Execute performance tests using Gatling load testing framework
The following configuration values are required
| Name | Description |
|---|---|
| targetHost | The host where the tests should be executed against |
| targetPort | The port of the target host where the tests should be executed against |
| numberOfUsers | The number of users executing the scenario |
| rampUpTime | The time in seconds to ramp up the defined number of users for the test scenario |
To have the correct server resources like routing rules and acls used for the Gatling tests, the following gradle task should be applied before the tests:
gradlew.bat uploadStaticFiles -PtargetHost=mytargethost -PtargetPort=1234
./gradlew uploadStaticFiles -PtargetHost=mytargethost -PtargetPort=1234
The Gatling simulations can be started with the following command:
gradlew.bat gatling -PtargetHost=mytargethost -PtargetPort=1234
./gradlew gatling -PtargetHost=mytargethost -PtargetPort=1234
The following scenarios described below are implmented in GateleenPerformanceTestSimulation.scala
This scenario is used to prepare the resources for the tests testing gateleens Expansion feature. A single "user" writes 120 json resources to a collection, which later can be requested with the expand parameter.
Description:
Making regular expand requests to the collection prepared in scenario prepareExpandResources. Regular expand requests make another request for each resource in the collection.
Setup:
Taking values from real world applications, Gateleen should be able to server 42'000 requests over a duration of 15 minutes. The tests are configured to use 75% of this load. So the setup is set to:
42'000 requests during 15 minute => 47 req/s * 75% = 35 req/s
Description:
Making storage expand requests to the collection prepared in scenario prepareExpandResources. Storage expand requests make the expansion directly in the storage.
Setup:
Taking values from real world applications, Gateleen should be able to server 42'000 requests over a duration of 20 minutes. The tests are configured to use 75% of this load. So the setup is set to:
42'000 requests during 20 minute => 35 req/s * 75% = 26 reg/s
Making CRUD storage requests. The requests include PUT, GET and DELETE requests for json values.
Description:
Making queued PUT requests.
Setup:
Having 10 users per second over 2 minutes making each 50 requests to a queue result in the following load.
1200 different queueus with 50 queue entries each => 60'000 requests total
The above described scenarios have been tested on the following hardware:
2 cores with the specifications listed below:
vendor_id : GenuineIntel
cpu family : 6
model : 45
model name : Intel(R) Xeon(R) CPU E5-4650L 0 @ 2.60GHz
stepping : 2
microcode : 0x710
cpu MHz : 2599.999
cache size : 20480 KB
physical id : 1
siblings : 4
core id : 3
cpu cores : 4
apicid : 7
initial apicid : 7
fpu : yes
fpu_exception : yes
cpuid level : 13
wp : yes
flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts mmx fxsr sse sse2 ss ht syscall nx rdtscp lm constant_tsc arch_perfmon pebs bts nopl xtopology tsc_reliable nonstop_tsc aperfmperf pni pclmulqdq ssse3 cx16 pcid sse4_1 sse4_2 x2apic popcnt aes xsave avx hypervisor lahf_lm ida arat epb pln pts dtherm
bogomips : 5199.99
clflush size : 64
cache_alignment : 64
address sizes : 40 bits physical, 48 bits virtual