I ran a JMeter test for 193 samples
where I could see my average response time as 5915ms and Throghput as 1.19832.
I just want to know how are they exactly related
All the answers are in JMeter Glossary
Elapsed time. JMeter measures the elapsed time from just before sending the request to just after the last response has been received.
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).
The relationship is: higher response time - lower throughput and vice versa.
You can use charts like Transactions per Second for throughput and Response Times Over Time for response times to get them plotted on your test timeline and Composite Graph to put them together. This way you will be able to track the trends.
All 3 charts can be installed using JMeter Plugins Manager
TL;DR
No, but yes.
Both aren't related directly, but when increasing Throughput, it will probably affect server response time due to load/stress on server.
If there are timeout errors response time will probably increase.
But for validation or firewall errors - response time will probably decrease.
There's a long explanation in JMeter archive, last is using Disney to demonstrate:
Think of your last trip to disney or your favorite amusement park. Lets define capacity of the ride to be the number of people that can sit on the ride per turn (think roller coaster). Throughput will be the number of people that exit the ride per unit of time. Lets define service time the the amount of time you get to sit on the ride. Lets define response time or latency to be your time queuing for the ride (dead time) plus service time.
In terms of load/Performance testing. Throughput and Response times are inversely proportional. i.e
With increase in response time throughput should decrease.
With increase in Throughput response time should decrease.
You can get more detailed definitions in this blog:
https://nirajrules.wordpress.com/2009/09/17/measuring-performance-response-vs-latency-vs-throughput-vs-load-vs-scalability-vs-stress-vs-robustness/
Throughout increases to some extent and remains stable when all the resources becomes busy. Now, if user requests increases further at this point response time would increase. But if response time increase is only because of internal queuing then due to the fact that system is taking more requests in at the same time response time is also increasing, throughout doesn't change. When queues are full more requests should fail. If response increase is due to some delay in processing or serving the request, for example running a query on database then due to the fact that system is not accepting more request and at the same time response time is also increasing, consequently throughout would drop.
Just a general explaination.
Respose Time : It is the time calculated when user send the request till request gets finnished.
Throughput : It is server property that number of transaction or request can be made during certain amount of time. here 1.19832 /minute means server cand hadle 1.19832 sample per minute.
As Respose Time increses Throughput increases.
Related
I am in confusion here for what is the right parameter to find how many requests my service can handle in a sec..
Eg: According to docs & this post TPS(transactions/sec) is calculated based on elapsed time of the request which seems to be fair when you have one service instance. Eg: My elapsed time is 1 second so my tps is 1 which makes sense, but the calculations fail when i have 3 service instance(H-Scaled) though the elapsed time remains the same but now i can process 3 concurrent requests in that same second which should ideally read back as 3 tps but it doesnt
Q:Then what is the right parameter in jmeter report to check for this ? or is my theory wrong?
As per 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).
And request is something produced by JMeter's Sampler
If you're doing some scalability testing you can measure it as follows:
Run a stress test with 1 service instance, i.e. start with 1 user and gradually increase the load at the same time looking at TPS. At some point you will reach the stage where increasing the number of users won't result in increased TPS due to some bottleneck. Measure the number of users and the TPS just before the bottleneck hits you.
Re-run your test with 3 service instances, you should see that the number of users and TPS before the bottleneck is higher now.
I am testing a scenario with 400 threads. Although I am almost getting no errors, I have very high average response. What can bring about this problem? Seems like server gives no time-out but gives response so late. I've addded the summary report. It is as follows:
This table doesn't tell the full story, if response time seems "so high" to you - this is definitely the bottleneck and you can report it already.
What you can do to localize the problem is:
Consider using a longer ramp-up period, i.e. start with 1 user and add 1 more user every 5 seconds (adjust these numbers according to your scenario) so you would have arrival phase, the "plateau" and the load decrease phase. This approach will allow you to correlate increasing load and increasing response time by looking at Active Threads Over Time and Response Times Over Time charts. This way you will be able to state that:
response time remains the same up to X concurrent users
after X concurrent users it starts growing so throughput is going down
after Z concurrent users response time exceeds acceptable threshold
It would also be good to see CPU, RAM, etc. usage on the server side as increased response time might be due to lack of resources, you can use JMeter PerfMon Plugin for this
Inspect your server configuration as you might need to tune it for high loads (same applies to JMeter, make sure to follow JMeter Best Practices)
Use a profiler tool on server side during the next test execution, it will show you the slowest places in your application code
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
Ok so I ran some stress tests on an application of mine and I came across some weird results compared to last time.
The Throughput was way off although the averages are similar.
The number of Samples did vary, however as I understood the Throughput is calculated by dividing the number of samples by the time it took.
In my understanding if the average time was similar the throughput should be similar even though the samples varied...
This is what I have:
PREVIOUS
RECENT
As you can see the throughput difference is pretty substantial...
Can somebody please explain me if my logic is correct or point me on why that is not the case?
Throughput is the number of requests per unit of time (seconds, minutes, hours) that are sent to your server during the test.
The throughput is the real load processed by your server during a run but it does not tell you anything about the performance of your server during this same run. This is the reason why you need both measures in order to get a real idea about your server’s performance during a run. The response time tells you how fast your server is handling a given load.
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.
Throughput =(number of requests) / (total time).
Average: This is the Average (Arithmetic mean μ = 1/n * Σi=1…n xi) Response time of your total samples.It is the arithmetic mean of all the samples response time.
Response time is the elapsed time from the moment when a given request is sent to the server until the moment when the last bit of information has returned to the client.
So these are two different things.
Think of a trip to Disney or your favorite amusement park. Let's
define the capacity of the ride to be the number of people that can
sit on the ride per turn (think roller coaster). Throughput will
be the number of people that exit the ride per unit of time. Let's
define service time -the amount of time you get to sit on the ride.
Response time to be your time queuing for the ride
plus service time.
How is this possible that in Jmetetr increasing number of users (threads) in my test did not changed the latency (Response time)?
I got the same latency for 100 threads and for 300 threads.
Latency is the difference between the time when a request was sent and time when the response has started to be received.
As per JMeter Glossary
JMeter measures the latency from just before sending the
request to just after the first response has been received. Thus the
time includes all the processing needed to assemble the request as
well as assembling the first part of the response, which in general
will be longer than one byte. Protocol analysers (such as Wireshark)
measure the time when bytes are actually sent/received over the
interface. The JMeter time should be closer to that which is
experienced by a browser or other application client.
Response time (= Sample time = Load time = Elapsed time) is a difference between the time when the request was sent and time when the response has been fully received.
As per JMeter Glossary
JMeter measures the elapsed time from just before sending the request
to just after the last response has been received. JMeter does not
include the time needed to render the response, nor does JMeter
process any client code, for example, Javascript.
So Response time always >= latency.
So it is possible that you may have same Latency for 100 and 300 threads but Response time will be different or increased.
If you have stable network connectivity between JMeter and Application Under Test it is expected that Latency wouldn't change not matter how many threads you kick off. It is "pure" network metric which tells how long did it take for the request to reach to the server.
Check out How to Analyze the Results of a Load Test article to see the impact of Latency for the end user