When we talk about capacity of a web application, we often mention the concurrent requests it could handle.
As my another question discussed, Ethernet use TDM (Time Division Multiplexing) and no 2 signals could pass along the wire simultaneously. So if the web server is connected to the outside world through a Ethernet connection, there'll be literally no concurrent requests at all. All requests will come in one after another.
But if the web server is connected to the outside world through something like a wireless network card, I believe the multiple signals could arrive at the same time through the electro-magnetic wave. Only in this situation, there are real concurrent requests to talk about.
Am I right on this?
Thanks.
Instead of sending one request, waiting for the response, then doing something different like sending another request, we can use the time we're usually waiting for the server to respond to send a second request to another (or the same) server.
By default each Cloud Run container instance can receive up to 80 requests at the same time; you can increase this to a maximum of 1000. Although you should use the default value, if needed you can lower the maximum concurrency. For example, if your code cannot process parallel requests, set concurrency to 1 .
A warning that you have exceeded your concurrency limit suggests that your login details are already in use - you may be logged in via another browser, computer and/or device. Tip: Ensure that you use the 'log out' button to immediately terminate your login session.
I imagine "concurrent requests" for a web application doesn't get down to the link level. It's more a question of the processing of a request by the application and how many requests arrive during that processing.
For example, if a request takes on average 2 seconds to fulfill (from receiving it at the web server to processing it through the application to sending back the response) then it could need to handle a lot of concurrent requests if it gets many requests per second.
The requests need to overlap and be handled concurrently, otherwise the queue of requests would just fill up indefinitely. This may seem like common sense, but for a lot of web applications it's a real concern because the flood of requests can bog down a resource for the application, such as a database. Thus, if the application has poor database interactions (overly complex procedures, poor indexing/optimization, a slow link to a database shared by many other applications, etc.) then that creates a bottleneck which limits the number of concurrent requests the application can handle, even though the application itself should be able to handle them.
.Imagining a http server listening at port 80, what happens is:
a client connects to the server to request some page; it is connecting from some origin IP address, using some origin local port.
the OS (actually the network stack) looks at the incoming request's destination IP (since the server may have more than one NIC) and destination port (80) and verifies that some application is registered to handle data on that port (the http server). The combination of 4 numbers (origin IP, origin port, destination IP, port 80) uniquely identifies a connection. If such a connection does not exists yet, a new one is added to the network stack's internal table and a connection request is passed on to the http server's listening socket. From now on the network stack just passes on data for that connection to the application.
Multiple client can be sending requests, for each one the above happens. So from the network perspective, all happens serially, since data arrives one packet at a time.
From the software perspective, the http server is listening to incoming requests. The number of requests it can have queued before the clients start getting errors is determined by the programmer based on the hardware capacity (this is the first bit of concurrency: there can be multiple requests waiting to be processed). For each one it will create a new socket (as fast as possible in order to continue emptying the request queue) and let the actual processing of the request be done by another part of the application (different threads). These processing routines will (ideally) spend most of their time waiting for data to arrive and react (ideally) quickly to it.
Since usually the processing of data is many times faster than the network I/O, the server can handle many requests while processing network traffic, even if the hardware consist of only one processor. Multiple processors increase this capability. So from the software perspective all happens concurrently.
How the actual processing of the data is implemented is where the key to performance lies (you want it to be as efficient as possible). Several possibilities exist (async socket operations as provided by the Socket class, threadpool, unique threads, the new parallel features from .NET 4).
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