I have an application that is currently running on IIS 6.0 with one worker process (the default). I am trying to determine if creating a web garden will improve performance. I have read a bunch of articles that say that a web garden is not the right approach for everyone (since it duplicates resources, cache is not shared, etc). I could not find an article that had a clear rational for using a web garden (Microsoft's site provides three bullet points, but no specific examples can be found). My situation is as follows:
We have can have up to 40 concurrent users at a given time.
Our application performs a series of calcuations (on the magnitude of 1,000s of calculations) that can take up to 10 minutes to complete.
We have multipe database calls some of which can take upwards to 30 seconds to complete.
Will creating a web garden improve performance, or should I simply increase the number of threads in the current worker process? When would be an example of when you should use a web garden? If a thread in the current worker process is performing calcuations (running .net code) and/or calling the database, can other threads run at the same time (I assume yes).
Thanks.
Ryan
Personally, I have gone the route of using a web garden when my web application required frequent worker process recycles.
In this specific case we needed to recycle the worker process often because we were using CodeDOM to emit assemblies dynamically, which has a memory leak by definition as more assemblies are loaded.
Having a web garden helped avoid a delay in server response every time the worker process was recycled.
Related
Goal
Determine the cause of the sporadic lock ups of our web application running on IIS.
Problem
An application we are running on IIS sporadically locks up throughout the day. When it locks up it will lock up on all workers and on all load balanced instance.
Environment and Application
The application is running on 4 different Windows Server 2016 machines. The machines are load balanced using ha-proxy using a round robin load balancing scheme. The IIS application pools this website is hosted in are configured to have 4 workers each and the application it hosts is a 32-bit application. The IIS instances are not using a shared configuration file but the application pools for this application are all configured the same.
This application is the only application in the IIS application pool. The application is an ASP.NET web API and is using .NET 4.6.1. The application is not creating threads of its own.
Theory
My theory for why this is happening is that we have requests that are coming in that are taking ~5-30 minutes to complete. Every machine gets tied up servicing these requests so they look "locked up". The company rolled their own logging mechanism and from that I can tell we have requests that are taking ~5-30 minutes to complete. The team responsible for the application has cleaned up many of these but I am still seeing ~5 minute requests in the log.
I do not have access to the machines personally so our systems team has gotten memory dumps of the application when this happens. In the dumps I generally will see ~50 threads running and all of them are in our code. These threads will be all over our application and do not seem to be stopped on any common piece of code. When the application is running correctly the dumps have 3-4 threads running. Also I have looked at performance counters like the ASP.NET\Requests Queued but it never seems to have any requests queued. During these times the CPU, Memory, Disk and Network usage look normal. Using windbg none of the threads seem to have a high CPU time other than the finalizer thread which as far as I know should live the entire time.
Conclusion
I am looking for a means to prove or disprove my theory as to why we are locking up as well as any metrics or tools I should look at.
So this issue came down to our application using query in stitch on a table with 2,000,000 records in it to another table. Memory would become so fragmented that the Garbage Collector was spending more time trying to find places to put objects and moving them around than it was running our code. This is why it appeared that our application was still working and why their was no exceptions. Oddly IIS would time out the requests but would continue processing the threads.
I have an application which I want to expose as a web service (SaaS). The application is CPU intensive and is a multithreaded application which takes good amount of time for the execution(on an average 15-20secs). Since, I want to expose it as a SaaS and want to use existing cloud services available in the market like Amazon, Google App Engine etc. so that the cost involved and the work involved while scaling my service is not much. I have couple of questions in my mind like:
1.) Since the application is multithreaded and the number of threads invoked depends on the number of results thrown by the service(so basically number of threads is a dynamic entity). Right now I have a 6 core processor so I have kept the threadpool size to be 6 but since I am moving onto the cloud, how can I optimally use the cloud infrastructure?
2.) Do the cloud service providers(which?) give the option to select number of CPU cores required for each request (or something similar to serve my purpose)?
3.) What changes are needed in the code (related to the threads)?
4.) Any other specific area which I should give a sight for moving to the cloud?
In Amazon EC2 you are basically paying for different types of instances - you are free to pick one with only single core and one with sixteen. You get what you pay for.
how can I optimally use the cloud infrastructure?
Your approach is fine, if your task is CPU-intenstive, have a thread pool with the same number of threads as CPU cores/CPUs.
select number of CPU cores required for each request
No, at least not Amazon. You run your application on a given instance and that's all you get. You have to pick instance type in advance, but of course you are free to switch between them, add new, etc. at any time. The cloud!
In Google App Engine you can't create threads, so it's a no-option for you. See also: Why does Google App Engine support a single thread of execution only?
3.) What changes are needed in the code (related to the threads)?
None. It's a standard PC, after all.
4.) Any other specific area which I should give a sight for moving to the cloud?
Well, see above, some services are completely useless for you, like GAE. Make some research before you actually pay for something.
First - a little bit about my background: I have been programming for some time (10 years at this point) and am fairly competent when it comes to coding ideas up. I started working on web-application programming just over a year ago, and thankfully discovered nodeJS, which made web-app creation feel a lot more like traditional programming. Now, I have a node.js app that I've been developing for some time that is now running in production on the web. My main confusion stems from the fact that I am very new to the world of the web development, and don't really know what's important and what isn't when it comes to monitoring my application.
I am using a Joyent SmartMachine, and looking at the analytics options that they provide is a little overwhelming. There are so many different options and configurations, and I have no clue what purpose each analytic really serves. For the questions below, I'd appreciate any answer, whether it's specific to Joyent's Cloud Analytics or completely general.
QUESTION ONE
Right now, my main concern is to figure out how my application is utilizing the server that I have it running on. I want to know if my application has the right amount of resources allocated to it. Does the number of requests that it receives make the server it's on overkill, or does it warrant extra resources? What analytics are important to look at for a NodeJS app for that purpose? (using both MongoDB and Redis on separate servers if that makes a difference)
QUESTION TWO
What other statistics are generally really important to look at when managing a server that's in production? I'm used to programs that run once to do something specific (e.g. a raytracer that finishes running once it has computed an image), as opposed to web-apps which are continuously running and interacting with many clients. I'm sure there are many things that are obvious to long-time server administrators that aren't to newbies like me.
QUESTION THREE
What's important to look at when dealing with NodeJS specifically? What are statistics/analytics that become particularly critical when dealing with the single-threaded event loop of NodeJS versus more standard server systems?
I have other questions about how databases play into the equation, but I think this is enough for now...
We have been running node.js in production nearly an year starting from 0.4 and currenty 0.8 series. Web app is express 2 and 3 based with mongo, redis and memcached.
Few facts.
node can not handle large v8 heap, when it grows over 200mb you will start seeing increased cpu usage
node always seem to leak memory, or at least grow large heap size without actually using it. I suspect memory fragmentation, as v8 profiling or valgrind shows no leaks in js space nor resident heap. Early 0.8 was awful in this respect, rss could be 1GB with 50MB heap.
hanging requests are hard to track. We wrote our middleware to monitor these especially as our app is long poll based
My suggestions.
use multiple instances per machine, at least 1 per cpu. Balance with haproxy, nginx or such with session affinity
write midleware to report hanged connections, ie ones that code never responded or latency was over threshold
restart instances often, at least weekly
write poller that prints out memory stats with process module one per minute
Use supervisord and fabric for easy process management
Monitor cpu, reported memory stats and restart on threshold
Whichever the type of web app, NodeJS or otherwise, load testing will answer whether your application has the right amount of server resources. A good website I recently found for this is Load Impact.
The real question to answer is WHEN does the load time begin to increase as the number of concurrent users increase? A tipping point is reached when you get to a certain number of concurrent users, after which the server performance will start to degrade. So load test according to how many users you expect to reach your website in the near future.
How can you estimate the amount of users you expect?
Installing Google Analytics or another analytics package on your pages is a must! This way you will be able to see how many daily users are visiting your website, and what is the growth of your visits from month-to-month which can help in predicting future expected visits and therefore expected load on your server.
Even if I know the number of users, how can I estimate actual load?
The answer is in the F12 Development Tools available in all browsers. Open up your website in any browser and push F12 (or for Opera Ctrl+Shift+I), which should open up the browser's development tools. On Firefox make sure you have Firebug installed, on Chrome and Internet Explorer it should work out of the box. Go to the Net or Network tab and then refresh your page. This will show you the number of HTTP requests, bandwidth usage per page load!
So the formula to work out daily server load is simple:
Number of HTTP requests per page load X the average number of pages load per user per day X Expected number of concurrent users = Total HTTP Requests to Server per Day
And...
Number of MBs transferred per page load X the average number of pages load per user per day X Expected number of concurrent users = Total Bandwidth Required per Day
I've always found it easier to calculate these figures on a daily basis and then extrapolate it to weeks and months.
Node.js is single threaded so you should definitely start a process for every cpu your machine has. Cluster is by far the best way to do this and has the added benefit of being able to restart died workers and to detect unresponsive workers.
You also want to do load testing until your requests start timing out or exceed what you consider a reasonable response time. This will give you a good idea of the upper limit your server can handle. Blitz is one of the many options to have a look at.
I have never used Joyent's statistics, but NodeFly and their node-nodefly-gcinfo is a great tools to monitor node processes.
We use Kentico CMS and I've exchanged emails with them about a web garden deployment.
We have a single site running on a server with 8 cpu cores. In line with Kentico's advice, we have not altered the application pool web garden setting from the default i.e. it is set to a maximum number of worker processes of 1.
Our experience is that the site only uses one of the cpu cores - the others are idling. When I emailed them about this, their response was that the OS/IIS would handle this and use other cores as necessary even though the application pool only has a single worker process.
Now, I've a lot of respect for the guys at Kentico, but this doesn't seem right to me?
Surely, if we want to use all cores, we need to permit eight worker processes (and implement session state storage in SQL server)?
Many thanks
Tony
I would suggest running perfmon for a 24 hours and see if you can determine what resources are being used. Indeed they might already be running on all cores . . . Also, if their web app is a heavily threaded system, then it will take full advantage of multiple cores(at least ours does). Threads, not worker processes, are what actually count for processor utilization.
Not sure if you got an answer on ServerFault, at any rate ASP.NET is multi-threaded and in a single worker process there are several threads, each serving a single request.
I am writing an application server (again, non-related with a question I already posted here) and I am wondering what are the strategies to use when creating worker threads that work on the database. Some preliminary dates: the server receives xml and sends back xml, all the requests query a database - each request could take a few milliseconds to a few seconds.
Say for example that your server services a small to medium number of clients which in turn send a small number of requests per connection. Is it safe to have one worker thread per connection or should it be per request? Also should a thread pool be used to limit the resources used by the server or a worker should be added each time a new connection/request is made?
Should the server limit the number of threads it creates to an upper limit?
Hope I am not too vague ... I can hardly keep my eyes open.
If you don't have extensive experience writing application servers is a daunting task. It can be eased by using frameworks like ACE that allow you to build different configurations of your app serving infrastructure like thread per connection, thread pools, leader follower and then load the appropriate configuration with an extensible service framework.
I would recommend to read these books on ACE to get
C++ Network Programming: Mastering Complexity Using ACE and Patterns
C++ Network Programming: Systematic Reuse with ACE and Frameworks
to get an idea about what the framework can do for you.
The way I write apps like this is to make the number of threads configurable via the command line and/or a configuration file. I then do some load testing with different numbers of threads - there is always an optimal number beyond which performance begins to degrade.
If you follow the model adopted by Java EE app server developers, there's a queue for incoming requests and a pool of worker threads to service them. It's one thread per request. When a worker thread fulfills a request it goes back into the pool. If the incoming requests show up faster than the worker thread pool can service them, the queue allows them to stack up until a worker thread is released. Both the queue size and the thread pool can be tuned to match for your situation.
I'd wonder why anyone would feel the need to write their own server from scratch, especially when the scenario you describe is solved so well by others. If your wish is education, good luck. If you think you're going to improve on what's been done in the past, I'd re-examine that assumption.