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All the test projects generate results in different format. The goal of a testing dashboard is to provide a consistent view of the different tests from the different projects.
We may describe the overall system dealing with test and testbeds as follow:
Each test project shall:
The test collection API is under review, it consists in a simple Rest API associated with simple json format collected in a Mongo DB.
A module shall extract the raw results pushed by the test projects to create a testing dashboard. This dashboard shall be able to show:
It shall be possible to filter per:
For each test case we shall be able to see:
And also the severity (to be commonly agreed) of the errors…
description | comment | |
---|---|---|
critical | testcase failed on 80% of the installers? | |
major | ||
minor |
The test projects shall agree on
Based on Arno, related to the result collection API could look like:
test-projects.json (example):
{ "id": 1, "name": "functest", "description":"functional testing for OPNFV. OPNFV seen as a black box." }, { "id": 2, "name": "yardstick", "description":"in VNF testing framework" }, { "id": 3, "name": "qtip", "description":"performance testing framework" }, { "id": 4, "name": "storeperf", "description":"storage performance" }, { "id": 5, "name": "vsperf", "description":"Virtual Switch testing" }
test-functest.json (example):
{ "id":1.1, "name":"vPing", "testproject": "1", "test": "VPing", "description": "Virtual Ping" }, { "id":1.2, "name":"ODL", "testproject": "1", "test": "", "description": "OpenDaylight functional test suite" }, { "id":1.3, "name":"Rally", "testproject": "1", "test": "", "description": "Rally Bench test suites for OpenStack" }, { "id":1.4, "name":"Tempest", "testproject": "1", "test": "", "description": "OpenStack functional test suite" }, ...
test-functest-vping.json (example):
{ "id": "1.1.1", "testcase": "1.1", "timestamp": "1434517568", "platform":"LF1", "global_status":"OK", "hardware_details":"", "installer_type":"Fuel", "version":"Arno R1", "details":{ "full_duration"=31 } }, { "id": "1.1.2", "testcase": "1.1", "timestamp": "1435182906", "platform":"LF2", "global_status":"OK", "hardware_details":"", "installer_type":"Foreman", "version":"Arno R1", "details":{ "full_duration"=102 } }, { "id": "1.1.3", "testcase": "1.1", "timestamp": "1434836687", "platform":"LF2", "global_status":"OK", "hardware_details":"", "installer_type":"Foreman", "version":"Arno R1", "details":{ "full_duration"=116 } },
Functest used to run automatically 4 suites:
The results are available on Jenkins Then we may imagine that functest call the API to store the raw results of each tests. The raw results will be stored in the Mongo DB (json files) A module (to be created) will perform post processing (cron) to generate json file usable for dashboarding (like in bitergia). In the exemple we build json file for LF2 POD (we could do it for the last 30 days, last 365 days, since the beginning)
Such files could look like:
functest-vPing-LF2.json (example):
{ "id": [0, 1, 2, 3, 4, 5, 6, 7 ], "timestamp": [1430987654, 1430987832, 1431234567,1431234999,1432123456,1432184561, 1434836687,1435182906 ], "results":{ "duration": [111, , 100, 103, 101, 122, 105, 116], "status": ["OK", "KO", "OK", "OK", "OK", "OK", "OK", "OK"], } }
functest-tempest-LF2.json (example):
{
"id": [0, 1, 2, 3, 4, 5, 6, 7 ], "timestamp": [1430987654, 1430987832, 1431234567,1431234999,1432123456,1432184561, 1434836687,1435182906 ], "results":{ "nb_tests": [105, 92, 104, 100, , 101, 102, 105], "nb_failures": [32, 34, 41, 32, , 28 , 30 ,29], "duration": [56, 62, 64, 58, , 61, 63, 58], "status": ["OK", "OK", "OK", "OK", "Critical", "OK", "OK", "OK"], } }
functest-odl-LF2.json (example):
{ "id": [0, 1, 2, 3, 4, 5, 6, 7 ], "timestamp": [1430987654, 1430987832, 1431234567,1431234999,1432123456,1432184561, 1434836687,1435182906 ], "results":{ "nb_tests": [18, 18, 18, 18, , 18, 18, 18], "nb_failures": [15, 15, 3, 3, 3 , 3 , 3 ,3], "duration": [23, 25, 18, 19, 18, 20, 18, 18], "status": ["OK", "OK", "OK", "OK", "OK", "OK", "OK", "OK"], } }
functest-rally-LF2.json (example only 2 modules partially used here):
{ "timestamp": [1433279100, 1433279122 ], "id": [0, 1 ], "modules": [ { "module_name": "authenticate", "scenarios": ["keystone", "validate_cinder", "validate_glance", "validate_heat", "validate_neutron" , "validate_nova"], "results": [ { "load_duration": [3.2, 0.95, 1.8, 1, 0.42 , 0.68], "full_duration": [17.1, 6.1, 6.64, 6.68, 5.27, 5.62], "iterations": [100, 10, 10, 10 ,10 ,10], "errors": [0, 0, 0, 0, 0, 0, 0], "sla" : ["OK", "OK","OK","OK","OK","OK" ] }, { "load_duration": [3.1, 1.42, 2.22, 0.91, 0.39 , 0.12], "full_duration": [17.8, 7.6, 8.0, 7.5, 6.0, 6.8], "iterations": [100, 10, 10,10 ,10 ,10], "errors": [0, 0, 0, 0, 0, 0, 0], "sla" : ["OK", "OK","OK","OK","OK","OK" ] } ] }, { "module_name": "neutron", "scenarios": ["create_and_delete_networks", "create_and_delete_ports", "create_and_delete_routers", "create_and_delete_subnets", "create_and_list_networks" , "create_and_list_ports", "create_and_list_routers", "create_and_list_subnets", "create_and_update_networks", "create_and_update_ports", "create_and_update_routers", "create_and_update_subnets"], "results": [ { "load_duration": [4.2, 32.6, 7.0, 7.5, 3.8, 19.4, 13.2, 1.9, 1.3, 4.9, 2.7, 2.1 ], "full_duration": [9.4, 44.2, 20.8, 19.9, 12.69, 83.4, 52.04, 22.2, 8.4, 15.4, 14.6, 23.5], "iterations": [100,100,30,100,100,100,100,10,10,10,10,10], "errors": [43, 16, 7, 33, 44, 17, 31, 1, 2, 2, 5, 1], "sla" : ["OK", "OK","OK","OK","OK","OK","OK","OK","OK","OK","OK","OK" ] }, { "load_duration": [4.0, 32.4, 5.2, 7.6, 3.9, 20.3, 13.7, 2.3, 1.2, 4.69, 3.87, 2.71], "full_duration": [9.2, 43.7, 14.7, 18.2, 13.7, 85.1 ,55.5, 23.9, 9.1, 14.9, 16.3, 23.5], "iterations": [100,100,30,100,100,100,100,10,10,10,10,10], "errors": [35, 19, 11, 26, 46, 14, 28, 2, 3, 4, 3, 2], "sla" : ["OK", "OK","OK","OK","OK","OK","OK","OK","OK","OK","OK","OK" ] }, ] } ] }
Based on these json files, it shall be possible to draw the graphs (e.g with vPing - simplest example only status, duration and timestamp):
Some ideas for discussions: