I have been facing the below exception in my application while calling another service. Upon investigation I was told that the waiting time of the requests (waiting to find an open connection), sitting in threadpool queue is reaching the max wait time and hence they are being rejected. As an action I got to tune in the total number of max connections(http.maxTotalConnections) that can be served by my application concurrently to avoid the long wait time for requests.
Our current http.maxTotalConnections value is set to 100.
Below is the error:
exception=reactor.netty.internal.shaded.reactor.pool.PoolAcquireTimeoutException:
Pool#acquire(Duration) has been pending for more than the configured
timeout of 50ms
I have below questions:
How does one decide the right value for http.maxTotalConnections ?
How do we decide the right balance between the apt total connections vs to a point
where it instead starts affecting the application performance.
Is there a time out for a http request which is kept in the IIS request queue?
If there is a time out, what will happens if a request stayed longer time in the IIS request queue ?
a - Does it discards or execute by the server when threads available?
Good question, I'm surprised it's infinite by default, as a surge would overload IIS with requests (up to the limit, which is 3000 by default).
If you have a well tuned application, I would say 1-3 seconds is a good range. Users typically don't wait longer than a second anyway, they'll hit refresh. In my case I have a dinosaur with all kinds of clunky reports so have set to 30 seconds.
I think I know what is happening here, but would appreciate a confirmation and/or reading material that can turn that "think" into just "know", actual questions at the end of post in Tl,DR section:
Scenario:
I am in the middle of testing my MVC application for a case where one of the internal components is stalling (timeouts on connections to our database).
On one of my web pages there is a Jquery datatable which queries for an update via ajax every half a second - my current task is to display correct error if that data requests times out. So to test, I made a stored procedure that asks DB server to wait 3 seconds before responding, which is longer than the configured timeout settings - so this guarantees a time out exception for me to trap.
I am testing in Chrome browser, one client. Application is being debugged in VS2013 IIS Express
Problem:
Did not expect the following symptoms to show up when my purposeful slow down is activated:
1) After launching the page with the rigged datatable, application slowed down in handling of all requests from the client browser - there are 3 other components that send ajax update requests parallel to the one I purposefully broke, and this same slow down also applied to any actions I made in the web application that would generate a request (like navigating to other pages). The browser's debugger showed the requests were being sent on time, but the corresponding break points on the server side were getting hit much later (delays of over 10 seconds to even a several minutes)
2) My server kept processing requests even after I close the tab with the application. I closed the browser, I made sure that the chrome.exe process is terminated, but breakpoints on various Controller actions were still getting hit for 20 minutes afterward - mostly on the actions that were "triggered" by automatically looping ajax requests from several pages I was trying to visit during my tests. Also breakpoints were hit on main pages I was trying to navigate to. On second test I used RawCap monitor the loopback interface to make sure that there was nothing actually making requests still running in the background.
Theory I would like confirmed or denied with an alternate explanation:
So the above scenario was making looped requests at a frequency that the server couldn't handle - the client datatable loop was sending them every .5 seconds, and each one would take at least 3 seconds to generate the timeout. And obviously somewhere in IIS express there has to be a limit of how many concurrent requests it is able to handle...
What was a surprise for me was that I sort of assumed that if that limit (which I also assumed to exist) was reached, then requests would be denied - instead it appears they were queued for an absolutely useless amount of time to be processed later - I mean, under what scenario would it be useful to process a queued web request half an hour later?
So my questions so far are these:
Tl,DR questions:
Does IIS Express (that comes with Visual Studio 2013) have a concurrent connection limit?
If yes :
{
Is this limit configurable somewhere, and if yes, where?
How does IIS express handle situations where that limit is reached - is that handling also configurable somewhere? ( i mean like queueing vs. immediate error like server is busy)
}
If no:
{
How does the server handle scenarios when requests are coming faster than they can be processed and can that handling be configured anywhere?
}
Here - http://www.iis.net/learn/install/installing-iis-7/iis-features-and-vista-editions
I found that IIS7 at least allowed unlimited number of silmulatneous connections, but how does that actually work if the server is just not fast enough to process all requests? Can a limit be configured anywhere, as well as handling of that limit being reached?
Would appreciate any links to online reading material on the above.
First, here's a brief web server 101. Production-class web servers are multithreaded, and roughly one thread = one request. You'll typically see some sort of setting for your web server called its "max requests", and this, again, roughly corresponds to how many threads it can spawn. Each thread has overhead in terms of CPU and RAM, so there's a very real upward limit to how many a web server can spawn given the resources the machine it's running on has.
When a web server reaches this limit, it does not start denying requests, but rather queues requests to handled once threads free up. For example, if a web server has a max requests of 1000 (typical) and it suddenly gets bombarded with 1500 requests. The first 1000 will be handled immediately and the further 500 will be queued until some of the initial requests have been responded to, freeing up threads and allowing some of the queued requests to be processed.
A related topic area here is async, which in the context of a web application, allows threads to be returned to the "pool" when they're in a wait-state. For example, if you were talking to an API, there's a period of waiting, usually due to network latency, between sending the request and getting a response from the API. If you handled this asynchronously, then during that period, the thread could be returned to the pool to handle other requests (like those 500 queued up requests from the previous example). When the API finally responded, a thread would be returned to finish processing the request. Async allows the server to handle resources more efficiently by using threads that otherwise would be idle to handle new requests.
Then, there's the concept of client-server. In protocols like HTTP, the client makes a request and the server responds to that request. However, there's no persistent connection between the two. (This is somewhat untrue as of HTTP 1.1. Connections between the client and server are sometimes persisted, but this is only to allow faster future requests/responses, as the time it takes to initiate the connection is not a factor. However, there's no real persistent communication about the status of the client/server still in this scenario). The main point here is that if a client, like a web browser, sends a request to the server, and then the client is closed (such as closing the tab in the browser), that fact is not communicated to the server. All the server knows is that it received a request and must respond, and respond it will, even though there's technically nothing on the other end to receive it, any more. In other words, just because the browser tab has been closed, doesn't mean that the server will just stop processing the request and move on.
Then there's timeouts. Both clients and servers will have some timeout value they'll abide by. The distributed nature of the Internet (enabled by protocols like TCP/IP and HTTP), means that nodes in the network are assumed to be transient. There's no persistent connection (aside from the same note above) and network interruptions could occur between the client making a request and the server responding to the request. If the client/server did not plan for this, they could simply sit there forever waiting. However, these timeouts are can vary widely. A server will usually timeout in responding to a request within 30 seconds (though it could potentially be set indefinitely). Clients like web browsers tend to be a bit more forgiving, having timeouts of 2 minutes or longer in some cases. When the server hits its timeout, the request will be aborted. Depending on why the timeout occurred the client may receive various error responses. When the client times out, however, there's usually no notification to the server. That means that if the server's timeout is higher than the client's, the server will continue trying to respond, even though the client has already moved on. Closing a browser tab could be considered an immediate client timeout, but again, the server is none the wiser and keeps trying to do its job.
So, what all this boils down is this. First, when doing long-polling (which is what you're doing by submitting an AJAX request repeatedly per some interval of time), you need to build in a cancellation scheme. For example, if the last 5 requests have timed out, you should stop polling at least for some period of time. Even better would be to have the response of one AJAX request initiate the next. So, instead of using something like setInterval, you could use setTimeout and have the AJAX callback initiate it. That way, the requests only continue if the chain is unbroken. If one AJAX request fails, the polling stops immediately. However, in that scenario, you may need some fallback to re-initiate the request chain after some period of time. This prevents bombarding your already failing server endlessly with new requests. Also, there should always be some upward limit of the time polling should continue. If the user leaves the tab open for days, not using it, should you really keep polling the server for all that time?
On the server-side, you can use async with cancellation tokens. This does two things: 1) it gives your server a little more breathing room to handle more requests and 2) it provides a way to unwind the request if some portion of it should time out. More information about that can be found at: http://www.asp.net/mvc/overview/performance/using-asynchronous-methods-in-aspnet-mvc-4#CancelToken
In order to overcome the (apparent) 4 minute idle connection timeout on the Azure load balancer, it seems necessary to send some data down the pipe to the client every now and again to keep the connection from being regarded as idle.
Our controller is set up as an AsyncController, and it fires several different asynchronous methods on other objects, all of which are set up to use IO Completion Ports. Thus, we return from our method immediately, and when the completion packet is processed, IIS hooks back up to the original request so that we can render our View.
Is there any way to periodically send a few bytes down the wire in this case? In a "classic" situation, we could have executed the method and then just spun while we waited, sending data every few seconds until the asynchronous method was complete. But, in this situation, the IIS thread is freed to go do other business, and we hook back up to it in our completion callback. What to do? Is this possible?
While your particular case concerns Windows Azure specific (the 4 minute timeout of LBs), the question is pure IIS / ASP.NET workwise. Anyway, I don't think it is possible to send "ping-backs" to the client while in AsyncController/AsyncPage. This is the whole idea of the AsyncPages/Controllers. The IIS leaves the socket aside having the thread serving other requests. And gets back only when you got the OutstandingOperations to zero with AsyncManager.OutstandingOperations.Decrement(); Only then the control is given back to send final response to the client. And once you are the point of sending response, there is no turning back.
I would rather argue for the architectural approach of why you thing someone would wait 4 minutes to get a response (even with a good animated "please wait")? A lot of things may happen during this time. From browser crash, through internet disruption to total power loss/disruption at client. If you are doing real Azure, why not just send tasks for a Worker Role via a Queue (Azure Storage Queues or Service Bus Queues). The other option that stays in front of you for so long running tasks is to use SingalR and fully AJAXed solution. Where you communicate via SignalR the status of the long running operation.
UPDATE 1 due to comments
In addition to the approach suggested by #knightpfhor this can be also achieved with a Queues. Requestor creates a task with some Unique ID and sends it to "Task submission queue". Then "listens" (or polls at regular/irregular intervals) a "Task completion" queue for a message with given Task ID.
In any way I don't see a reason for keeping client connected for the whole duration of the long running task. There are number of ways to decouple such communication.
Is it safe to assume that when a user requests an .aspx page via HTTP, that ASP.NET creates at least 1 thread for it?
If so, how long does it last?
If 1000 people make the HTTP request to the same .aspx page, is there some recycling of threads involved, so it doesn't spawn different 1000 threads?
Each request is allocated a thread from the iis page pool. the idea is that this should be a short running process so that thread can be returned to the page pool for use by another request coming (page pool sizes are not huge, usually, like 50). So, if you have a long running request, it's important you make an async call to free the thread for some other request. then, on your long running requests completion, you will get another thread from the pool and finish up.
Bottom line, if 1000 people make requests at the same time and none of them finish, 50 or so will run and the other 950 will wait.