How many client per server

Clients that use persistent connections SHOULD limit the number of simultaneous connections that they maintain to a given server. These guidelines are intended to improve HTTP response times and avoid congestion.

The latter technique can exacerbate network congestion. If the body is being sent using a "chunked" encoding section 3. The purpose of the Continue status see section In some cases, it might either be inappropriate or highly inefficient for the client to send the body if the server will reject the message without looking at the body. Because of the presence of older implementations, the protocol allows ambiguous situations in which a client may send "Expect: continue" without receiving either a Expectation Failed status or a Continue status.

Therefore, when a client sends this header field to an origin server possibly via a proxy from which it has never seen a Continue status, the client SHOULD NOT wait for an indefinite period before sending the request body. If the client does retry this request, it MAY use the following "binary exponential backoff" algorithm to be assured of obtaining a reliable response:.

When a client connects to a server, it picks a random, unused high-order source port. First, let's use netstat to see what is happening on this computer. We will use port instead of 80 because a whole bunch of stuff is happening on port 80 as it is a common port, but functionally it does not make a difference. The local address is 0. An easy mistake to make is to listen on address So this is not a connection, this just means that a process requested to bind to port IP, and that process is responsible for handling all connections to that port.

This hints to the limitation that there can only be one process per computer listening on a port there are ways to get around that using multiplexing, but this is a much more complicated topic.

If a web-server is listening on port 80, it cannot share that port with other web-servers. Doing netstat again while this is happening displays the following:.

So there is never confusion between the IP addresses. Normally, for every connecting client the server forks a child process that communicates with the client TCP. The parent server hands off to the child process an established socket that communicates back to the client.

When you send the data to a socket from your child server, the TCP stack in the OS creates a packet going back to the client and sets the "from port" to Multiple clients can connect to the same port say 80 on the server because on the server side, after creating a socket and binding setting local IP and port listen is called on the socket which tells the OS to accept incoming connections.

When a client tries to connect to server on port 80, the accept call is invoked on the server socket. This creates a new socket for the client trying to connect and similarly new sockets will be created for subsequent clients using same port Stack Overflow for Teams — Collaborate and share knowledge with a private group.

Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. How do multiple clients connect simultaneously to one port, say 80, on a server? Asked 11 years, 3 months ago. Active 1 year, 11 months ago. Viewed k times. Improve this question. Add a comment. Active Oldest Votes. Improve this answer. Borealid Borealid If you connect to the same web server twice from your client, the two connections will have the same destination port too.

Only the source port is different. From the perspective of the server, the connections have different source ports. The source port that the original computer set, and the external source port on the router. The latter is chosen by the router, not the hosts. Since, internally, each host has a different IP address, there is no collision. With both HTTP protocols, setting http-reuse to always provides much better results. In this scenario, I instructed hey to keep the connections persistent for all 50 users.

This is the best case scenario! Re-using already established connections allows you to get better performance from the network layer, hence the benefits for the application layer.

To manage the pools of connections, HAProxy provides multiple parameters that can be set on a server line in a backend section:. Since HAProxy 2. It provides live information about the number of connections and their state per server for each backend, as well as the number of idle connections per thread, and more.

The information you get from this command will help you when setting the parameters seen above. It can be used to protect servers against traffic spikes by routing requests to other servers or by queueing requests within HAProxy.

At that point in time, one connection was equivalent to one request being processed by the server. So a maxconn of meant that requests at most could be processed in parallel by the server.

This means that with a maxconn of , a server could have:. While HTTP 1. HAProxy leverages persistent connections on the server side to support connection pools, wherein idle connections to backend servers can be reused among clients.

You can control the behavior of the connection pool by setting the http-reuse directive in a backend section. Benchmarks indicate that setting it to always is typically best. Fine tune it more with the pool-low-conn , pool-max-conn , and pool-purse-delay parameters on a server line. Finally, you learned that the maxconn setting has evolved over time.

The setup is summarized by the diagram in Figure We can improve on the previous design further by using STM. With STM, we can avoid the broadcast channel by storing the current factor in a single shared TVar :. This design needs two threads per client. The overall structure is depicted in Figure First, the main function, which has a couple of changes compared with the previous version:. Here, we create the TVar that contains the current factor and initialize its value to 2.

The talk function now takes the factor TVar as an additional argument. The talk function sets up the threads to handle the new client connection:. Creates the new TChan that will carry the messages from the receive thread. Creates the server and receive threads.

The server and receive functions will be defined shortly. Note that we are using race from Symmetric Concurrency Combinators. If either thread fails for any reason, then we want to cancel the other thread and raise the exception, which will cause the client connection to be cleanly shut down. Furthermore, race gives us the ability to terminate one thread by simply returning from the other.

The receive function repeatedly reads a line from the Handle and writes it to the TChan :. Next, we have the server thread, where most of the application logic resides. The overall structure is as follows: loop waits for the next event, which is either a change in the factor or a command from the client, and calls newfactor or command , respectively.

The newfactor and command functions take whatever action is necessary and then call back to loop to process the next event. The loop function itself is implemented as an STM transaction that returns an IO action , which is then performed. This is a common pattern in STM. If the two are different, indicating that the factor has been changed, then we call the newfactor function.

If the factor has not been changed, we read from the TChan. This may retry if the channel is empty, but note that in the event of a retry , the transaction will be re-executed if either the factor TVar or the TChan changes.

You can think of this transaction as a composition of two blocking operations: waiting for the factor TVar to change, and reading from the TChan. But we can code it without orElse thanks to the following equality:. Having read a line of input from the TChan , we call command to act upon it.

The newfactor function reports the change in factor to the client and continues with loop. If the client said end , then we terminate the connection by simply returning, instead of recursively calling loop. As mentioned earlier, this will cause race to terminate the receive thread. If the client requests a change in factor, then we update the global factor value and call loop , passing the old factor value. Thus the transaction will immediately notice the change in factor and report it, giving the client confirmation that the factor was changed.

Try this server yourself by compiling and running the server2. Start up a few clients with the nc program or another suitable telnet-style application and check that it is working as expected.

Test the error handling: what happens when you close the client connection without sending the end command, or if you send a non-number? You might want to add some additional debugging output to various parts of the program in order to track more clearly what is happening. Continuing on from the simple server examples in the previous sections, we now consider a more realistic example: a network chat server.

A chat server enables multiple clients to connect and type messages to one another interactively. Real chat servers e. For simplicity, we will be building a chat server that has a single channel, whereby every message is seen by every client. Each line received from the client is interpreted as a command, which is one of the following :. The basic architecture will be similar. We need a receive thread to forward the network input into a TChan and a server thread to wait for the different kinds of events and act upon them.

Compared to the previous example, though, we have a lot more shared state. A client needs to be able to send messages to any other client, so the set of clients and their corresponding TChan s must be shared.

This implies some synchronized, shared state for each client to indicate whether it has been kicked. A server thread can then check that it has not already been kicked itself before kicking another client. To inform the victim that it has been kicked, we could send a message to its TChan , but because we are using STM, we might as well just watch the global state for changes as we did in the factor example in the previous section.

There is input from the client over the network and also messages from other clients to be sent back to this client. We could use separate TChan s for the different kinds of events, but it is slightly better to use just one; the ordering on events is retained, which makes things more predictable for the client.

So the design we have so far is a TVar to indicate whether the client has been kicked and a TChan to carry both network input and events from other clients. Now that we have established the main architectural design, we can fill in the details. In the previous examples, we passed around the various pieces of state explicitly, but now that things are more complicated, it will help to separate the state into the global server state and the per-client state.

The per-client state is defined as follows:.