Load is not getting increased in AppD when we increase the threads count in JMeter. For example, if we are able to achieve 100k calls/min for 500 users with 20 ms avg response time. Load remains at 135 k with 25ms avg resp time when we give 1200 as threads in JMeter. Even we increase the load thrice, load is not going to the application. Didn't observe errors in JMeter as well. We are giving host entries in all the load generators. Is that could be a reason for controlling the load from JMeter? Request help to resolve this issue please
If you increase the number of threads and the throughput is not increasing there could be 2 possible reasons for this:
The throughput is not increasing as response time is increasing which indicates your application performance bottleneck, look at Response Times vs Threads and the point where the response time starts increasing will match the maximum number of users your application can support
JMeter is not capable of sending requests fast enough due to lack of resources or improper configuration, make sure to follow JMeter Best Practices and if it doesn't help - consider allocating more load generator machines and switch to Distributed Mode of JMeter tests execution
As depicted in the following graph, the relationship between the load (Uvsers) and KPIs such as Throughput (TP) is non-linear. At certain point, increasing the load will not result on an increased Throughput that is proportional/linear (the Heavy Load zone).
Related
I am running my jmeter script for almost a week and observed an interesting thing today. Below is the scenario:
Overview: I am gradually increasing the load on the application. In my last test I gave load of 100 users on the app and today I increased the load to 150 users.
Result of 150 users test:
Response time of the requests decreased compared to the last test. (Which is a good sign)
Throughput decreased drastically to half of what I got in the previous test with less load.
Received 225 errors while executing the test.
My questions are:
What could be the possible reason for such strange behavior of throughput? Why did throughput decrease instead of increasing with the increasing load?
Did I get good response time as many of my requests failed?
NOTE: Till 100 users test throughput was increasing with the increasing load of users.
Can anyone please help me with this question. I am a new bee in performance testing. Thanks in Advance!!
Also, would like to request if anyone can suggest good articles/site etc on finding performance bottleneck and learning crucial things in performance.
Most probably these 225 requests which failed returned failure immediately therefore average response time decreased, that's why you should be looking into i.e. Response Times Over Time chart and pay more attention to percentiles as mean response time can mask the real problem.
With regards to the bottleneck discovery, make sure to collect as much information from the server side as you can, i.e.
CPU, RAM, Network, Disk usage from JMeter PerfMon Plugin
Slow queries log from the database
"heaviest" functions and largest objects from the profiling tool for your application
I am trying to stress test my server.
To do so I am using Jmeter and here is my set up:
I use
my Setup
Thread: 1000
schedule for 3 mins
So as you see I keep going with 1000 thread for a period of 3 mins.
But when I look at the throughput I only get around 230 per second
results
So what should I do to increase the through put to for example 1000000 per second? How come increasing the thread which I assume means more load does not increase throughput?
According to JMeter Glossary
Throughput is calculated as requests/unit of time. The time is calculated from the start of the first sample to the end of the last sample. This includes any intervals between samples, as it is supposed to represent the load on the server.
The formula is: Throughput = (number of requests) / (total time).
Throughput explicitly relies on the application response time. Looking into your results, the average response time is 3.5 seconds therefore you will not get more than 1000 / 3.5 = 285 requests per second
Theoretically you could use Throughput Shaping Timer and Concurrency Thread Group combination, this way JMeter will kick off extra threads if the current amount is not enough to reach/maintain the desired throughput, however looking into 8.5% error rate and maximum response time for your application > 2 minutes my expectation is that you will not be able to get more throughput because most probably your application is overloaded and cannot respond faster.
Throughput measures the number of transactions or requests that can be made in a given period of time. basically, it lists the number of requests server managed to serve in a given time period. Throughput value depends on lot of factors and maybe your application under test not able to cater the expected load.
So with 1000 threads, you can't expect a 1000 throughput.
It's up to you to find out how much throughput your application can handle. For that maybe you need to do different optimizations on your side like optimize your script, distribute load via JMeter execution, increase theard count,...etc
Do we need to adjust Throughput given by jmeter, to find out the actual tps of the system
For eg : I am getting 100 tps for concurrent 250 users. This ran for 10 hrs. Can I come to a conclusion like my software can handle 100 transactions per second. Or else do I need to do some adjustment and need to get a value. Why i am asking this because when load started, system will take sometime to perform in adequate level (warm up time). If so how to do this. Please help me to understand this.
By default JMeter sends requests as fast as it can, the main factor which are affecting TPS rate are:
number of threads (virtual users) - this you can define in Thread Group
your application response time - this is not something you can control
Ideally when you increase number of threads the number of TPS should increase by the same factor, i.e. if you have 250 users and getting 100 tps you should get 200 tps for 500 users. If this is not the case - these 500 users are beyond saturation point and your application bottleneck is somewhere between 250 and 500 users (if not earlier).
With regards to "warm up" time - the recommended approach of conducting the load is doing it gradually, this way you will allow your application to get prepared to increasing load, warm up caches, let JIT compiler/optimizer to go their work, etc. Moreover this way you will be able to correlate the increasing load with increasing/decreasing throughput, response time, number of errors, etc. while having 250 users released at once doesn't tell the full story. See
The system warmup period varies from one system to the other. Warm up period is where configurations are cached, different libraries are initialized (eg. Builder.init()) and other initial functions that usually don't happen for subsequent calls. If you study results of the load test, there is a slow period at the very beginning. For most systems, it could be as small as 5 to 10 minutes. These values could be even negligible if the test is as long as 10 hours. But then again, average calculation can be effected if the results give extremely low values at the start (it always depend on the jump from initial warming up period to normal operations).
As per jmeter configurations this thread may explain the configuration. How to exclude warmup time from JMeter summary?
I'm getting the following results, where the throughput does not have a change, even when I increase the number of threads.
Scenario#1:
Number of threads: 10
Ramp-up period: 60
Throughput: 5.8/s
Avg: 4025
Scenario#2:
Number of threads: 20
Ramp-up period: 60
Throughput: 7.8/s
Avg: 5098
Scenario#3:
Number of threads: 40
Ramp-up period: 60
Throughput: 6.8/s
Avg: 4098
The my JMeter file consists of a single ThreadGroup that contains a single GET.
When I perform the request for an endpoit where the response time faster (less than 300 ms) I can achieve throughput greater than 50 requests per seconds.
Can you see the bottleneck of this?
Is there a relationship between response time and throughput?
It's simple as JMeter user manual states:
Throughput = (number of requests) / (total time)
Now assuming your test contains only a single GET then Throughput will be correlate average response time of your requests.
Notice Ramp-up period: 60 will start to create threads over 1 minute, so it will add to total time of execution, you can try to reduce it to 10 or equal to Number of threads.
But you may have other sampler/controllers/component that may effect total time.
Also in your case especially in Scenario 3, maybe some requests failed then you are not calculating Throughput of successful transactions.
In ideal world if you increase number of threads by factor of 2x - throughput should increase by the same factor.
In reality the "ideal" scenario is hardly achievable so it looks like a bottleneck in your application. The process of identifying the bottleneck normally looks as follows:
Amend your test configuration to increase the load gradually so i.e. start with 1 virtual user and increase the load to i.e. 100 virtual users in 5 minutes
Run your test and look into Active Threads Over Time, Response Times Over Time and Server Hits Per Second listeners. This way you will be able to correlate increasing load with increasing response time and identify the point where performance starts degrading. See What is the Relationship Between Users and Hits Per Second? for more information
Once you figure out what is the saturation point you need to know what prevents your application from from serving more requests, the reasons could be in:
Application simply lacks resources (CPU, RAM, Network, Disk, etc.), make sure to monitor the aforementioned resources, this could be done using i.e JMeter PerfMon Plugin
The infrastructure configuration is not suitable for high loads (i.e. application or database thread pool settings incorrect)
The problem is in your application code (inefficient algorithm, large objects, slow DB queries). These items can be fetched using a profiler tool
Also make sure you're following JMeter Best Practices as it might be the case JMeter is not capable of sending requests fast enough due to either lack of resources on JMeter load generator side or incorrect JMeter configuration (too low heap, running test in GUI mode, using listeners, etc)
I'm trying to understand a significant performance increase in my Jmeter test.
In a multi-tenancy database environment, I have a single RESTful service test containing a Thread Group with a single HTTP Request sampler posting an XML payload. The XML payload is then evaluated via stored procedures, and a response is received stating if the claim was qualified. I run this test from a .bat file (non-gui mode) in an Apache 7 environment with a single JVM running.
Test Thread Group Properties
# of Threads: ${__P(test.threads,200)}
Ramp-Up Period: ${__P(test.rampup,1)}
Loop Count: Forever
Delay Thread: Enabled
Scheduler: Enabled
Duration: ${__P(test.duration,1800)}
HTTP Request
Method: POST
https://serverName:port/database/.../${__P(tenant,1111)}/Claim/${__property(contractId)}
When I duplicate the HTTP Request sampler within the TG and change the tenant ID within the URL, for some reason the performance seems to increase by > 55%. (i.e., the # of claims/second is increased by 55%) It appears the test did not fail, so I cannot attribute the performance increase to an increased error rate.
I would have expected an increase if I had enabled another JVM to let the Load Balancer perform optimization, but this is not the case. (still using only 1 JVM)
HTTP Request 1
https://serverName:port/database/.../${__P(tenant,1111)}/Claim/${__property(contractId)}
HTTP Request 2
https://serverName:port/database/.../${__P(tenant,2222)}/Claim/${__property(contractId)}
The theory going around here is that Jmeter generates a workload at a higher rate for multiple requests than for a single request. I'm skeptical, but haven't found anything "solid" to support my skepticism.
Is this theory true? If so, why would two HTTP Requests increase the performance?
In short: it's OK.
Longer version:
Here is how JMeter works:
JMeter starts all the threads during ramp-up period
Each thread starts executing samplers upside down (or according to the Logic Controllers)
When request doesn't have more samplers to execute and no more loops to iterate it's being shut down.
So how does number of virtual users correlate with the "performance". When you increase virtual users number of requests number for a load test it affects Throughput
Throughput is calculated as requests/unit of time. The time is calculated from the start of the first sample to the end of the last sample. This includes any intervals between samples, as it is supposed to represent the load on the server.
The formula is: Throughput = (number of requests) / (total time).
So if you increase load on well-behaved system throughput should increase by the same factor or linearly.
When you increase load but throughput does not increase, such situation is known as "saturation point" when you get the maximum performance from the system. Further load increasing will lead to throughput going down.
References:
Apache JMeter Glossary
An extended Glossary version
And how do you messure your performance? According to your "theory" your messurements includes jmeter overhead and this would be wrong. More over, is the response the same for both cases? What I mean, is the backend doing the same work work both cases?
Maybe first request returns different output then the other one. Maybe it is more expensive to generate output in one of the request. That is why you will notice "incresed" performance as normally you would do N x Heavy task in X seconds, and in second case G x heavy tasks + H X light tasks in the same time where G < N/2 - more requests in the same time? Sure! Incresed perfomance? Nope.
So to completly investigate what is happening, you need to review your measurement method. I would start with comparing the the actual time for both requests.