Skip to content

ai.md

Latest commit

 

History

History
123 lines (99 loc) · 5.46 KB

ai.md

File metadata and controls

123 lines (99 loc) · 5.46 KB

Deploy an Artificial Intelligence Microservice

  1. Prerequisites

  2. Instructor will provide the following info:

    • OpenShift Console URL (OCP_CONSOLE_URL)
    • The username and password for OpenShift and Git Server (default values are user1, user2, etc.. for users and password for password).

  3. Set TOOLKIT_USERNAME environment variable. If you are participation in a workshop replace userdemo with your assigned username (ex. user01).

    TOOLKIT_USERNAME=userdemo

  4. (Skip if using KubeAdmin or IBM Cloud) Login to OpenShift using oc

    • If using IBM Cloud cluster then login with your IBM account email and IAM API Key or Token by using the Copy Login Command Login
    • If using a cluster that was configured with the workshop scripts outside IBM Cloud then use respective assigned username (ex. user01), and the password is password
    oc login $OCP_URL -u $TOOLKIT_USERNAME -p password

  5. Set TOOLKIT_PROJECT environment variable If you are participation in a workshop replace projectdemo based on your assigned username (ex. project01).

    TOOLKIT_PROJECT=projectdemo

  6. Create a project/namespace using your project as prefix, and -dev and suffix

    oc sync $TOOLKIT_PROJECT-dev

  7. Fork application template git repo

    • Open Developer Dashboard from the OpenShift Console Developer Dashboard{.center}
    • Select Starter Kits Starter Kits{.center}
    • Select One in our case Artificial Intelligence Microservice
    • Click Fork
    • Login into GIT Sever using the provided username and password (ie userdemo and password)
    • Click Fork Repository

  8. Setup environment variable GIT_URL for the git url using the value from previous step or as following. Note: We are including username/password in git url for simplicity of this lab. You would NOT want to do this in your development environment.

    GIT_REPO=ai-model-object-detector
GIT_URL=http://${TOOLKIT_USERNAME}:password@$(oc get route -n tools gitea --template='{{.spec.host}}')/${TOOLKIT_USERNAME}/${GIT_REPO}
echo GIT_URL=${GIT_URL}

  9. Clone the git repository and change directory

    cd $HOME
git clone $GIT_URL app
cd app

  10. Create a Tekton pipeline for the application

    oc pipeline --tekton
    • Use down/up arrow and select ibm-general
    • Enter n and hit Enter to disable image scanning
    • Hit Enter to enable Dockerfile linting
    • Hit Enter to select default health endpoint /
    • Open the url to see the pipeline running in the OpenShift Console

  11. Verify that Pipeline Run completed successfully

    • On the OpenShift web console select Pipelines
    • At the top of the page select your development project/namespace created above (ex. project01-dev)
    • The app pipeline last run status should be Succeeded Pipeline Run{.center}

  12. Review the Pipeline Tasks/Stages.

    • Click on the last run Last pipeline run{.center}
    • Click on the Test task and view the logs Test task{.center}
    • Open SonarQube from Console Link
    • Open Registry from Console Link
    • Open Artifactory from Console Link

  13. The gitops step of the pipeline triggers Argo CD to deploy the app to QA. Select Developer perspective, select project $TOOLKIT_PROJECT-qa and then select Topology from the Console and verify the application running Last pipeline run{.center}

  14. Open the application route url and try out the application using the swagger UI or append /app to the URL to load Web UI for the Application. You can download the this sample picture to test the app open url{.center} ai app{.center}

  15. Make a change to the application in the git repository and see the pipeline running again from the Console. Lets change the Machine Learning being used from ssd_mobilenet_v1 to faster_rcnn_resnet101

    git config --local user.email "${TOOLKIT_USERNAME}@example.com"
git config --local user.name "${TOOLKIT_USERNAME}"
sed -i 's/ssd_mobilenet_v1/faster_rcnn_resnet101/' Dockerfile
git add .
git commit -m "update model"
git push -u origin master

  16. Verify that change in Git Server and Git WebHook

    • Open Git Dev from Console Link
    • Navigate to user app git repository
    • Review the recent commit
    • Review the webhook recent delivery webhook{.center}

  17. Verify that a new Pipeline starts successfully

  18. Verify that the App manifests are being updated in the gitops repo in the git account toolkit under the qa directory.

    • Open Git Ops from Console Link
    • Select toolkit/gitops git repository gitops{.center}

  19. Congratulations you finished this lab, continue with lab Promote an Application using CD with GitOps and ArgoCD