I made a TPS graph using jmeter, but I can't interpret what it means. Please tell me how to interpret the graph
request of type get named "A"
threads: 1000
ramp-up period: 100
loop Count: 1
Active Threads Over Time
1. image
Response Times Over Time
2. image
Transactions per Second
3. image
Your graphs mean that:
You run 1 thread (virtual user)
You can reach 10 transactions per second with this 1 thread
Average response time is around 100 milliseconds
You might also be interested in:
Apache JMeter HTML Reporting Dashboard - an alternative and automated way of generating pretty zoomable charts
Apache JMeter Glossary - so you would understand what do your metrics mean in general
Performance Metrics for Websites - so you would understand how to correlate the metrics and what are possible relationships between them
Related
In Pagespeed insights, I get the following message in Origin Summary: "Over the previous 28-day collection period, the aggregate experience of all pages served from this origin does not pass the Core Web Vitals assessment."
screenshot of the message in PageSpeed Insights
Does anyone know what % of URLs have to pass the test in order to change this? Or what the criteria is?
Explanation
Lets use Largest Contentful Paint (LCP) as an example.
Firstly, the pass / fail is not based on the percentage of URLs, it is based on the average time / score.
This is an important distinction as you could have 50% of the data fail, but if it only fails by 0.1s (2.6s) and the other 50% of data is passing by 1 second (1.5s) the average will be a pass (average of 2.05s which is a pass).
Obviously this is an over-simplified example but you hopefully get the idea that you could have 50% of your site in the red and still pass in theory, which is why the percentages in each category are more for diagnostics.
If the average time for LCP across all pages in the CrUX dataset is less than 2.5 seconds ("Good") then you will get a green score and that is a pass.
If the time is less than 4 seconds the score will be orange ("Needs improvement") but this will still count as a fail.
Over 4 seconds and it fails and will be red ("Poor").
Passing criteria
So you need the following to be true to pass the web vitals (at time of writing):-
Largest Contentful Paint (LCP) average is less than 2.5 seconds
First Input Delay (FID) is less than 100ms
Cumulative Layout Shift is less than 0.1
If any one of those is over the threshold you will fail, even if the other two are within the green / passes.
FID - when running lighthouse (or Page Speed Insights) on a page you do not get the FID as part of the synthetic test (Lab Data).
Instead you get Total Blocking Time (TBT) - this is a close enough approximation for FID in most circumstances so use that (or run a performance trace).
I'm trying to measure a online mini-batch processing system with a per-second metrics (total query per second). For every batch, a metric (e.g. "stats.gauges.<host>.query.count") will be send to graphite. batches are processed in several different hosts in parallel and a batch of data take about 5 seconds to process.
I've tried:
simply sum series: sumSeries(stats.gauges.*.query.count),
the result metrics is many times greater than the actual value;
scale to 1 second:
scaleToSeconds(sumSeries(stats.gauges.*.query.count),
1), the result metrics is much less than the actual value;
integral then derivative: nonNegativeDerivative(sumSeries(integral(stats.gauges.*.query.count))), same as the first case ...
send gauges with
delta=True param, then derivative. the result is about 20% greater
than the actual value
so, how to get per-second metrics from batch metrics? what is the best practice?
You should use carbon-aggregator service to add several metrics together as they come in. There is an example which fits your case at http://graphite.readthedocs.io/en/latest/config-carbon.html#aggregation-rules-conf
As your batch takes 5 secs to process, frequency should be 5 to buffer all the metrics. After five seconds, aggregator will sum them up and write to graphite.
I am trying to understand the "Graph Result" in JMeter I got when I followed the following scenario:
I am hitting www.google.com with:
No. of users: 10,
Ramp up Period is 5 Seconds,
Loop count is 10
I am finding it difficult to read "Graph Result", I have used another listeners too (View Results in Tree, View Results in Table, Summary Report) which are easy to understand but I would like to learn this too.
Please refer the result Image link:
https://www.cubbyusercontent.com/pli/Image.png/_2855385a0bbb40a0b7cd2d31224b521c
Help appreciated.
According to JMeter Help,
Graph results contains,
The Graph Results listener generates a simple graph that plots all
sample times. Along the bottom of the graph, the current sample
(black), the current average of all samples(blue), the current
standard deviation (red), and the current throughput rate (green) are
displayed in milliseconds.
The throughput number represents the actual number of requests/minute
the server handled. This calculation includes any delays you added to
your test and JMeter's own internal processing time.
Basically it shows data,average,median,deviation,throughput i.e.system statistics during test in a graphical format.
These values are plotted runtime thus it updates values at bottom at runtime i.e. total no. of samples are no. of samples occurred till that point of time with deviation at that point of time and similarly other counters represent their values.
Due to its runtime behavior, this listener consumes lot of memory and cpu and it is advised that it should not be used while load test (I think you have used it just to know its use and working.)
While running actual load test you can learn/understand these statistics from aggregate report other reports which can be created in non-ui mode also.
I hope this have cleared what graph result shows and how to read it and when to use it.
I have a requirement where I need to send HTTP requests to large number of small files (probably many 100 thousands) and I am trying to find an efficient way to create a large nuumber of HTTP Samplers under a thread group.
Is there a way to automate this so that I can create a request in such a way that
http:///folder[index]/file[index]
index can vary from 0..500000
I would like to pump the traffic with GETs on this request.
I believe that JMeter Functions is something which can help you in implementing your scenario.
If that index bit can be a random value in range from zero to 500000 amend your request as follows to use __Random function:
http://folder${__Random(0,500000,)}/file${__Random(0,500000,)}
If you want the index to be consecutive, i.e.
1st request - index=1
2nd request - index=2
etc.
Then __counter function is your friend and path stanza should be something like:
http://folder${__counter(,)}/file${__counter(,)}
See How to Use JMeter Functions post series for more details on the most popular JMeter functions.
How is a load test different from a Spike test, Considering the below scenarios.
Load test: Using an automation tool(JMeter in my case) I create a load of 1000 virtual users loaded in 1 sec(ramp up period).
Spike test: Using an automation tool(JMeter in my case) I create a continuous load of 400 virtual users loaded every 1 sec and a spike load of 600 virtual users loaded in 1 sec at a certain point in time.
When there is a spike load induced is it not the same as a load test described?
So my point is what is the need of a spike test if load tests can be carried out continuously at varied load conditions?
Test scenario:
Application tested : Website.
Automation tool : Jmeter.
Speed of internet used while testing: 3 MBPS.
I`m thanking you all in advance.
According to "Performance Testing Guidance for Web Applications", "spike testis a type of performance test focused on determining or validating performance characteristics of the product under test when subjected to workload models and load volumes that repeatedly increase beyond anticipated production operations for short periods of time.". So I think about analogy with Geometric or Algebraic progression, because volumes are repeatedly (and rapidly) increased. Also this and other definitions are paying attention to short period of time.
Load testing is more general term, without specified time (short or long) of testing or pattern to increase load volumes.
Load Testing: It helps us to know how much load a application/System can bear at a point of time.
Ex: Let a normal man can drink Maximum 3lt water at a time.
spike testing: It helps us to know the behaviour of a system by giving suddenly high amount of load.
Ex: For spike testing we try to know whether a normal man can drink 4lt or more at a time?
A spike test is a kind of load test, used to simulate bursty traffic patterns.
For example, you might want to support 1 million client requests an hour. That's an average of 277 requests/sec. However, that doesn't account for varying usage patterns, like a sudden burst of traffic followed by a lull period. A spike test would simulate these bursts, where the short-term request rate can be much higher or lower than the expected average.