There’s nothing much that can be inferred from this graph but is useful to find out in case there are failure responses. requestsPerSec: This will target the rate of request per second. ), in the form of either JSON or XML. Each of those requests must contain data for the game (game ID, game name etc. Gatling data in simulation.log file. Selecting the metric. One of those features is :concurrency-distribution. format. Source: I'm one of the guys behind k6. In this case, they are more interested in the rate of requests per second than the number of users. Gatling comes up with a recorder to … The quick command supports some other flags to control how the load will be distributed, like rate, which can be used to define the number of new users per second, or the duration, which defines a fixed time for the test. I need to write Gatling scenario that will mimic real users interaction. By default Gatling works with HTTP Rest requests. time. Conclusion. More is possible, but we didn't push further. From what I see in the docs, constantUsersPerSec accepts double but it's rounded while reachRps in throttling deals only with seconds. Keeping Gatling code maintainable and reusable is a good practice to create complex performance scenarios. gatling. By default it is not possible without creating a custom Gatling Action. It's supposed to issue some requests occasionally, e.g. It generates various types of reports i.e active users along the simulation, response time distribution, response time percentiles over time(OK), number of requests per second & number of responses per second. Gatling gives a complete analysis of each and every request with graphical representation (charts) in HTML files. In our test, the final reports produced by Gatling looks somewhat like this: Picture 1: Gatling reports – endpoint list Gatling default reports also produce a few very useful charts, like the ones below: Picture 2: Gatling reports – overall requests/responses per second The above examples are “real-life” results from iFood platform load tests. The problem you encounter is not the number of requests per second being unreachable by Gatling, it is the number of scenarios started in one second (via the ramp keyword). Since this feature was proposed clj-gatling has got quite a lot of other new features. LocalDate import java. When we only get 14 requests per minute; Gatling reports that the max response time was 1 second. It makes it possible to simulate a high number of requests per second with a single machine. More than 100 requests per second (3) “Less than 1% failed requests” was in fact the only criterion that properly represents a system under load between the three. The number of responses per second. The number of requests per second. Selecting the metrics. //Magnus. It follows our second Gatling Simulation scripts parameterization article. I have very heterogeneous use cases. good and not so good news - the good news is that under moderate load (ie. DateTimeFormatter import io. I am not sure why this would be the case. Response time 50 th percentile is at 506 milliseconds. CPU interrupts per second: The average number of hardware interrupts that a process receives. We ran the same SSL simulation with JMeter with 10 concurrent users and got 10000 requests per minute, so we are pretty confident that Apache isn't the bottleneck. Gatling is a powerful tool: with only a few machines, you can simulate hundreds of thousands of requests per second on your web application and get high-precision metrics. Most problems only arise with higher loads. They allow us to view details of a specific request. We ramped up from 1 to 25 requests per second. I hope all of you readers find this article useful! Gatling is a performance scala library that facilitates running performance tests on your web services/applications. Graph the requests per second and the responses per second, including the comparison of the quantity of active users. That test lasted for 6 min and generated 1.5 billion requests in total. Sign in to view. is it possible to get Gatling to wait more than 60 seconds for a request? Let's be clear that the real number of requests per sec would depend on the time it takes for a user to complete the scenario. Set the number of req/s to a known number (to have a given charge in terms of req/s) or something else? Having a central data feeder was a problem. 10 per hour per user (total 20 users). On the `k6 cloud` side, we have executed 500k+ VUs. Magnus Jensen: 9/22/15 5:41 AM: I have tweaked alle the parameters in gatling.conf that comes with default 60.000 ms to 90.000 but still I get timeout after 60.000. The number of requests per second is 236 – over twice the result we saw with non-persistentsdf connections. How to stress Kafka with thousands of request per second using a Gatling Scala codebase. 50 requests per second) on my MBP the test roughly passes. It is important to put holdFor() method, otherwise, Gatling goes to unlimited requests per second and can crash the server. This will launch 10 virtual users that will do 20 requests each, to the specified URL. Latency against Global RPS – distribution of current request’s latency (process time) related to total request per second of the simulation. is it possible to get Gatling to wait more than 60 seconds for a request? The problem I have then is that I have one request per user, but still the requests per second falls dramatically when max times significantly increase. What it allows you to do is to simulate thousands of requests per second on your web application and get a complete report of the execution, with just a few load generators. The total number of request that we are sending is 5*4*60 = 1200 requests. Miscellaneous Private bytes, page faults, disk queue length, maximum active sessions, network bytes total per second. Gatling calls 20 requests per second, while our service can process 10 requests every 1 second so we accumulate 10 requests in the Tomcat requests queue every second. The original request was redirected and Gatling followed the redirection and sent a second request. Number of requests per second; There are also the charts that do not aggregate information for all requests. Also this had to be done by invoking a few of APIs during the load to simulate varying requests per second (For example: One api is invoked every 5 seconds while another is done every 10 seconds). More details on simulation setup can be found on Gatling Simulation setup page. Showing 1-13 of 13 messages . The report printed to the terminal is not bad, but where Gatling really shines, in my opinion, is the graphical reports it produces. Latency against Global RPS – distribution of current request’s latency (process time) related to total request per second of the simulation. So it looks like Gatling hangs for a long time between making requests. We will continue to load test a fake e-commerce, and so we are going to improve our Virtual User to make it browse the store in a more humanly way. From simple performance regression tests that are executed from a Jenkins node to eventual large-ish stress tests that run with over 100K requests per second and > 100 load generators. Create a new Scala class in the simulations folder, give it a name of CustomFeeder. max: This performs the assertions on the maximum time of the metric. We ran this test for the duration of 3 hours. (iv) Responses per second: Similar to the requests per second, this represents the number of responses that were received per second. The most RPS I achieved with k6 was 4 791 928 (~4.8 million requests per second). With instantaneous values, we can find out what time during the test, there were more failures and vice versa. where beforeRequest is measured before the request is passed to AHC (the async http client atop netty). Components Recorder. We will use a custom feeder to create that data. Gatling implemented a fully new architecture for a performance testing tool, in order to be more resource efficient. Gatling API provides a wide range of functionalities to support this … Let's do it. At the end of your test, Gatling automatically generates an exhaustive, dynamic and colorful report. So they should be adapted too. Latency: Amount of time between a user request and the start of a system’s response. We ran this test for the duration of 3 hours. 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