I have met a problem when I want to run load tests on a server using locust.
I set the users number = 4000, the min_wait = 5000 and the max_wait = 15000.
I think the RPS(requests per second) should be around 400, but it's around 100.
Then I try to run it with 3 slaves at different device, which should increase the value of RPS, but it doesn't work and still be around 100.
What's wrong with my configuration or my understanding?
Related
I have tried couple of suggestions as mentioned in other sites on how to configure/Limit 100 requests per minute for a given REST endpoint for a single user. its not working !
Can someone please guide me to setup on how to limit a 100 requests for a given REST endpoint?
Thankyou in Advance!!
The easiest way is adding Constant Throughput Timer however be aware that it's precise enough on minute level so you will have to let your test to run for at least a minute before you start seeing the rate limiting, if your test throughput is higher during the first minute - consider playing with ramp-up.
If you have only 1 user and your test runs for a minute or less you will have to consider the following options:
Precise Throughput Timer
Throughput Shaping Timer
the latter one is extremely easy to use and it provides visual way of defining the target throughput:
I like Locust, but I'm having a problem interpreting the results.
e.g. my use case is that I have a petition site. I expect 10,000 people to sign the petition over a 12 hour period.
I've written a locust file that simulates user behaviour:
Some users load but don't sign petition
Some users load and submit invalid data
Some users (hopefully) successfully submit.
In real life the user now goes away (because the petition is an API not a main website).
Locust shows me things like:
with 50 concurrent users the median time is 11s
with 100 concurent users the median time is 20s
But as one "Locust" just repeats the tasks over and over, it's not really like one user. If I set it up with a swarm of 1 user, then that still represents many real world users, over a period of time; e.g. in 1 minute it might do the task 5 times: that would be 5 users.
Is there a way I can interpret the data ("this means we can handle N people/hour"), or some way I can see how many "tasks" get run per second or minute etc. (ie locust gives me requests per second but not tasks)
Tasks dont really exist on the logging level in locust.
If you want, you could log your own fake samples, and use that as your task counter. This has an unfortunate side effect of inflating your request rate, but it should not impact things like average response times.
Like this:
from locust.events import request_success
...
#task(1)
def mytask(self):
# do your normal requests
request_success.fire(request_type="task", name="completed", response_time=None, response_length=0)
Here's the hacky way that I've got somewhere. I'm not happy with it and would love to hear some other answers.
Create class variables on my HttpLocust (WebsiteUser) class:
WebsiteUser.successfulTasks = 0
Then on the UserBehaviour taskset:
#task(1)
def theTaskThatIsConsideredSuccessful(self):
WebsiteUser.successfulTasks += 1
# ...do the work...
# This runs once regardless how many 'locusts'/users hatch
def setup(self):
WebsiteUser.start_time = time.time();
WebsiteUser.successfulTasks = 0
# This runs for every user when test is stopped.
# I could not find another method that did this (tried various combos)
# It doesn't matter much, you just get N copies of the result!
def on_stop(self):
took = time.time() - WebsiteUser.start_time
total = WebsiteUser.successfulTasks
avg = took/total
hr = 60*60/avg
print("{} successful\nAverage: {}s/success\n{} successful signatures per hour".format(total, avg, hr)
And then set a zero wait_time and run till it settles (or failures emerge) and then stop the test with the stop button in the web UI.
Output is like
188 successful
0.2738157498075607s/success
13147.527132862522 successful signatures per hour
I think this therefore gives me the max conceivable throughput that the server can cope with (determined by changing the No. users hatched until failures emerge, or until the average response time becomes unbearable).
Obviously real users would have pauses, but that makes it harder to test the maximums.
Drawbacks
Can't use distributed Locust instances
Messy; also can't 'reset' - have to quit the process and restart for another test.
I'm trying to build a web application that should be able to handle at least 15000 rps. Some of the optimizations I have done is increase the worker pool size to 20 and set an accept back log to 25000. Since I have set my worker pool size to 20; wil this help with the the blocking piece of code?
A worker pool size of 20 seems to be the default.
I believe the important question in your case is how long do you expect each request to run. On my side, I expect to have thousands of short-lived requests, each with a payload size of about 5-10KB. All of these will be blocking, because of a blocking database driver I use at the moment. I have increased the default worker pool size to 40 and I have explicitly set my deploy vertical instances using the following formulae:
final int instances = Math.min(Math.max(Runtime.getRuntime().availableProcessors() / 2, 1), 2);
A test run of 500 simultaneous clients running for 60 seconds, on a vert.x server doing nothing but blocking calls, produced an average of 6 failed requests out of 11089. My test payload in this case was ~28KB.
Of course, from experience I know that running my software in production would often produce results that I have not anticipated. Thus, the important thing in my case is to have good atomicity rules in place, so that I don't get half-baked or corrupted data in the database.
So, I am using JMeter's throughput shaping timer to test the performance of our REST Server. I noticed a few things i did not expect.
First of all my setup details :
1)JMeter Version : 3.0 r1743807
2)JMX file : DropBox Link
Now , my questions :
1)The throughput shaping timer is configured to run for 60 seconds(100rps - 30 secs, 200 rps - next 30 secs). But the actual test runs only for 3 seconds as shown below. Why?
2) As per the plan the number of requests per second should go from 100 - 200. But here it seems to decrease , as in above.
3)As per this plugin's documentation , the number of thread groups = desired requests per second * server response time / 1000 . Is it because how this plugin internally works or is it a simple logic i am missing?
The issue is with the Thread Group settings.
You only one have 1 iteration and ramp up 300 users in 1 second. So if Jmeter can send all the 300 requests and get the response, JMeter will finish the test immediately. Those timer settings will apply only if the test is running.
If you need the test to run for some duration (say 60 seconds), then set the loop count to forever & duration to 60
Is there a way in locust.io to set the rate at which the requests will be sent? I am using locust to see how my database will perform under increased load. I am not interested in the max request rate the database can take but rather the performance of the database when it receives a specific rate. For example I want to see the latency of the read operations under a specific write load.
I think You need to set min_rate and max_rate at the same value:
class MyUser(MyLocustExtendedClass):
host = "myhost"
min_wait = __VALUE__
max_wait = __VALUE__
...
It is not possible to set locust to a specific RPS, also check reply on this post: specifying RPS
But you can attempt to reach a specific number with using this formula:
rps = wait time X #_users
Change wait time in the Locust class and number of users