources
Memory problems (UPDATE 19/2, 2013: This is most likely another problem)
1) Some queue(s) fill up
The outgoing asynchronous request exception message does indicate that some queue of buffer has been filled up. But it does not say which queue/buffer. Via the IIS forum (and blog post referenced there) I have been able to distinguish 4 of possibly 6 (or more) different types of queues in the request pipeline labeled A-F below.
Though it should be stated that of all the below defined queues, we see for certain that the 1.B) ThreadPool performance counter Requests Queued gets very full during the problematic load. So it is likely that the cause of the problem is in .NET level and not below this (C-F).
1.A) .NET Framework level queue?
We use the .NET framework class WebClient for issuing the asynchronous call (async support) as opposed to the HttpClient that we experienced had the same issue but with far lower req/s threshold. We do not know if the .NET Framework implementation hides any internal queue(s) or not above the Thread pool. We don’t think this is the case.
1.B) .NET Thread Pool
The Thread pool acts as a natural queue since the .NET Thread (default) Scheduler is picking threads from the thread pool to be executed.
Performance counter: [ASP.NET v4.0.30319].[Requests Queued].
Configuration possibilities:
(ApplicationPool) maxConcurrentRequestsPerCPU should be 5000 (instead of previous 12). So in our case it should be 5000*16=80.000 requests/sec which should be sufficient enough in our scenario.
(processModel) autoConfig = true/false which allows some threadPool related configuration to be set according to machine configuration. We use true which is a potential error candidate since these values may be set erroneously for our (high) need.
1.C) Global, process wide, native queue (IIS integrated mode only)
If the Thread Pool is full, requests starts to pile up in this native (not-managed) queue.
Performance counter:[ASP.NET v4.0.30319].[Requests in Native Queue]
Configuration possibilities: ????
1.D) HTTP.sys queue
This queue is not the same queue as 1.C) above. Here’s an explanation as stated to me “The HTTP.sys kernel queue is essentially a completion port on which user-mode (IIS) receives requests from kernel-mode (HTTP.sys). It has a queue limit, and when that is exceeded you will receive a 503 status code. The HTTPErr log will also indicate that this happened by logging a 503 status and QueueFull“.
Performance counter: I have not been able to find any performance counter for this queue, but by enabling the IIS HTTPErr log, it should be possible to detect if this queue gets flooded.
Configuration possibilities: This is set in IIS on the application pool, advanced setting: Queue Length. Default value is 1000. I have seen recommendations to increase it to 10.000. Though trying this increase has not solved our issue.
1.E) Operating System unknown queue(s)?
Although unlikely, I guess the OS could actually have a queue somewhere in between the network card buffer and the HTTP.sys queue.
1.F) Network card buffer:
As request arrive to the network card, it should be natural that they are placed in some buffer in order to be picked up by some OS kernel thread. Since this is kernel level execution, and thus fast, it is not likely that it is the culprit.
Windows Performance Counter: [Network Interface].[Packets Received Discarded] using the network card instance.
Configuration possibilities: ????
2) Problems with TCP connections and ports
This is a candidate that pops up here and there, though our outgoing (async) TCP requests are made of a persisted (keep-alive) TCP connection. So as the traffic grows, the number of available ephemeral ports should really only grow due to the incoming requests. And we know for sure that the problem only arises when we have outgoing requests enabled.
However, the problem may still arise due to that the port is allocated during a longer timeframe of the request. An outgoing request may take as long as 120 ms to execute (before the .NET Task (thread) is canceled) which might mean that the number of ports get allocated for a longer time period. Analyzing the Windows Performance Counter, verifies this assumption since the number of TCPv4.[Connection Established] goes from normal 2-3000 to peaks up to almost 12.000 in total when the problem occur.
We have verified that the configured maximum amount of TCP connections is set to the default of 16384. In this case, it may not be the problem, although we are dangerously close to the max limit.
When we try using netstat on the server it mostly returns without any output at all, also using TcpView shows very few items in the beginning. If we let TcpView run for a while it soon starts to show new (incoming) connections quite rapidly (say 25 connections/sec). Almost all connections are in TIME_WAIT state from the beginning, suggesting that they have already completed and waiting for clean up. Do those connections use ephemeral ports? The local port is always 80, and the remote port is increasing. We wanted to use TcpView in order to see the outgoing connections, but we can’t see them listed at all, which is very strange. Can’t these two tools handle the amount of connections we are having?
(To be continued.... But please fill in with info if you know it… )
Furhter more, as a side kick here. It was suggested in this blog post "ASP.NET Thread Usage on IIS 7.5, IIS 7.0, and IIS 6.0" that ServicePointManager.DefaultConnectionLimit should be set to int maxValue which otherwise could be a problem. But in .NET 4.5, this is the default already from the start.
UPDATE 19/2, 2013:
It is reasonable to assume that we did in fact hit the max limit of 16.384 ports. We doubled the number of ports on all but one server and only the old server would run into problem when we hit the old peak load of outgoing requests. So why did the TCP.v4.[Connections Established] never show us a higher number than ~12.000 at problem times? MY theory: Most likely, although not established as fact (yet), the Performance Counter TCPv4.[Connections Established] is not equivalent to the number of ports that are currently allocated. I have not had time to catch up on the TCP state studying yet, but I am guessing that there are more TCP states than what the "Connection Established" shows which would render the port as being ccupied. Though since we cannot use the "Connection Established" performance counter as a way to detect the danger of running out of ports, it is important that we find some other way of detecting when reaching this max port range. And as described in the text above, we are not able to use either with NetStat or the application TCPview for this on our production servers. This is a problem! (I'll write more about it in an upcoming response I think to this post)
The number of ports are restricted on windows to some maximum 65.535 (although the first ~1000 should probably not be used). But it should be possible to avoid the problem of running out of ports by decreasing the time for TCP state TIME_WAIT (default to 240 seconds) as described in numerous places.It should free up ports faster. I was first a bit hestitant about this doing this since we use both long running database queries as well as WCF calls on TCP and I wouldn't like to descrease the time constraint. Although not having caught up in my TCP state machine reading yet, I think it might not be a problem after all. The state TIME_WAIT, I think, is only there in order to allow for the handshake of a proper shut down to the client. So the actual data transfer on an existing TCP connection should not time out due to this time limit. Worse case scenario, the client is not shut down properly and it instead neads to time out. I guess all browsers may not be implementing this correctly and it could possibly be a problem on the client side only. Though I am guessing a bit here...
END UPDATE 19/2, 2013
UPDATE 24/4, 2013:
We have increased the number of port to to the maximum value. At the same time we do not get as many forwarded outgoing requests as earlier. These two in combination should be the reason why we have not had any incidents. However, it is only temporary since the number of outgoing requests are bound to increase again in the future on these servers. The problem thus lies in, I think, that port for the incoming requests has to remain open during the time frame for the response of the forwarded requests. In our application, this cancelation limit for these forwarded requests is 120 ms which could be compared with the normal <1ms to handle a non forwarded request. So in essence, I believe the definite number of ports is the major scalability bottleneck on such high throughput servers (>1000 requests/sec on ~16 cores machines) that we are using. This in combination with the GC work on cache reload (se below) makes the server especially vulernable.
END UPDATE 24/4
3) Too slow allocation of resources
Our performance counters show that the number of queued requests in the Thread Pool (1B) fluctuates a lot during the time of the problem. So potentially this means that we have a dynamic situation in which the queue length starts to oscillate due to changes in the environment. For instance, this would be the case if there are flooding protection mechanisms that are activated when traffic is flooding. As it is, we have a number of these mechanisms:
3.A) Web load balancer
When things go really bad and the server responds with a HTTP 503 error, the load balancer will automatically remove the web server from being active in production for a 15 second period. This means that the other servers will take the increased load during the time frame. During the “cooling period”, the server may finish serving its request and it will automatically be reinstated when the load balancer does its next ping. Of course this only is good as long as all servers don’t have a problem at once. Luckily, so far, we have not been in this situation.
3.B) Application specific valve
In the web application, we have our own constructed valve (Yes. It is a "valve". Not a "value") triggered by a Windows Performance Counter for Queued Requests in the thread pool. There is a thread, started in Application_Start, that checks this performance counter value each second. And if the value exceeds 2000, all outgoing traffic ceases to be initiated. The next second, if the queue value is below 2000, outgoing traffic starts again.
The strange thing here is that it has not helped us from reaching the error scenario since we don’t have much logging of this occurring. It may mean that when traffic hits us hard, things goes bad really quickly so that the 1 second time interval check actually is too high.
3.C) Thread pool slow increase (and decrease) of threads
There is another aspect of this as well. When there is a need for more threads in the application pool, these threads gets allocated very slowly. From what I read, 1-2 threads per second. This is so because it is expensive to create threads and since you don’t want too many threads anyways in order to avoid expensive context switching in the synchronous case, I think this is natural. However, it should also mean that if a sudden large burst of traffic hits us, the number of threads are not going to be near enough to satisfy the need in the asynchronous scenario and queuing of requests will start. This is a very likely problem candidate I think. One candidate solution may be then to increase the minimum amount of created threads in the ThreadPool. But I guess this may also effect performance of the synchronously running requests.
4) Memory problems
(Joey Reyes wrote about this here in a blog post)
Since objects get collected later for asynchronous requests (up to 120ms later in our case), memory problem can arise since objects can be promoted to generation 1 and the memory will not be recollected as often as it should. The increased pressure on the Garbage Collector may very well cause extended thread context switching to occur and further weaken capacity of the server.
However, we don’t see an increased GC- nor CPU usage during the time of the problem so we don’t think the suggested CPU throttling mechanism is a solution for us.
UPDATE 19/2, 2013: We use a cache swap mechanism at regular intervalls at which an (almost) full in-memory cache is reload into memory and the old cache can get garbage collected. At these times, the GC will have to work harder and steal resources from the normal request handling. Using Windows Performance counter for thread context switching it shows that the number of context switches decreases significantly from the normal high value at the time of a high GC usage. I think that during such cache reloads, the server is extra vulnernable for queueing up requests and it is necessary to reduce the footprint of the GC. One potential fix to the problem would be to just fill the cache without allocating memory all the time. A bit more work, but it should be doable.
UPDATE 24/4, 2013:
I am still in the middle of the cache reload memory tweak in order to avoid having the GC running as much. But we normally have some 1000 queued requests temporarily when the GC runs. Since it runs on all threads, it is naturall that it steals resources from the normal requests handling. I'll update this status once this tweak has been deployed and we can see a difference.
END UPDATE 24/4
I have implemented a reverse proxy through an Async Http Handler for benchmarking purposes (as a part of my Phd. Thesis) and run into the very same problems as you.
In order to scale it is mandatory to have processModel set to false and fine tune the thread pools. I have found that, contrary to what the documentation regarding processModel defaults says, many of the thread pools are not properly configured when processModel is set to true. The maxConnection setting it is also important as it limits your scalability if the limit is set too low. See http://support.microsoft.com/default.aspx?scid=kb;en-us;821268
Regarding your app running out of ports because of the TIME_WAIT delay on the socket, I have also faced the same problem because I was injecting traffic from a limited set of machines with more than 64k requests in 240 seconds. I lowered the TIME_WAIT to 30 seconds without any problems.
I also mistakenly reused a proxy object to a Web Services endpoint in several threads. Although the proxy doesn't have any state, I found that the GC had a lot of problems collecting the memory associated with its internal buffers (String [] instances) and that caused my app to run out of memory.
Some interesting performance counters that you should monitor are the ones related to Queued requests, requests in execution and request time under the ASP.NET apps category. If you see queued requests or that the execution time is low but the clients see long request times, then you have some sort of contention in your server. Also monitor counters under the LocksAndThreads category looking for contention.
Since asynchronous requests hold up the tcp sockets for longer, maybe you need to look at
maxconnection property within connection management in your web.config?
Please refer to this link: http://support.microsoft.com/default.aspx?scid=kb;en-us;821268
We faced similar problem and tuned this parameter to fix our issue. Maybe this will help you.
Edit: Also, lots of TIME_WAITs indicate a connection leak within the code based on past experience. Possible causes: 1) Not disposing connections used. 2) Incorrect implementation of connection pooling.
Say if I was to get shared, virtual or dedicated hosting, I read somewhere a server/machine can only handle 64,000 TCP connections at one time, is this true? How many could any type of hosting handle regardless of bandwidth? I'm assuming HTTP works over TCP.
Would this mean only 64,000 users could connect to the website, and if I wanted to serve more I'd have to move to a web farm?
In short:
You should be able to achieve in the order of millions of simultaneous active TCP connections and by extension HTTP request(s). This tells you the maximum performance you can expect with the right platform with the right configuration.
Today, I was worried whether IIS with ASP.NET would support in the order of 100 concurrent connections (look at my update, expect ~10k responses per second on older ASP.Net Mono versions). When I saw this question/answers, I couldn't resist answering myself, many answers to the question here are completely incorrect.
Best Case
The answer to this question must only concern itself with the simplest server configuration to decouple from the countless variables and configurations possible downstream.
So consider the following scenario for my answer:
No traffic on the TCP sessions, except for keep-alive packets (otherwise you would obviously need a corresponding amount of network bandwidth and other computer resources)
Software designed to use asynchronous sockets and programming, rather than a hardware thread per request from a pool. (ie. IIS, Node.js, Nginx... webserver [but not Apache] with async designed application software)
Good performance/dollar CPU / Ram. Today, arbitrarily, let's say i7 (4 core) with 8GB of RAM.
A good firewall/router to match.
No virtual limit/governor - ie. Linux somaxconn, IIS web.config...
No dependency on other slower hardware - no reading from harddisk, because it would be the lowest common denominator and bottleneck, not network IO.
Detailed Answer
Synchronous thread-bound designs tend to be the worst performing relative to Asynchronous IO implementations.
WhatsApp can handle a million WITH traffic on a single Unix flavoured OS machine - https://blog.whatsapp.com/index.php/2012/01/1-million-is-so-2011/.
And finally, this one, http://highscalability.com/blog/2013/5/13/the-secret-to-10-million-concurrent-connections-the-kernel-i.html, goes into a lot of detail, exploring how even 10 million could be achieved. Servers often have hardware TCP offload engines, ASICs designed for this specific role more efficiently than a general purpose CPU.
Good software design choices
Asynchronous IO design will differ across Operating Systems and Programming platforms. Node.js was designed with asynchronous in mind. You should use Promises at least, and when ECMAScript 7 comes along, async/await. C#/.Net already has full asynchronous support like node.js. Whatever the OS and platform, asynchronous should be expected to perform very well. And whatever language you choose, look for the keyword "asynchronous", most modern languages will have some support, even if it's an add-on of some sort.
To WebFarm?
Whatever the limit is for your particular situation, yes a web-farm is one good solution to scaling. There are many architectures for achieving this. One is using a load balancer (hosting providers can offer these, but even these have a limit, along with bandwidth ceiling), but I don't favour this option. For Single Page Applications with long-running connections, I prefer to instead have an open list of servers which the client application will choose from randomly at startup and reuse over the lifetime of the application. This removes the single point of failure (load balancer) and enables scaling through multiple data centres and therefore much more bandwidth.
Busting a myth - 64K ports
To address the question component regarding "64,000", this is a misconception. A server can connect to many more than 65535 clients. See https://networkengineering.stackexchange.com/questions/48283/is-a-tcp-server-limited-to-65535-clients/48284
By the way, Http.sys on Windows permits multiple applications to share the same server port under the HTTP URL schema. They each register a separate domain binding, but there is ultimately a single server application proxying the requests to the correct applications.
Update 2019-05-30
Here is an up to date comparison of the fastest HTTP libraries - https://www.techempower.com/benchmarks/#section=data-r16&hw=ph&test=plaintext
Test date: 2018-06-06
Hardware used: Dell R440 Xeon Gold + 10 GbE
The leader has ~7M plaintext reponses per second (responses not connections)
The second one Fasthttp for golang advertises 1.5M concurrent connections - see https://github.com/valyala/fasthttp
The leading languages are Rust, Go, C++, Java, C, and even C# ranks at 11 (6.9M per second). Scala and Clojure rank further down. Python ranks at 29th at 2.7M per second.
At the bottom of the list, I note laravel and cakephp, rails, aspnet-mono-ngx, symfony, zend. All below 10k per second. Note, most of these frameworks are build for dynamic pages and quite old, there may be newer variants that feature higher up in the list.
Remember this is HTTP plaintext, not for the Websocket specialty: many people coming here will likely be interested in concurrent connections for websocket.
This question is a fairly difficult one. There is no real software limitation on the number of active connections a machine can have, though some OS's are more limited than others. The problem becomes one of resources. For example, let's say a single machine wants to support 64,000 simultaneous connections. If the server uses 1MB of RAM per connection, it would need 64GB of RAM. If each client needs to read a file, the disk or storage array access load becomes much larger than those devices can handle. If a server needs to fork one process per connection then the OS will spend the majority of its time context switching or starving processes for CPU time.
The C10K problem page has a very good discussion of this issue.
To add my two cents to the conversation a process can have simultaneously open a number of sockets connected equal to this number (in Linux type sytems) /proc/sys/net/core/somaxconn
cat /proc/sys/net/core/somaxconn
This number can be modified on the fly (only by root user of course)
echo 1024 > /proc/sys/net/core/somaxconn
But entirely depends on the server process, the hardware of the machine and the network, the real number of sockets that can be connected before crashing the system
It looks like the answer is at least 12 million if you have a beefy server, your server software is optimized for it, you have enough clients. If you test from one client to one server, the number of port numbers on the client will be one of the obvious resource limits (Each TCP connection is defined by the unique combination of IP and port number at the source and destination).
(You need to run multiple clients as otherwise you hit the 64K limit on port numbers first)
When it comes down to it, this is a classic example of the witticism that "the difference between theory and practise is much larger in practise than in theory" - in practise achieving the higher numbers seems to be a cycle of a. propose specific configuration/architecture/code changes, b. test it till you hit a limit, c. Have I finished? If not then d. work out what was the limiting factor, e. go back to step a (rinse and repeat).
Here is an example with 2 million TCP connections onto a beefy box (128GB RAM and 40 cores) running Phoenix http://www.phoenixframework.org/blog/the-road-to-2-million-websocket-connections - they ended up needing 50 or so reasonably significant servers just to provide the client load (their initial smaller clients maxed out to early, eg "maxed our 4core/15gb box # 450k clients").
Here is another reference for go this time at 10 million: http://goroutines.com/10m.
This appears to be java based and 12 million connections: https://mrotaru.wordpress.com/2013/06/20/12-million-concurrent-connections-with-migratorydata-websocket-server/
Note that HTTP doesn't typically keep TCP connections open for any longer than it takes to transmit the page to the client; and it usually takes much more time for the user to read a web page than it takes to download the page... while the user is viewing the page, he adds no load to the server at all.
So the number of people that can be simultaneously viewing your web site is much larger than the number of TCP connections that it can simultaneously serve.
in case of the IPv4 protocol, the server with one IP address that listens on one port only can handle 2^32 IP addresses x 2^16 ports so 2^48 unique sockets. If you speak about a server as a physical machine, and you are able to utilize all 2^16 ports, then there could be maximum of 2^48 x 2^16 = 2^64 unique TCP/IP sockets for one IP address. Please note that some ports are reserved for the OS, so this number will be lower. To sum up:
1 IP and 1 port --> 2^48 sockets
1 IP and all ports --> 2^64 sockets
all unique IPv4 sockets in the universe --> 2^96 sockets
There are two different discussions here: One is how many people can connect to your server. This one has been answered adequately by others, so I won't go into that.
Other is how many ports yours server can listen on? I believe this is where the 64K number came from. Actually, TCP protocol uses a 16-bit identifier for a port, which translates to 65536 (a bit more than 64K). This means that you can have that many different "listeners" on the server per IP Address.
I think that the number of concurrent socket connections one web server can handle largely depends on the amount of resources each connection consumes and the amount of total resource available on the server barring any other web server resource limiting configuration.
To illustrate, if every socket connection consumed 1MB of server resource and the server has 16GB of RAM available (theoretically) this would mean it would only be able to handle (16GB / 1MB) concurrent connections. I think it's as simple as that... REALLY!
So regardless of how the web server handles connections, every connection will ultimately consume some resource.