I want to test a rate-limiting app with Ruby where I define different behavior based on the number of requests per second.
For example, if I see 300 request per second or more, I want it to respond with a block.
But how would I test this by generating 300 requests per second in Ruby? I understand there are hard limitations based on CPU for example, but if I kept the number well below that limitation, how would I still send something that both exceeds the threshold and stays below?
Just looping N-times doesn't guarantee me the throughput.
The quick and dirty way is to spin up 300 threads that each do one request per second. The more elegant way is to use something like Eventmachine to create requests at the required rate. With the right non-blocking HTTP library it can easily generate that level of activity.
You also might try these tools:
ab the Apache benchmarking tool, common many systems. It's very good at abusing your system.
Seige for load testing.
How about a minimal homebrew solution:
OPS_PER_SECOND = 300
count = 0
duration = 10
start = Time.now
while true
elapsed = Time.now - start
break if elapsed >= duration
delay = (count - (elapsed / OPS_PER_SECOND)) / OPS_PER_SECOND
sleep(delay) if delay > 0
do_request
count += 1
end
Related
I am using Locust and my code looks as below
class RecommenderTasks(TaskSet):
#task
def test_recommender_multiple_platforms(self):
start = round(time.time() * 1000)
self.client.get('recommendations', name='Test')
end = round(time.time() * 1000)
print(end - start)
class RecommenderUser(FastHttpUser):
tasks = [RecommenderTasks]
wait_time = constant(1)
host = "https://my-host.com/"
When I test with this code, I get the following output times
374
62
65
68
64
I am not sure why the very first task time alone is about 300+ ms and the rest are as expected. With this, my overall average time also increases. Could you please help me here?
Locust response times are measured from the time the initial request is sent to the server to the time a response is received. By default Locust reuses socket connections when available but creates new ones if an existing one isn't available. When connecting via HTTPS, there are a number of things that need to be done to set up the connection initially. Generally performance of that connection set up is dependent on things the server is doing. You could look into ways of reducing your connection setup time. How to do that will vary widely depending on your stack but you can find general principles in SO answers like this one:
how to reduce ssl time of website
I'm running load tests in gatling, and noticed when I ramp 250 users over 10 seconds, the report gives me an average of 31 req/s:
val combinedScenario = scenario("Combined")
.feed(UuidFeeder.feeder)
.exec(_.set("token", token))
.exec(saveData)
.exec(processDocumentRequest)
)
val scn = List(OAuthRequest.inject(atOnceUsers(1)),
combinedScenario.inject(nothingFor(5 seconds),
rampUsers(250) over (10 seconds)));
setUp(scn).protocols(httpConf).maxDuration(60 minutes)
However, when I surround the scenario in a forever loop and put a 60 second pace in between each set of requests, the report then says I average about 8 req/s:
val combinedScenario = scenario("Combined")
.feed(UuidFeeder.feeder)
.exec(_.set("token", token))
.forever(
pace(60 seconds)
.exec(saveData)
.exec(processDocumentRequest)
)
Is this simply because the report factors in the 50 seconds in between iterations where 0 requests are being sent? Can I assume that it's still sending around 31 req/s for the short bursts of requests being sent each minute?
Yes - the reports just show what the actual throughout during the scenario was, not some hypothetical maximum. The number you get could be constrained by your scenario or by the application under test. You would need to run some experiments to confirm.
With the pace in the scenario, you should also be able to increase the number of concurrent users, based on your initial testing
I'm having some trouble with sending batch requests for the pagespeed API. From what I have seen in my google developers console I should have 100 requests per second with a max of 25,000 per day. However, I'm running into a problem even just trying to do 50 per second. I have tried to impose timing into my ruby application and for some reason that doesn't change the error. I still get the rateLimitExceeded Error from google on a decent amount of the results. I'm doing this on arrays containing ~1000 urls if that matters.
Here's my batch function, I call it in a loop from another function, I thought this might work better for timing. But it didn't seem to change anything.
def send_request(urls)
#psservice.batch do |ps|
urls.each do |url|
ps.run_pagespeed(url) do |result, err|
err.nil? ? #data.push(result) : #errors.push("#{url}, #{err}")
end
end
end
end
This gets called from
#urls.each_slice(50).to_a.each do |url_list|
send_request(url_list, options)
sleep(1)
end
Any ideas why this would occur? Thanks in advance
I misread the quota for Google Pagespeed - it's 100 requests / 100 seconds. So one request a second. It seems the more I check that it actually is 1 request / second. I still have trouble trying to run 100 requests then waiting 100 seconds.
I am working on a eventmachine based application that periodically polls for changes of MongoDB stored documents.
A simplified code snippet could look like:
require 'rubygems'
require 'eventmachine'
require 'em-mongo'
require 'bson'
EM.run {
#db = EM::Mongo::Connection.new('localhost').db('foo_development')
#posts = #db.collection('posts')
#comments = #db.collection('comments')
def handle_changed_posts
EM.next_tick do
cursor = #posts.find(state: 'changed')
resp = cursor.defer_as_a
resp.callback do |documents|
handle_comments documents.map{|h| h["comment_id"]}.map(&:to_s) unless documents.length == 0
end
resp.errback do |err|
raise *err
end
end
end
def handle_comments comment_ids
meta_product_ids.each do |id|
cursor = #comments.find({_id: BSON::ObjectId(id)})
resp = cursor.defer_as_a
resp.callback do |documents|
magic_value = documents.first['weight'].to_i * documents.first['importance'].to_i
end
resp.errback do |err|
raise *err
end
end
end
EM.add_periodic_timer(1) do
puts "alive: #{Time.now.to_i}"
end
EM.add_periodic_timer(5) do
handle_changed_posts
end
}
So every 5 seconds EM iterates over all posts, and selects the changed ones. For each changed post it stores the comment_id in an array. When done that array is passed to a handle_comments which loads every comment and does some calculation.
Now I have some difficulties in understanding:
I know, that this load_posts->load_comments->calculate cycle takes 3 seconds in a Rails console with 20000 posts, so it will not be much faster in EM. I schedule the handle_changed_posts method every 5 seconds which is fine unless the number of posts raises and the calculation takes longer than the 5 seconds after which the same run is scheduled again. In that case I'd have a problem soon. How to avoid that?
I trust em-mongo but I do not trust my EM knowledge. To monitor EM is still running I puts a timestamp every second. This seems to be working fine but gets a bit bumpy every 5 seconds when my calculation runs. Is that a sign, that I block the loop?
Is there any general way to find out if I block the loop?
Should I nice my eventmachine process with -19 to give it top OS prio always?
I have been reluctant to answer here since I've got no mongo experience so far, but considering no one is answering and some of the stuff here is general EM stuff I may be able to help:
schedule next scan on first scan's end (resp.callback and resp.errback in handle_changed_posts seem like good candidates to chain next scan), either with add_timer or with next_tick
probably, try handling your mongo trips more often so they handle smaller chunks of data, any cpu cycle hog inside your reactor would make your reactor loop too busy to accept events such as periodic timer ticks
no simple way, no. One idea would be to measure diff of Time.now to next_tick{Time.now}, do benchmark and then trace possible culprits when the diff crosses a threshold. Simulating slow queries (Simulate slow query in mongodb? ?) and many parallel connections is a good idea
I honestly don't know, I've never encountered people who do that, I expect it depends on other things running on that server
To expand upon bbozo's answer, specifically in relation to your second question, there is no time when you run code that you do not block the loop. In my experience, when we talk about 'non-blocking' code what we really mean is 'code that doesn't block very long'. Typically, these are very short periods of time (less than a millisecond), but they still block while executing.
Further, the only thing next_tick really does is to say 'do this, but not right now'. What you really want to do, as bbozo mentioned, is split up your processing over multiple ticks such that each iteration blocks for as little time as possible.
To use your own benchmarks, if 20,000 records takes about 3 seconds to process, 4,000 records should take about 0.6 seconds. This would be short enough to not usually affect your 1 second heartbeat. You could split it up even farther to reduce the amount of blockage and make the reactor run smoother, but it really depends on how much concurrency you need from the reactor.
I need to regulate how often a Mechanize instance connects with an API (once every 2 seconds, so limit connections to that or more)
So this:
instance.pre_connect_hooks << Proc.new { sleep 2 }
I had thought this would work, and it sort of does BUT now every method in that class sleeps for 2 seconds, as if the mechanize instance is touched and told to hold 2 seconds. I'm going to try a post connect hook, but it is obvious I need something a bit more elaborate, but what I don't know what at this point.
Code is more explanation so if you are interested following along: https://github.com/blueblank/reddit_modbot, otherwise my question concerns how to efficiently and effectively rate limit a Mechanize instance to within a specific time frame specified by an API (where overstepping that limit results in dropped requests and bans). Also, I'm guessing I need to better integrate a mechanize instance to my class as well, any pointers on that appreciated as well.
Pre and post connect hooks are called on every connect, so if there is some redirection it could trigger many times for one request. Try history_added which only gets called once:
instance.history_added = Proc.new {sleep 2}
I use SlowWeb to rate limit calls to a specific URL.
require 'slowweb'
SlowWeb.limit('example.com', 10, 60)
In this case calls to example.com domain are limited to 10 requests every 60 seconds.