You’re correct that this is the ddos throttling.  The real question is what do 
you want to do?  JMeter with zero think time is an imperfect load generator- 
this is only one complication. The bigger one is the open/closed model issue. 
With you design you have back ptesssure from your system under test to your 
load generator. A jmeter virtual user will only ever issue a request when the 
prior one completes. Real users are not so well behaved which is why your test 
results will always be over optimistic with this design.

Better approach us to use a load generator that replicates the desired request 
distribution without triggering the ddos protection. Wrk2, Tsung, httperf are 
candidates, as well as the cloud based load generator services. Also see Neil 
Gunther’s paper on how to combine multiple jmeter instances to replicate real 
world tragic patterns.

Peter

Sent from my iPhone

> On Mar 26, 2018, at 4:21 PM, John Melom <john.me...@spok.com> wrote:
> 
> Hi,
>  
> I am load testing our system using Jmeter as a load generator.  We execute a 
> script consisting of an https request executing in a loop.  The loop does not 
> contain a think time, since at this point I am not trying to emulate a “real 
> user”.  I want to get a quick look at our system capacity.  Load on our 
> system is increased by increasing the number of Jmeter threads executing our 
> script.  Each Jmeter thread references different data.
>  
> Our system is in AWS with an ELB fronting Nginx, which serves as a reverse 
> proxy for our Docker Swarm application cluster.
>  
> At moderate loads, a subset of our https requests start experiencing to a 1 
> second delay in addition to their normal response time.  The delay is not due 
> to resource contention.  System utilizations remain low.  The response times 
> cluster around 4 values:  0 millilseconds, 50 milliseconds, 1 second, and 
> 1.050 seconds.  Right now, I am most interested in understanding and 
> eliminating the 1 second delay that gives the clusters at 1 second and 1.050 
> seconds.
>  
> The attachment shows a response time scatterplot from one of our runs.  The 
> x-axis is the number of seconds into the run, the y-axis is the response time 
> in milliseconds.  The plotted data shows the response time of requests at the 
> time they occurred in the run.
>  
> If I run the test bypassing the ELB and Nginx, this delay does not occur. 
> If I bypass the ELB, but include Nginx in the request path, the delay returns.
>  
> This leads me to believe the 1 second delay is coming from Nginx. 
>  
> One possible candidate Nginx DDOS.  Since all requests are coming from the 
> same Jmeter system, I expect they share the same originating IP address.  I 
> attempted to control DDOS throttling by setting limit_req as shown in the 
> nginx.conf fragment below:
>  
> http {
> …
>     limit_req_zone $binary_remote_addr zone=perf:20m rate=10000r/s;
> …
>     server {
> …
>         location /myReq {
>             limit_req zone=perf burst=600;
>             proxy_pass xxx.xxx.xxx.xxx;
>         }
> ….
>     }
>  
> The thinking behind the values set in this conf file is that my aggregate 
> demand would not exceed 10000 requests per second, so throttling of requests 
> should not occur.  If there were short bursts more intense than that, the 
> burst value would buffer these requests.
>  
> This tuning did not change my results.  I still get the 1 second delay.
>  
> Am I implementing this correctly?
> Is there something else I should be trying?
>  
> The responses are not large, so I don’t believe limit_req is the answer.
> I have a small number of intense users, so limit_conn does not seem likely to 
> be the answer either.
>  
> Thanks,
>  
> John Melom
> Performance Test Engineer
> Spōk, Inc.
> +1 (952) 230 5311 Office
> john.me...@spok.com
>  
> <image003.jpg>
>  
> 
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