UPSTREAM: 11480: chore(backend): Fixed namespace in job creation

[hbelmiro]

Cherry-pick from kubeflow#11480

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[openshift-ci]

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[dsp-developers]

Commit Checker results:

**NOTE**: These are the results of the commit checker scans. 
If these are not commits from upstream kfp, then please ensure
you adhere to the commit checker formatting

commitchecker verson unknown
Validating 1 commits between 2969fcac9a590bc26c59ca95a9ed8eacc514b6a3...34bf2f8d6b5b2f35fb3e6ff641e6bda09cb4a24e

[dsp-developers]

A set of new images have been built to help with testing out this PR:
API Server: quay.io/opendatahub/ds-pipelines-api-server:pr-122
DSP DRIVER: quay.io/opendatahub/ds-pipelines-driver:pr-122
DSP LAUNCHER: quay.io/opendatahub/ds-pipelines-launcher:pr-122
Persistence Agent: quay.io/opendatahub/ds-pipelines-persistenceagent:pr-122
Scheduled Workflow Manager: quay.io/opendatahub/ds-pipelines-scheduledworkflow:pr-122
MLMD Server: quay.io/opendatahub/mlmd-grpc-server:latest
MLMD Envoy Proxy: registry.redhat.io/openshift-service-mesh/proxyv2-rhel8:2.3.9-2
UI: quay.io/opendatahub/ds-pipelines-frontend:pr-122

[dsp-developers]

An OCP cluster where you are logged in as cluster admin is required.

The Data Science Pipelines team recommends testing this using the Data Science Pipelines Operator. Check here for more information on using the DSPO.

To use and deploy a DSP stack with these images (assuming the DSPO is deployed), first save the following YAML to a file named dspa.pr-122.yaml:

apiVersion: datasciencepipelinesapplications.opendatahub.io/v1alpha1
kind: DataSciencePipelinesApplication
metadata:
  name: pr-122
spec:
  dspVersion: v2
  apiServer:
    image: "quay.io/opendatahub/ds-pipelines-api-server:pr-122"
    argoDriverImage: "quay.io/opendatahub/ds-pipelines-driver:pr-122"
    argoLauncherImage: "quay.io/opendatahub/ds-pipelines-launcher:pr-122"
  persistenceAgent:
    image: "quay.io/opendatahub/ds-pipelines-persistenceagent:pr-122"
  scheduledWorkflow:
    image: "quay.io/opendatahub/ds-pipelines-scheduledworkflow:pr-122"
  mlmd:  
    deploy: true  # Optional component
    grpc:
      image: "quay.io/opendatahub/mlmd-grpc-server:latest"
    envoy:
      image: "registry.redhat.io/openshift-service-mesh/proxyv2-rhel8:2.3.9-2"
  mlpipelineUI:
    deploy: true  # Optional component 
    image: "quay.io/opendatahub/ds-pipelines-frontend:pr-122"
  objectStorage:
    minio:
      deploy: true
      image: 'quay.io/opendatahub/minio:RELEASE.2019-08-14T20-37-41Z-license-compliance'

Then run the following:

cd $(mktemp -d)
git clone [email protected]:opendatahub-io/data-science-pipelines.git
cd data-science-pipelines/
git fetch origin pull/122/head
git checkout -b pullrequest 34bf2f8d6b5b2f35fb3e6ff641e6bda09cb4a24e
oc apply -f dspa.pr-122.yaml

More instructions here on how to deploy and test a Data Science Pipelines Application.