We are trying to optimize our ASP.NET MVC app and get a big time difference between our server side logs and client side delay.
When refresh the page in Chrome in Timeline it shows 4.47s:
As I understand from the picture, the time for server side code execution should be 3.34s, but in our server logs we have the following:
Begin Request 15:41:52.421
End Request 15:41:53.218
Pre Send Request Headers 15:41:53.218
Pre Send Request Content 15:41:53.218
So, according to server side logs code execution took only 797ms in total.
It does not happen all the time and very often the Chrome timeline shows times very close to server logs. But sometimes we have this couple of seconds delay.
Where could this delay come from?
There is lot of stuff that can affect the time sporadically to such an extent, even though addition of almost three seconds is sort of excessive for this scenario. Since you don't mention much about how is your network set up, what operating system u use etc,
I'll try to sum up a list of what comes to my mind when dealing with this sort of a delay, sorted by probability.
The main problem here is the Waiting part of the total time there you should concentrate your detective talent.
Please note that the answer is very general since the question says virtually nothing about configuration of the server, client computer or the network (if any) between them. Since you say the delay is not present all the time, there are one or more moving targets you need to aim at.
Antivirus
If you have an internet shield or similarly named component, it is not uncommon that the antivirus can seemingly randomly delay some connections while leaving other virtually untouched. For the browser this is transparent (it's just a delay, whatever may have caused it), hence the Waiting.
Network issue
Especially if you are connected through a wireless network or poorly configured wired network, a few seconds delay may occur even though the label on the network device says TurboSpeedTM.
Server side issue
Server may be overloaded with previous requests in a manner not covered by your in-application timer, since there are many steps the server performs before and after your script is executed.
Client OS issue
Just like the antivirus, the OS can delay your packets virtually randomly for various reasons.
When hunting down such issue, I would recommend trying to perform the query on the server itself and compare resulting times, try as may combinations of network setup and operation systems as possible, prefer well planned network environments to those with many unknown or external factors (read wireless) and make use of some packet sniffing software (like wireshark) to check whether the browser doesn't lie. And that would be just the start of it :)
Related
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.
I'm not sure if this is the right place to ask this, but I'll do it anyway.
I have developed an uploader for the Umbraco CMS that lets people upload a queue of files in one go. This uses some simple flash app that just calls a .NET ashx to upload the files one at a time. When one is done, the next one starts.
Recently I've had a user hit a problem where 1 or 2 uploads will go up fine, but then the rest fail. This happens for himself and a client of his. After some debugging, he thinks he's found the problem, but it seems weird so was wondering if anyone else has had this problem?
Both him and his client are on a fibre optic broadband connection so have got really fast upload speeds. When it was tested on a lesser speed broadband connection, all the files were uploaded no problem. According to one of his developer friends, apparently they had come across it before and had to put a slight delay in the upload script to make it work.
Does this sound possible? Had anyone else hit this problem? Is there a known workaround to prevent the uploads from failing?
I have not struck this precise problem before, but I have done a lot of diagnosis of DSL and broadband troubleshooting before, so will do my best to answer this.
There are 2 possible causes for this particular symptom, both generally outside of your network control (I would have thought).
1) Packet loss
Of course where some links receive a very high volume of traffic then they can chose to just dump a lot of data (eg all that is over that link maximum set size), but TCP/IP should be controlling that, and also expecting that sort of thing to drop from time to time, so this seems less likely.
2) The receiving server
May have some HTTP bottlenecks into that server or even the receiving server CPU / RAM etc, may be at capacity.
From a troubleshooting perspective, even if these symptoms shouldn't (in theory) exist, the fact that they do, and you have a specific
Next steps if you really need to understand how it is all working might be to get some sort of packet sniffer (like WireShark) to try to work out at a packet level what exactly is happening.
Also Socket programming can often program directly to the TCP/IP sockets, so you would be processing at the lower network layers, and seeing the responses and timeouts etc.
Also if you control the receiving server, then you can do the same from that end, or at least review the error logs to see what is getting thrown up as a problem.
A really basic method could be to send a pathping to the receiving server if that is possible, and that might highlight slow nodes getting the server, or packet loss between your local machine and the end server.
The upshot? Put in a slow down function in the upload code, and that should at least make the code work.
Get in touch if you need any analysis of the WireShark stuff.
I have run into a similar problem with an MVC2 website using Flash uploader and Firefox. The servers were load balanced with a Big-IP load balancer. What we found out in debugging this is that Flash, in Firefox, did not send the session ID on continuation requests and the load balancer would send continuation requests off to another server. Because the user had no session on the new server, the request failed.
If a file could be sent in one chunk, it would upload fine. If it required a second chunk, it failed. Because of this the upload would fail after an undetermined number of files being uploaded.
To fix it, I wrote a Silverlight uploader.
I'm writing a multiplayer Flash game, and the server is written in Python and it updates 25 times a second. Every update, if a player is moving, the server sends out TCP messages containing the new positions of that player. Running locally, everything was lovely, but I've recently pushed the code to a higher-spec deployment server (with a 100Mbps pipe connection) to test how it plays.
I'm glad I did, because what I am noticing is that these update messages are bunching up during sending and they arrive in six's. Testing locally, the messages were arriving at 1/25th of a second intervals, and so player movement was very smooth, now it really isn't.
If you had this same issue, what are the things you would look at, experiment with, in order to find a solution?
You can try disabling Nagle's algorithm to make sure segments are sent straight away. However, given your requirements, I wonder if UDP isn't a better match.
Even on big-time sites such as Google, I sometimes make a request and the browser just sits there. The hourglass will turn indefinitely until I click again, after which I get a response instantly. So, the response or request is simply getting lost on the internet.
As a developer of ASP.NET web applications, is there any way for me to mitigate this problem, so that users of the sites I develop do not experience this issue? If there is, it seems like Google would do it. Still, I'm hopeful there is a solution.
Edit: I can verify, for our web applications, that every request actually reaching the server is served in a few seconds even in the absolute worst case (e.g. a complex report). I have an email notification sent out if a server ever takes more than 4 seconds to process a request, or if it fails to process a request, and have not received that email in 30 days.
It's possible that a request made from the client took a particular path which happened to not work at that particular moment. These are unavoidable - they're simply a result of the internet, which is built upon unstable components and which TCP manages to ensure a certain kind of guarantee for.
Like someone else said - make sure when a request hits your server, you'll be ready to reply. Everything else is out of your hands.
They get lost because the internet is a big place and sometimes packets get dropped or servers get overloaded. To give your users the best experience make sure you have plenty of hardware, robust software, and a very good network connection.
You cannot control the pipe from the client all the way to your server. There could be network connectivity issues anywhere along the pipeline, including from your PC to your ISP's router which is a likely place to look first.
The bottom line is if you are having issues bringing Google.com up in your browser then you are guaranteed to have the same issue with your own web application at least as often.
That's not to say an ASP application cannot generate the same sort of downtime experience completely on it's own... Test often and code defensively are the key phrases to keep in mind.
Let's not forget browser bugs. They aren't nearly perfect applications themselves...
This problem/situation isn't only ASP related, but it covers the whole concept of keeping your apps up and its called informally the "5 nines" or "99.999% availability".
The wikipedia article is here
If you lookup the 5 nines you'll find tons of useful information, which you can apply as needed to your apps.
All,
so, I inventedmade up a simple protocol that I want to use for a client to talk to a server. It's the typical (I think) three-phase layout:
Connection Establishment (will eventually include capability negotiation)
Actual Data Exchange - packets are happily travelling to and fro', get interpreted by the respective receiver which acts on them accordingly
Connection Teardown - one side says "don't wanna no more', other side says 'so be it' (will eventually allow the other side to send some data until it is done instead of simply closing the conversation)
The framework is a simple setup: The server does java.net.ServerSocket.accept() and starts a thread to handle the incoming connection by a client, which creates a java.net.Socket() to the host/port where the server is waiting. Both sides use the java.io.InputStream and java.io.OutputStream and spew data at each other, assembling outgoing and parsing incoming messages. Fine, so far.
So far, the protocol is hard-coded. Connection Establishment and Teardown are pretty much ok, while the Data Exchange part - which I want to be full-duplex - is pretty much a mess.
So, thinks me, let's do this the good way and set up a state machine using, surprise, the design pattern of the same name. I'm pretty clear about what the states should be for the server and the client, respectively, and what kinds of events should happen for a transition to take place, and what actions should be undertaken when a transition does happen. That looks good - on paper, that is. In practice, I've stubmled over a couple of questions that I can't solve on paper.
In particular, the inputs of the state machine are ... a little diverse. How could I possibly be able to write data, read data and check the connection (it might have closed or may be broken) at the same time? Also, the 1st and 3rd phase should get timers to avoid potentially infinite waiting times for answers.
So, I'd be grateful for any help that bridges my gap between the theory state machine and the code state machine.
BTW, I can read C/C++/C# too - no need to translate to Java (which is what I'm using).
The state for your machine needs to be stored per "Connection"
Each client connecting might be in a different state. So if you had an object tracking your state, you would have an instance of that object for every connection.
I actually wrote a little library that abstracts out just about everything from the state machine if you're interested. There is some test code in there as well that should show you how to work it. State Machine Code
It does some stuff you might forget, like ensuring that state transitions that are not "valid" are actually an error rather than maybe being missed, and logging state transitions is free.
ps. (Anyone) If you look at it and don't like it--please let me know why. I'd like to make it usable for anyone.