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=== Test Method === | === Test Method === | ||
| - | * The way to get "Rate" is straightforward. | + | * The way to get "Rate" is straightforward. In each test case, sending specified number of workflows(such 3000, 20000...) to BOSS then record the start and end time. Then it's easy to get the "Rate" for that test case. |
| - | === Test | + | === Test Environment === |
| + | * Hardware: CPU E5520(x16 cores), RAM 16G, openSUSE 11.2 | ||
| + | * Virtual Machine: CPU E8400(x1 core), RAM 512M, openSUSE 11.2 | ||
| + | * BOSS packages taken from OBS(https://build.opensuse.org/project/show?project=Maemo%3AMeeGo-Infra%3ABOSS) | ||
| + | |||
| + | === Test Scripts === | ||
We created the test suit(http://gitorious.org/boss-performance-test) including: | We created the test suit(http://gitorious.org/boss-performance-test) including: | ||
* A client to send multiple workflows to BOSS(or to say "launch workflows") at once time. | * A client to send multiple workflows to BOSS(or to say "launch workflows") at once time. | ||
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* An utility to analyze the time data. Here we select the earliest start time and latest end time of all workflows to calculate the whole duration. | * An utility to analyze the time data. Here we select the earliest start time and latest end time of all workflows to calculate the whole duration. | ||
| - | === Test | + | === Test Cases === |
| - | * | + | * Test Case Set 1 |
| - | * | + | In this case set, we test the rates for launching different workflow scales(for N=[several hundreds, ..., several thousands]). Here we also compared the situation of different number of workers. And the CPU/MEM/DISK load is record. |
| - | + | * Raw data and graph | |
[[File:boss_performance_test_0920.PNG]] | [[File:boss_performance_test_0920.PNG]] | ||
| - | + | * CPU/MEM/DISK load for 10k and 20k cases | |
[[File:load_10k.PNG]] | [[File:load_10k.PNG]] | ||
[[File:load_20k.PNG]] | [[File:load_20k.PNG]] | ||
| - | * Here we got the "reponse time" testing results. The way is to launch 1k workflows each time after previous 1k workflows finished. Observing the durations for executing each 1k workflows we can get the response time trend. Following are results on VM and HW | + | * Test Case Set 2 |
| + | Here we got the "reponse time" testing results. The way is to launch 1k workflows each time after previous 1k workflows finished. Observing the durations for executing each 1k workflows we can get the response time trend. Following are results on VM and HW | ||
[[File:Response_1k.PNG]] | [[File:Response_1k.PNG]] | ||
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=== TODO === | === TODO === | ||
| - | |||
| - | |||
| - | |||
| - | |||
| - | |||
* think about why we lost workflows in some cases | * think about why we lost workflows in some cases | ||
* different storage | * different storage | ||
| - | |||
=== Some Thoughts === | === Some Thoughts === | ||
| - | + | * Using more workers can boost performance? | |
| - | * Using more workers can boost performance? | + | * Using multiple engines can boost performance? |
| - | * | + | |
This page is to talk about the way of BOSS performance testing.
Contents |
We created the test suit(http://gitorious.org/boss-performance-test) including:
In this case set, we test the rates for launching different workflow scales(for N=[several hundreds, ..., several thousands]). Here we also compared the situation of different number of workers. And the CPU/MEM/DISK load is record.
* Raw data and graph
* CPU/MEM/DISK load for 10k and 20k cases
Here we got the "reponse time" testing results. The way is to launch 1k workflows each time after previous 1k workflows finished. Observing the durations for executing each 1k workflows we can get the response time trend. Following are results on VM and HW