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?
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'm using jmeter to generate a performance test, to keep things short and straight i read the initial data from a json file, i have a single thread group in which after reading the data i randomize certain values to prevent data duplication when i need it, then i'm passing the final data to the endpoint using variables, this will end up in a json body that is recieved by the endpoint and it will basically generate a new transaction in the database. Also i added a constant timer to add a 7 seconds delay between requests, with a test duration of 10 minutes and no ramp up, i calculated the requests per second like this:
1 minute has 60 seconds and i have a delay of 7 seconds per request then it's logical to say that every minute i'm sending approximately 8.5 requests per minute, this is my calculation (60/7) = 8.5 now if the test lasts for 10 minutes then i multiply (8.5*10) = 85 giving me a total of 85 transactions in 10 minutes, so i should be able to see that exact same amount of transactions created in the database after the test completes.
This is true when i'm running 10-20-40 users, after the load test run i query the db and i get the exact same number of transaction however, as i increase the users in the thread group this doesn't happen anymore, for example if i set 1000 users i should be able to generate 8500 transactions in 10 minutes, but this is not the case, the db only creates around 5.1k transactions.
What is happening, what is wrong? Why it initially works as expected and as i increase the users it doesn't? I can provide more information if needed. Please help.
There could be 2 possible reasons for this:
You discovered your application bottleneck. When you add more users the application response time increases therefore throughput decreases. There is a term called saturation point which stands for the maximum performance of the system, if you go beyond this point - the system will respond slower and you will get less TPS than initially. From the application under test side you should take a look into the following areas:
It might be the case your application simply lacks resources (CPU, RAM, Network, etc.), make sure that it has enough headroom to operate using i.e. JMeter PerfMon Plugin
Your application middleware (application server, database, load balancer, etc.) are not properly set up for the high loads. Identify your application infrastructure stack and make sure to follow performance tuning guidelines for each component
It is also possible that your application code needs optimization, you can detect the most time/resource consuming functions, largest objects, slowest DB queries, idle times, etc. using profiling tools
JMeter is not sending requests fast enough
Just like for the application under test check that JMeter machine(s) have enough resources (CPU, RAM, etc.)
Make sure to follow JMeter Best Practices
Consider going for Distributed Testing
Can you please check once CPU and Memory utilization(RAM and java heap utilization) of jmeter load generator while running jemter for 1000 users? If it is higher or reaching to max then it may affect requests/sec. Also just to confirm requests/sec from Jmeter side, can you please add listener in Jmeter script to track Hit/sec or TPS?
This will also be true(8.5K requests in 10 mins test duration) if your API response time is 1 second and also you have provided enough ramp-up time for those 1000 users.
So possible reason is:
You did not provide enough ramp-up time for 1000 users.
Your API average response time is more than 1 second while you performing tests for 1000 users.
Possible workarounds:
First, try to measure the API response time for 1 user.
Then calculate accordingly that how many users you need to reach 8500 requests in 10 mins. Use this formula:
TPS* max response time in second
Give proper ramp-up time for 1000 users. Check this thread to understand how you should calculate ramp-up time.
Check that your load generator is able to generate 1000 users without any memory or health (i.e CPU usage) issues. If requires, try to use distributed architecture.
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
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)
We want to demonstrate that our REST API for a customer can handle 500 concurrent requests. In order to implement this, what is the best way to setup ramp up time ?
Is it 500 requests in 1 sec ?
2500 requests in 5 seconds ?
Any other option ?
With first option, the app and webservers will be flooded. With second option
How should i go about setting this up ?
Appreciate any inputs on this.
Actually performance testing has many different faces, for example:
Load Testing: the process of verifying whether the application under test can handle anticipated load, if you expect 500 users - set 500 threads under Thread Group and configure Ramp-Up period so the load would increase gradually. According to JMeter documentation:
Ramp-up needs to be long enough to avoid too large a work-load at the start of a test, and short enough that the last threads start running before the first ones finish (unless one wants that to happen).
Start with Ramp-up = number of threads and adjust up or down as needed.
So if you have 500 seconds ramp-up time all 500 users will be online in ~8 minutes, after that you can leave test running for some time (i.e. another 500 seconds) and then again gradually (500 more seconds) decrease the load to zero.
This way you will be able to correlate increasing response time (or increasing number of errors) with the increasing load and vice versa.
Soak Testing: basically the same as above, but leave the test running overnight or over the weekend to see how does your application survives the prolonged load. This way you will be able to detect for example memory leaks
Stress Testing: again the same as load testing but don't limit the maximum load to 500 users, gradually increase the load until your application breaks to see how many maximum users it can serve. Then you might also want to gradually descrease the load to see whether it recovers when the load comes back to normal
Spike Testing: this doesn't assume any ramp-up, this way you will test how your application handles 500 users arriving at once
See Why ‘Normal’ Load Testing Isn’t Enough article for more detailed explanation on various performance testing types and why you need to consider all of them.