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Before Frankfurt

Until Frankfurt there were 2 tests

  • stability test: vFw (then vFWCL) run continuously
  • resilency test: test when we destroy some pods and retest that the use case vFw is still OK (only up to El Alto)

In frankfurt we also consider the stability of the installation through teh Dialy chains

Guilin

The stability tests considered for the release were:

  • 1 week stability test based on basic_vm
  • 1 day HC verification
  • Daily CI Guilin installation chain

See https://docs.onap.org/projects/onap-integration/en/guilin/integration-s3p.html#integration-s3p

Evolution for Honolulu

In Honolulu we would like to revisit the stability/resiliency testing part by introducing automated tests on CI weekly chain.

It means we want to execute tests over a week to verify the resiliency and the stability of the solution during the development life cycle.

Definition of the KPIs

what do we want to test, which figures? Nb of onboardings / instantiations? test duration//

we estimate our needs to  < to be discussed/commented/challenged/questioned/...>:

  • 10 parallel service onboarding
  • 50 parallel intsantiation
  • ....

Parallel onboarding tests

Description

The goal of this test is to create in parallel several services in the SDC.

We estimate that this number is not very high in the reality of operations because it corresponds to the upload of a new service model, which does not occur frequently.

Environment

Tests executed from 07/01/2021 to 13/01/2021 on a Guilin lab. Reusing the basic_vm with different service names (it means that we recreate all the SDC objects VSP, VF Services).

2 series run several times:

  • 5 simutalneous onboarding
  • 10 simultaneous onboarding

The main component used for this test is the SDC (+AAI).

During the test we monitor the ONAP cluster resources through a prometheus/grafana

<graph grafana memory & CPU générale>

<graph grafana memory & CPU SDC>

Results

Data format is MM:SS

5 parallel onboarding (10 series)

criteria \ Serie12345678910Global
Success rate (%)100100100100100100100100100100100
Min duration27:3910:2410:1510:2611:1807:4207:5408:0508:3508:2007:42
Max duration27:4310:3610:1710:2711:2207:5308:0008:1908:4208:4427:43
Average duration27:4127:4010:1610:2711:2007:4807:5808:1208:3908:4211:09
Median duration27:4110:2610:1610:2711:1907:4907:5908:1308:4008:3809:30
Comments/Errrors/////

/

/////

Evolution of the average duration in seconds over time for series of 5.

10 parallel onboarding (5 series)

criteria \ Serie12345Global
Success rate (%)100100100100100100
Min duration16:0415:2416:3219:4019:0715:24
Max duration16:2217:1017:3620:0119:5020:01
Average duration16:1516:5117:2319:5219:4618:00
Median duration16:2017:0817:3319:5319:3817:33
Comments/Errrors////

/

/

Evolution of the average duration in seconds over time for series of 10.

Evolution of test durations over the campaign for series of 5 (red/first circle) and 10 (green/second circle).

Some insight into ressources consumption .


Databases ressource consumption.

Conclusions

ONAP Guilin is able to support 10 parallel onboarding, which is what we do expect.


The creation of resources is linear. It means that on serie 10, 9 services have been already created. We could have expected a linear increase of the onboarding duration because the client used for test list several times the services.So the more services in SDC, the bigger the list is. So globally the SDC resources increases continuously because we cannot delete them but it has no direct impact on the onboarding duration. The duration evolution is not linear and the duration may depend on the cluster status.

The more // processing we have, the slower the onboarding this.

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