See the backlog parameter mentioned here:
All listen() methods can take a backlog parameter to specify the maximum length of the queue of pending connections. The actual length will be determined by the OS through sysctl settings such as tcp_max_syn_backlog and somaxconn on Linux. The default value of this parameter is 511 (not 512).
A more thorough explanation of this parameter would be appreciated. Some questions that come to mind after reading that description:
When is a connection 'pending' vs accepted?
How do you max out this backlog limitation?
What happens when the backlog parameter is exceeded, is an error returned?
This parameter will help you throttle connections to your server and, hence, protect it from "too many connections" issues.
Without this parameter, your server will (theoretically speaking and without OS limitations) accepts any number of connections. And since each connection consumes memory from your underlying machine, you will get to an "out of memory" situation when there are too many connections to your server and your server will stop running or, at least, will behaving in unexpected manner.
Receiving too many connections can be either normal (too many valid users trying to use your server) or abnormal (a result of a DOS/DDOS attack). In all cases, it is a good practice to put a limit to the number of connections your server can handle to ensure a high quality of service (connections above the limit will be "polity" declined).
Hopefully, Linux put some system-wide limitations that are tcp_max_syn_backlog and somaxconn. Even if you set the backlog parameter to a high value, Linux will review it to align it with the value set for these two system parameters. You can read more about this feature in this post.
We are running a Java-based trading application, and there are certain periods where we want to prioritize outgoing network traffic as much as possible for about 10 ms. Is there a way to temporarily buffer all incoming network traffic during a short time period, either on the network card or via a process or buffer on our Redhat Linux box?
The rationale behind this is that the incoming network traffic spikes during this same period, and the application processing this traffic is stealing CPU cycles from the process we are trying to prioritize. We do not have fine-grained control over the application treating the incoming network traffic.
We're on a 1 Gbps connection so a buffer of about 1 MB should be sufficient. We would prefer not dropping the incoming traffic and requesting retransmission as this would increase load on our network during quite busy periods.
Possible using Qos on the router, or using trickle to control your bandwidth by a sample configuration of :
/etc/trickled.conf.
see example in url.
I am not sure whether I understand your problem correctly. Your concern is sometimes you have priority to deal with output network traffic and at this time the incoming traffic will build up and finally might cause package drop or retransmission which you don't want. Therefore, you want to buffer your incoming traffic.
If my understanding is correct and your are using TCP, try to make your tcp buffer bigger.
http://kaivanov.blogspot.com/2010/09/linux-tcp-tuning.html and then Use netstat to check whether your change is effective.
Adrian, have you tried setting the priority of your outgoing communication process to be higher than that of the process receiving the incoming data? Using the nice command this can be achieved. Note that in Unix/Linux the lower the number the higher the priority.
Otherwise I am not sure this is possible without having a direct tie in between the two applications that are sending / receiving, allowing you to effectively ignore the incoming connections that are ready to read from until any data you have is sent out.
In my company we experienced a serious problem today: our production server went down. Most people accessing our software via a browser were unable to get a connection, however people who had already been using the software were able to continue using it. Even our hot standby server was unable to communicate with the production server, which it does using HTTP, not even going out to the broader internet. The whole time the server was accessible via ping and ssh, and in fact was quite underloaded - it's normally running at 5% CPU load and it was even lower at this time. We do almost no disk i/o.
A few days after the problem started we have a new variation: port 443 (HTTPS) is responding but port 80 stopped responding. The server load is very low. Immediately after restarting tomcat, port 80 started responding again.
We're using tomcat7, with maxThreads="200", and using maxConnections=10000. We serve all data out of main memory, so each HTTP request completes very quickly, but we have a large number of users doing very simple interactions (this is high school subject selection). But it seems very unlikely we would have 10,000 users all with their browser open on our page at the same time.
My question has several parts:
Is it likely that the "maxConnections" parameter is the cause of our woes?
Is there any reason not to set "maxConnections" to a ridiculously high value e.g. 100,000? (i.e. what's the cost of doing so?)
Does tomcat output a warning message anywhere once it hits the "maxConnections" message? (We didn't notice anything).
Is it possible there's an OS limit we're hitting? We're using CentOS 6.4 (Linux) and "ulimit -f" says "unlimited". (Do firewalls understand the concept of Tcp/Ip connections? Could there be a limit elsewhere?)
What happens when tomcat hits the "maxConnections" limit? Does it try to close down some inactive connections? If not, why not? I don't like the idea that our server can be held to ransom by people having their browsers on it, sending the keep-alive's to keep the connection open.
But the main question is, "How do we fix our server?"
More info as requested by Stefan and Sharpy:
Our clients communicate directly with this server
TCP connections were in some cases immediately refused and in other cases timed out
The problem is evident even connecting my browser to the server within the network, or with the hot standby server - also in the same network - unable to do database replication messages which normally happens over HTTP
IPTables - yes, IPTables6 - I don't think so. Anyway, there's nothing between my browser and the server when I test after noticing the problem.
More info:
It really looked like we had solved the problem when we realised we were using the default Tomcat7 setting of BIO, which has one thread per connection, and we had maxThreads=200. In fact 'netstat -an' showed about 297 connections, which matches 200 + queue of 100. So we changed this to NIO and restarted tomcat. Unfortunately the same problem occurred the following day. It's possible we misconfigured the server.xml.
The server.xml and extract from catalina.out is available here:
https://www.dropbox.com/sh/sxgd0fbzyvuldy7/AACZWoBKXNKfXjsSmkgkVgW_a?dl=0
More info:
I did a load test. I'm able to create 500 connections from my development laptop, and do an HTTP GET 3 times on each, without any problem. Unless my load test is invalid (the Java class is also in the above link).
It's hard to tell for sure without hands-on debugging but one of the first things I would check would be the file descriptor limit (that's ulimit -n). TCP connections consume file descriptors, and depending on which implementation is in use, nio connections that do polling using SelectableChannel may eat several file descriptors per open socket.
To check if this is the cause:
Find Tomcat PIDs using ps
Check the ulimit the process runs with: cat /proc/<PID>/limits | fgrep 'open files'
Check how many descriptors are actually in use: ls /proc/<PID>/fd | wc -l
If the number of used descriptors is significantly lower than the limit, something else is the cause of your problem. But if it is equal or very close to the limit, it's this limit which is causing issues. In this case you should increase the limit in /etc/security/limits.conf for the user with whose account Tomcat is running and restart the process from a newly opened shell, check using /proc/<PID>/limits if the new limit is actually used, and see if Tomcat's behavior is improved.
While I don't have a direct answer to solve your problem, I'd like to offer my methods to find what's wrong.
Intuitively there are 3 assumptions:
If your clients hold their connections and never release, it is quite possible your server hits the max connection limit even there is no communications.
The non-responding state can also be reached via various ways such as bugs in the server-side code.
The hardware conditions should not be ignored.
To locate the cause of this problem, you'd better try to replay the scenario in a testing environment. Perform more comprehensive tests and record more detailed logs, including but not limited:
Unit tests, esp. logic blocks using transactions, threading and synchronizations.
Stress-oriented tests. Try to simulate all the user behaviors you can come up with and their combinations and test them in a massive batch mode. (ref)
More specified Logging. Trace client behaviors and analysis what happened exactly before the server stopped responding.
Replace a server machine and see if it will still happen.
The short answer:
Use the NIO connector instead of the default BIO connector
Set "maxConnections" to something suitable e.g. 10,000
Encourage users to use HTTPS so that intermediate proxy servers can't turn 100 page requests into 100 tcp connections.
Check for threads hanging due to deadlock problems, e.g. with a stack dump (kill -3)
(If applicable and if you're not already doing this, write your client app to use the one connection for multiple page requests).
The long answer:
We were using the BIO connector instead of NIO connector. The difference between the two is that BIO is "one thread per connection" and NIO is "one thread can service many connections". So increasing "maxConnections" was irrelevant if we didn't also increase "maxThreads", which we didn't, because we didn't understand the BIO/NIO difference.
To change it to NIO, put this in the element in server.xml:
protocol="org.apache.coyote.http11.Http11NioProtocol"
From what I've read, there's no benefit to using BIO so I don't know why it's the default. We were only using it because it was the default and we assumed the default settings were reasonable and we didn't want to become experts in tomcat tuning to the extent that we now have.
HOWEVER: Even after making this change, we had a similar occurrence: on the same day, HTTPS became unresponsive even while HTTP was working, and then a little later the opposite occurred. Which was a bit depressing. We checked in 'catalina.out' that in fact the NIO connector was being used, and it was. So we began a long period of analysing 'netstat' and wireshark. We noticed some periods of high spikes in the number of connections - in one case up to 900 connections when the baseline was around 70. These spikes occurred when we synchronised our databases between the main production server and the "appliances" we install at each customer site (schools). The more we did the synchronisation, the more we caused outages, which caused us to do even more synchronisations in a downward spiral.
What seems to be happening is that the NSW Education Department proxy server splits our database synchronisation traffic into multiple connections so that 1000 page requests become 1000 connections, and furthermore they are not closed properly until the TCP 4 minute timeout. The proxy server was only able to do this because we were using HTTP. The reason they do this is presumably load balancing - they thought by splitting the page requests across their 4 servers, they'd get better load balancing. When we switched to HTTPS, they are unable to do this and are forced to use just one connection. So that particular problem is eliminated - we no longer see a burst in the number of connections.
People have suggested increasing "maxThreads". In fact this would have improved things but this is not the 'proper' solution - we had the default of 200, but at any given time, hardly any of these were doing anything, in fact hardly any of these were even allocated to page requests.
I think you need to debug the application using Apache JMeter for number of connection and use Jconsole or Zabbix to look for heap space or thread dump for tomcat server.
Nio Connector of Apache tomcat can have maximum connections of 10000 but I don't think thats a good idea to provide that much connection to one instance of tomcat better way to do this is to run multiple instance of tomcat.
In my view best way for Production server: To Run Apache http server in front and point your tomcat instance to that http server using AJP connector.
Hope this helps.
Are you absolutely sure you're not hitting the maxThreads limit? Have you tried changing it?
These days browsers limit simultaneous connections to a max of 4 per hostname/ip, so if you have 50 simultaneous browsers, you could easily hit that limit. Although hopefully your webapp responds quickly enough to handle this. Long polling has become popular these days (until websockets are more prevalent), so you may have 200 long polls.
Another cause could be if you use HTTP[S] for app-to-app communication (that is, no browser involved). Sometimes app writers are sloppy and create new connections for performing multiple tasks in parallel, causing TCP and HTTP overhead. Double check that you are not getting an inflood of requests. Log files can usually help you on this, or you can use wireshark to count the number of HTTP requests or HTTP[S] connections. If possible, modify your API to handle multiple API calls in one HTTP request.
Related to the last one, if you have many HTTP/1.1 requests going across one connection, and intermediate proxy may be splitting them into multiple connections for load balancing purposes. Sounds crazy I know, but I've seen it happen.
Lastly, some crawl bots ignore the crawl delay set in robots.txt. Again, log files and/or wireshark can help you determine this.
Overall, run more experiments with more changes. maxThreads, https, etc. before jumping to conclusions with maxConnections.
I need to send identical information to 100's of clients over the Internet. I currently maintain a list of client connections and iterate over the list. Obviously the longer the list gets the more latency there is toward the end of the list.
I have looked at multicasting. However unless I am missing something it is only good for LAN-based communications at present. It requires routers that support multicasting and most routers do not. There is no mechanism that I can see where one requests an available multicast address to avoid broadcasting to an address already in use.
So my questions are:
1) Am I missing something and can I use multicasting to accomplish this? (have tried without success)
2) Other than multicasting, is there a short cut to sending identical packets to many recipients?
I solved the problem by multicasting between threads in the server. Every client connection results in the creation of an object. These objects are stored in a queue. Each object has its own thread and joins the multicast group. When the server multicasts a string to the client objects the delay that arose from the list iteration no longer occurs.
Every now and then there is huge latency (nearly a second). I suspect that this is a JVM thing.
If you need high performing low latency IO, you shoud try http://nodejs.org/
You may be also interested in some cache http://memcached.org/
I am using Fedora 18 with the avahi command line tools (version 0.6.31)
I use avahi-resolve-host-name to discover the IP address of units on my subnet, for testing purposes during development. I monitor the request and response with Wireshark. After one successful request and response, no further requests show up on Wireshark, but the tool still returns an IP address. Is it possible the computer/avahi daemon/something else is 'caching' the result?
The Question: I wish to send out the request packet with EVERY CALL of avahi-resolve-host-name. Is this possible?
The Reason: I'm getting 'false positives' so to speak. I try to resolve 'test1.local', and I am getting a resulting IP, but the unit is no longer located at this IP. I want the request sent every time so I can avoid seeing units at incorrect IP addresses.
I see that I'm a bit late to answer your question but I'm going to leave a generic answer in case someone else stumbles upon this.
My answer is based on avahi-0.6.32_rc.
Is it possible the computer/avahi daemon/something else is 'caching' the result?
Yes, avahi-daemon is caching lookup results. While this doesn't seem to be explicitly listed in features, the avahi-daemon(8) manpage tips it:
The daemon [...] provides two IPC APIs for local programs to make use of the mDNS record cache the avahi-daemon maintains.
I wish to send out the request packet with EVERY CALL of avahi-resolve-host-name. Is this possible?
Yes, it is. The relevant option is cache-entries-max (from avahi-daemon.conf(5)):
cache-entries-max= Takes an unsigned integer specifying how many resource records are cached per interface. Bigger values allow mDNS work correctly in large LANs but also increase memory consumption.
To achieve the desired effect, you can simply set:
cache-entries-max=0
This will disable the caching entirely and force avahi-daemon to reissue the MDNS packets on every request, therefore making it possible for you to monitor them.
However, I should note here that this will also render avahi pretty much useless for normal use. While avahi-daemon will be issuing lookup packets, it will be unable to store the results and every call of avahi-resolve-host-name (as well as other command-line tools, nss-mdns, D-Bus API…) will fail.
I just stumbled upon this problem myself and found solution that doesn't require changing the config. It seems that simply killing the daemon (avahi-daemon --kill) flushes the cache. I'm on Ubuntu 18.04 and the daemon is restarted automatically. If on some other distro it isn't running after being killed, it can be restarted with avahi-daemon --daemonize.
Note that root is needed to kill avahi daemon, so this might not be the best option in some cases.