We are running a web API hosted in IIS 10 on an 8 core machine with 16 GB Memory and running Windows 10, and throwing a load of say 100 to 200 requests per second through JMeter on the server.
Individual transactions are taking less than 500 milliseconds. When we throw the load initially, IIS threads grow up to around 150-160 mark (monitored through resource monitor and Performance monitor) and throughput increases up to 22-24 transactions per second but throughput and number of threads stop to grow beyond this point even though the CPU usage is less than 40 per cent and we have enough physical memory also available at the peak, the resource monitor does not show any choking at the network or IO level.
The web API is making calls to the Oracle database (3-4 select calls and 2-3 inserts/updates).
We fail to understand what is stopping IIS to further grow its thread pool to process more requests in parallel while all the resources including processing power, memory, network etc are available.
We have placed many performance counters as well, there is no queue build-up (that's probably because jmeter works in synchronous mode)
Also, we have tried to set the min and max threads settings through machine.config as well as ThreadPool.SetMin and Max threads APIs but no difference was observed and seems like those setting are not taking any effect.
Important to mention that we are using synchronous calls/operations (no asnch and await). Someone has advised to convert all our blocking IO calls e.g. database calls to asynchronous mode to achieve more throughput but my understanding is that if threads cant be grown beyond this level then making async calls might not help or may indeed negatively impact the throughput. Since our code size is huge, that would be a very costly activity in terms of time and effort and we dont want to invest in it till we are sure that it would really help. If someone has anything to share on these two problems, pls do share.
Below is a screenshot of the permanence monitor.
So for example there would be service 1 that runs on http://127.0.0.1:5000 that runs on thread 1.
And I would like to run service 2 that would run on http://127.0.0.1:5001 that would run on any thread but not on thread 1.
Is it possible to do something like that?
First off, I think you meant to say "CPU core" instead of "thread". Code runs in a thread and a thread runs on a CPU core when it is running. A process may contain one or more threads. In fact, a nodejs process contains several threads, one thread for running your Javascript, but other threads are involved in running the overall nodejs process.
Which CPU core a given thread runs on is up to the operating system.
Normally with a multi-core CPU, two processes that are trying to run at the same time will be assigned to different CPU cores. This is a dynamic thing inside the OS and can change from time to time as different threads/processes are time sliced. Processes of any kind (including nodejs processes) are not hard bound to a particular core and threads within those processes are not hard bound to a particular core either.
The operating system will decide based on which threads in which processes are vying for time to run how to allocate CPU cores to each thread and it is a dynamically changing assignment depending upon demand. If more threads are trying to run than there are cores, then the threads will each get slices of time on a CPU core and they will all share the CPU cores, each making progress, but not getting to hog a CPU core all to themselves.
If your two services, one running on port 5000 and one running on port 5001 are both nodejs apps, then the operating system will dynamically allocate CPU cores upon demand to each of them. Neither of those two service processes are bound to a specific core. If they are both heavily busy at the same time and you have a multi-core CPU and there's not a lot else in computer also contending for CPU time, then each service's main thread that runs your Javascript will have a different CPU core to run on.
But, keep in mind that this is a dynamic assignment. If you have a four core CPU and all of a sudden several other things start up on your computer and are also contending for CPU resources, then the CPU cores will be shared across all the threads/processes contending for CPU resources. The sharing is done via rotation in small time slices and can incorporate a priority system too. The specific details of how that works vary by operating system, but the principle of "time-sharing" the available CPU cores among all those threads requesting CPU resources is the same.
I had googled about how many clusters could be initialized per core, and all articles I read sad that one node per core is good enough. Therefore, I haven't found a nice explanation about that.
I have an app that uses a lot of i/o and only does few computations, like push/remove from a queue then schedule a task to the database. For this app, I had initialized 5 clusters per core, and it had increased the number of requests I could receive. however the load Avg in the server is very high, about 30 sometimes.
The points are, what are the side effects using this approach (more than one node per core)?
A single core can only run one process at a time.
Most processes that run on your computer are mostly idle (they sit around and wait for something to happen), that's how you can have dozens, or hundreds, of processes running on your computer without much problems.
However, active processes, that do a lot of stuff (like your processes do; and in this case, a lot of I/O also counts), keep a CPU core pretty busy. So it's useless to start more than one of such processes per core, because they will all be contending for a time slice on that core.
That's also why you get a high load average, which is an indication of how many processes are either using the CPU, or are waiting to use the CPU.
I have written two simple services returning a constant value. After running 100'000 concurrent client threads to consum them on the same machine in separated experiments, I found out none of CPU cores are utilized over 10 percent. Even after changing the client code to generate client threads in an infinitive loop, server core utilization doesn't changed.
Is this behavior because of some none CPU instructions which are executed via each request?
If yes what kind of structure are them?
Some tasks are I/O bound, rather than being CPU bound.
Meaning whatever load you create, the RAM and Disk and Network activity will max out long before the CPU will.
And in some cases, after reaching a certain percentage of CPU load, it just will not increase any more because the nature of the load is utilizing only a sub-set of functions that are finite in nature.
In my experience, if Apache is using 100% of the CPU, you have a bad PHP script or a faulty PHP process.
How does one determine the best number of maxSpare, minSpare and maxThreads, acceptCount etc in Tomcat? Are there existing best practices?
I do understand this needs to be based on hardware (e.g. per core) and can only be a basis for further performance testing and optimization on specific hardware.
the "how many threads problem" is quite a big and complicated issue, and cannot be answered with a simple rule of thumb.
Considering how many cores you have is useful for multi threaded applications that tend to consume a lot of CPU, like number crunching and the like. This is rarely the case for a web-app, which is usually hogged not by CPU but by other factors.
One common limitation is lag between you and other external systems, most notably your DB. Each time a request arrive, it will probably query the database a number of times, which means streaming some bytes over a JDBC connection, then waiting for those bytes to arrive to the database (even is it's on localhost there is still a small lag), then waiting for the DB to consider our request, then wait for the database to process it (the database itself will be waiting for the disk to seek to a certain region) etc...
During all this time, the thread is idle, so another thread could easily use that CPU resources to do something useful. It's quite common to see 40% to 80% of time spent in waiting on DB response.
The same happens also on the other side of the connection. While a thread of yours is writing its output to the browser, the speed of the CLIENT connection may keep your thread idle waiting for the browser to ack that a certain packet has been received. (This was quite an issue some years ago, recent kernels and JVMs use larger buffers to prevent your threads for idling that way, however a reverse proxy in front of you web application server, even simply an httpd, can be really useful to avoid people with bad internet connection to act as DDOS attacks :) )
Considering these factors, the number of threads should be usually much more than the cores you have. Even on a simple dual or quad core server, you should configure a few dozens threads at least.
So, what is limiting the number of threads you can configure?
First of all, each thread (used to) consume a lot of resources. Each thread have a stack, which consumes RAM. Moreover, each Thread will actually allocate stuff on the heap to do its work, consuming again RAM, and the act of switching between threads (context switching) is quite heavy for the JVM/OS kernel.
This makes it hard to run a server with thousands of threads "smoothly".
Given this picture, there are a number of techniques (mostly: try, fail, tune, try again) to determine more or less how many threads you app will need:
1) Try to understand where your threads spend time. There are a number of good tools, but even jvisualvm profiler can be a great tool, or a tracing aspect that produces summary timing stats. The more time they spend waiting for something external, the more you can spawn more threads to use CPU during idle times.
2) Determine your RAM usage. Given that the JVM will use a certain amount of memory (most notably the permgen space, usually up to a hundred megabytes, again jvisualvm will tell) independently of how many threads you use, try running with one thread and then with ten and then with one hundred, while stressing the app with jmeter or whatever, and see how heap usage will grow. That can pose a hard limit.
3) Try to determine a target. Each user request needs a thread to be handled. If your average response time is 200ms per "get" (it would be better not to consider loading of images, CSS and other static resources), then each thread is able to serve 4/5 pages per second. If each user is expected to "click" each 3/4 seconds (depends, is it a browser game or a site with a lot of long texts?), then one thread will "serve 20 concurrent users", whatever it means. If in the peak hour you have 500 single users hitting your site in 1 minute, then you need enough threads to handle that.
4) Crash test the high limit. Use jmeter, configure a server with a lot of threads on a spare virtual machine, and see how response time will get worse when you go over a certain limit. More than hardware, the thread implementation of the underlying OS is important here, but no matter what it will hit a point where the CPU spend more time trying to figure out which thread to run than actually running it, and that numer is not so incredibly high.
5) Consider how threads will impact other components. Each thread will probably use one (or maybe more than one) connection to the database, is the database able to handle 50/100/500 concurrent connections? Even if you are using a sharded cluster of nosql servers, does the server farm offer enough bandwidth between those machines? What else will run on the same machine with the web-app server? Anache httpd? squid? the database itself? a local caching proxy to the database like mongos or memcached?
I've seen systems in production with only 4 threads + 4 spare threads, cause the work done by that server was merely to resize images, so it was nearly 100% CPU intensive, and others configured on more or less the same hardware with a couple of hundreds threads, cause the webapp was doing a lot of SOAP calls to external systems and spending most of its time waiting for answers.
Oce you've determined the approx. minimum and maximum threads optimal for you webapp, then I usually configure it this way :
1) Based on the constraints on RAM, other external resources and experiments on context switching, there is an absolute maximum which must not be reached. So, use maxThreads to limit it to about half or 3/4 of that number.
2) If the application is reasonably fast (for example, it exposes REST web services that usually send a response is a few milliseconds), then you can configure a large acceptCount, up to the same number of maxThreads. If you have a load balancer in front of your web application server, set a small acceptCount, it's better for the load balancer to see unaccepted requests and switch to another server than putting users on hold on an already busy one.
3) Since starting a thread is (still) considered a heavy operation, use minSpareThreads to have a few threads ready when peak hours arrive. This again depends on the kind of load you are expecting. It's even reasonable to have minSpareThreads, maxSpareThreads and maxThreads setup so that an exact number of threads is always ready, never reclaimed, and performances are predictable. If you are running tomcat on a dedicated machine, you can raise minSpareThreads and maxSpareThreads without any danger of hogging other processes, otherwise tune them down cause threads are resources shared with the rest of the processes running on most OS.