I have a 32GB, i7 core processor running on windows 10 and I am trying to generate 10kVU concurrent load via jmeter. For some reason I am unable to go beyond 1k concurrent and I start getting BindException error or Socket connection error. Can someone help me with the settings to achieve that kind of load? Also if someone is up for freelancing I am happy to consider that as well. Any help would be great as I am nearing production and am unable to load test this use case. If you guys have any other tools that I can use effectively, that would also help.
You reach the limit of 1 computer, thus you must execute in distributed environment of multiple computers.
You can setup JMeter's distributed testing on your own environment or use blazemeter or other cloud based load testing tool
we can use BlazeMeter, which provides us with an easy way to handle our load tests. All we need to do is to upload our JMX file to BlazeMeter. We can also upload a consolidated CSV file with all the necessary data and BlazeMeter will take care of splitting it, depending on the amount of engines we have set.
On BlazeMeter we can set the amount of users or the combination of engines (slave systems) and threads that we want to apply to our tests. We can also configure additional values like multi locations.
1k concurrent sounds low enough that it's something else ... it's also the default amount of open file descriptor limits on a lot of Linux distributions so maybe try to raise the limit.
ulimit -Sn
will show you your current limit and
ulimit -Hn
will show you the hard limit you can go before you have to touch configuration files. Editing /etc/security/limits.conf as root and setting something like
yourusername soft nofile 50000
yourusername hard nofile 50000
yourusername - will have to be the username of the user which with you run jmeter.
After this you will probably have to restart in order for the changes to take effect. If not on Linux I don't know how to actually do this you will have to google :D
Recommendation:
As a k6 developer I can propose it as an alternative tool, but running 10k VUs on a single machine will be hard with it as well. Every VU will take some memory - like at least 1-3mb and this will go up the larger your script is. But with 32gb you could still run upto 1-2kVUs and use http.batch to make concurrent requests which might simulate the 10k VUs depending on what your actual workflow is like.
I managed to run the stages sample with 300VUs on a single 3770 i7 CPU and 4gb of ram in a virtual machine and got 6.5k+ rps to another virtual machine on a neighboring physical machine (the latency is very low) so maybe 1.5-2kVUs with a a somewhat more interesting script and some higher latency as this will give time to the golang to actually run GC while waiting for tcp packets. I highly recommend using discardResponseBodies if you don't need them and even if you need some to actually get the response for them. This helps a lot with the memory consumption a each VU
Related
This is for e-commerce project where the number of users login will be more. I have been given a benchmark 8000 concurrent users need to login and response time should be 3 minutes
#abi , hi .
Let me provide couple notes here.
Depending upon Your connection bandwidth , from my experience as performance test engineer, I'd say jmeter single instance usually holds up to 1k(1000)- 2k(2000) in best case users load.
Considering You have a requirement for 8k (8000 users) load, You need to launch jmeter in distributed mode ( master <-> slaves).
For this config setup I'd recommend to go with 1 master node and 4slaves. For that - You will need 5 machines (aws/azure, whatever) in the same sub-network.
Re more technical details on distributed setup, please take a look:
in public jmeter documentation
please also look into this step-by-step setup manual
Also, when i've been doing set-up for 10k load for one of my recent projects - I did couple notes for myself in g-doc . Let me know if it opens fine for You.
Last note, If You need to do some load/performance tests on APIs that require AUTHZ, I'd recommend to split authorize (IDP bypass) and performance scenario itself - in different thread groups. As usually IDP in DEVs/Stagings does not hold much load .
So at first You need to authorize w/o any load (1st Thread group).
And in 2nd Thread group - start calling target APIs under the test.
It depends on:
Your machine specifications (CPU, RAM, NIC card, hard drive, etc.)
The nature of your Test Plan (number of requests, size of requests/responses, number of pre/post processors, assertions, timers, etc.)
Response time of your application
So if your test is a simple GET request which returns small text response - you might simulate 10 000 of users on a mid-range modern laptop. And if your test is connected with heavy requests, large responses, file uploads, etc. - it might be 1000 users.
Make sure to follow recommendations from JMeter Best Practices
Make sure to have monitoring of resources usage of your system (CPU, RAM, Swap, etc.). You can use JMeter PerfMon Plugin for this.
Make sure that your test behaves like a real browser
Start with 1 virtual user and gradually increase the load until you reach 8000 virtual users or JMeter starts lacking resources, whatever comes the first. If you can simulate 8000 users from a single machine - you're good to go. If not - you will have to consider Distributed Testing.
I need to test 200.000 VU hitting an app in 10 seconds, so I started to make a test of 10.000 VU, running Jmeter in Non-GUI mode, to see the response of my computer, my internet connection and the site response, but I got 83.50% of Errors.
95% of the errors were these:
Non HTTP response code: java.net.ConnectException/Non HTTP response message: Connection timed out: connect
This means that the internet connection was not enough for the short time of the test?
Thanks.
Running 200K users
Generally speaking in traditional HTTP running 200.000 users from one machine is impossible: there isn't that many ports. I.e. if you maximize your port usage (and it's likely you need to change OS settings to do that, since usually OS will limit number of open ports to somehwere between 1000 and 10000), JMeter will have about 64500 ports to run requests on. Each JMeter HTTP sampler needs a separate port, so you need 200K ports. Thus you need to have at least 4 machines to run 200K requests concurrently.
But that may not be enough: if you have more than one request sequentially (like most performance tests do), you will be able to run even less concurrent requests, since ports are usually not closed right away after request is done, so next request has to use a different port.
Don't forget that server also must be able to receive similar load.
But even that may not be enough: JMeter needs to have enough memory to accommodate 10-30K threads. Size of thread in memory will depend on a few things, and how your script is designed among them.
Bottom line: with all the tweaking, realistically, port availability limits number of concurrent requests JMeter can run from one machine to 10-30K concurrent users. Thus to test 200K users, you need about 7-20 JMeter machines.
Running 10K users
If you were testing in a designated environment (where clients and servers are next to each other with optimized network between them), you should be able to run 10K users from one machine, if other limits, e.g. memory and max ports were properly tweaked. But sounds like you are trying to test them over the internet connection?
Well, 2 problems here:
Performance testing over internet connection is absolutely pointless. You don't know what is between you and servers, and how those things in between are changing the shape of the load. You won't know if it was 10K concurrent requests, or 10K sequential requests. And results will only tell you how fast your internet is.
Any ISP will have a limit on number of connections from one IP, and it will be well below 10K. Not to mention that some ISPs may flag / temporary ban your IP for such flood.
Bottom line: whoever asked you to test 10K or 200K concurrent users, should also provide a set of JMeter machines to run this test from. Those machines should be close to tested servers, preferably without any extra routing in between (or with well known and well configured routing)
I don't think that stressing your application by kicking off 200k users at once is a good idea (same applies to 10k users) as the results, even in case of success, won't tell the full story. Moreover, in case of error you will be able to state only that 10k users in 10 seconds is not possible, however you won't have the information like:
What was the number of users when errors start occurring
What is the correlation between number of concurrent users and response time and/or throughput
What is the saturation point (the maximum system performance)
So I would recommend re-running your test and increasing the load gradually from one virtual user to 10 000 and see when it breaks. The breaking point is called bottleneck and the cause can be determined like:
First of all make sure you're following JMeter Best Practices as default JMeter configuration is not suitable for high loads and if JMeter is not capable of sending requests fast enough you will not get accurate results. Most probably you will have to run JMeter in Distributed mode, it is highly unlikely you will be able to mimic 20k requests per second from a single machine (or it has to be a very powerful one)
Set up monitoring of the application under test in order to ensure that it has enough headroom in terms of CPU, RAM, Disk, etc. You can use JMeter PerfMon Plugin for this
Check your application infrastructure, like JMeter the majority of middleware components like web/application servers, load balancers, databases, etc. default configurations are suitable for development and debugging, they need to be tuned for high throughput.
Check your application code using profiler tools telemetry, the reason could be in i.e. slow DB query, inefficient algorithm, large object, heavy function, etc.
I want to simulate up to 100,000 requests per second and I know that tools like Jmeter and Locust can run in distributed mode to generate load.
But since there are cloud VMs with up to 64 vCPUs and 240GB of RAM on a single VM, is it necessary to run in a cluster of smaller machines, or can I just use 1 large VM?
Will I be able to achieve more "concurrency" with more machines due to a network bottleneck coming from the 1 large machine?
If I just use one big machine, would I be limited by the number of ports there are?
In the load generator, does every simulated "user" that sends a request also require a port on the machine to receive a 200 response? (Sorry, my understanding of how TCP ports work is a bit weak.)
Also, we use Kubernetes pretty heavily, but with Jmeter or Locust, I feel like it'd be easier to run it on bare VM, without containerizing (even in distributed mode) while still maintaining reproducibility. Should I be trying to containerize Jmeter or Locust and running in Kubernetes instead?
According to KISS principle it is better to go for a single machine assuming it is capable of conducting the required load.
Make sure you're following JMeter Best Practices
Make sure you have monitoring of baseline OS health metrics (CPU, RAM, swap, network and disk IO, JVM statistics, etc.)
Start with low number of users and gradually increase the load until you reach the desired throughput or limit of any of the monitored metrics, whatever comes the first. If there will be a lack of CPU or RAM or something - see what could be done to overcome the limitation.
More information: What’s the Max Number of Users You Can Test on JMeter?
What will be the hardware configuration required to run concurrent of 10,000 user's load in jmeter through non-gui mode?
There is no exact answer for this, but in my experience 10,000 users on a single instance doing anything other than very basic work will be too many.
You should look into setting up distributed testing, so that you have many different injectors. Without knowing anything about your application, I would still want at least 10 instances.
This link should get you started: http://jmeter.apache.org/usermanual/jmeter_distributed_testing_step_by_step.pdf
If you have budget for it, any of the cloud based Jmeter services will make it a lot less painless. Blazemeter is one such offering in this area: http://blazemeter.com/
I have created a test plan for creating userprofile.
I want to run my test plan for 100 users but when i run it for 10 users then it is running successfully with rump up time of 2 sec; but when i try it for 100 users & more than that it is getting failed I am giving rump uptime of 40 sec for 100 users.
I am not able to understand what may be the problem with it.
In my test plan the thread user are differentiated with id
Thanks in Advance.
It's a wide question, this behavior can be caused by
Your application under test can't handle load of 100 threads. Check logs for errors and make sure that application/web server and/or database configuration allow 100+ concurrent connections. Also you can check "Latency" metric to see if there is a problem with infrastructure or application itself.
Your load generator machine can't create 100 concurrent threads. If so - you'll need to consider JMeter Distributed Testing
Your script isn't optimized. I.e. using memory-consuming listeners like "View Results Tree", any graph listeners, regular expression extractors. Try following JMeter Performance and Tuning Tips guide and see whether it resolves your issue.
Agree with Dmitri, reason could be one of the above three.
One more thing you can try.
You can run your jmeter in ui mode for validation of your script and after validation you can run it in non-ui mode which will save lot of memory and cpu processing (basically UI is heaviest part in jmeter).
you can run your jmeter script in non-ui mode like this,
Jmeter -n -t -H proxy -P port
generally on a single dual core machine with 2 GB ram (Load Generator in your case) 100 user test can be carried out successfully.
some more things you can look at to find out the actual bottleneck
1.check application server logs (server on which your application is hosted)
if there are any failures in that then see performance counters on server (CPU, Memory, network etc) to see anything is overloaded.
(if server is windows then check using perfmon if linux then try sar)
if something is overloaded then reason is your app server cant take load of 100 users
probably try tuning it more.
2.check load generator system performance counters (JVM heap usage,CPU,Memory etc)
if JVM heap size is small enough try increasing it but if other counters are overloaded then try distributed load testing.
3.remove unwanted/heavy listeners, assertion from script.
maybe this will help :)