Installing Release on GCP GKE
This section describes how to install the Release application on GCP GKE.
This guide is intended for administrators with cluster administrator credentials who are responsible for application deployment.
The following are the prerequisites required to install Deploy using Kubernetes Operator installer:
- Docker version 17.03 or later
- Access to a Kubernetes cluster version 1.19 or later
- Kubernetes cluster configuration
- Keycloak is the default authentication manager with Release 22.1 and later.
- This is defined by the
spec.keycloak.installparameter that is set to
trueby default in the
- If you want to disable Keycloak as the default authentication manager for Digitial.ai Release, set the
- After you disable the Keycloak authentication, the default login credentials (
admin/admin) will be applicable when you log in to the Digital.ai Release interface.
- For more information about how to configure Keycloak for Kubernetes Operator-based Installer for Release, see Keycloak Configuration for Kubernetes Operator Installer.
Create a folder on your workstation from where you will execute the installation tasks, for example, ReleaseInstallation.
- Download the release-operator-gcp-gke-22.2.0.zip file from the Release Software Distribution site.
- Extract the ZIP file to the ReleaseInstallation folder.
To deploy the Deploy application on the Kubernetes cluster, update the
infrastructure.yaml file parameters (Infrastructure File Parameters) in DeployInstallation folder with the parameters corresponding to the
kubeconfig file (GCP GKE Kubernetes Cluster Configuration File Parameters) as described in the table below. You can find the Kubernetes cluster information in the default location
~/.kube/config. Ensure the location of the
kubeconfig configuration file is your home directory.
Note: The deployment will not proceed further if the
infrastructure.yaml is updated with wrong details.
|Infrastructure File Parameters||GCP GKE Kubernetes Cluster Configuration File Parameters||Steps to Follow|
|apiServerURL||server||Enter the server details of the cluster.|
|caCert||certificate-authority-data||Before updating the parameter value, decode to base 64 format.|
|token||access token||Enter the access token details.|
Run the following command to get the storage class list:
kubectl get sc
- Convert the Release license and the repository keystore files to the base 64 format.
- Run the following commands:
To convert the xlrLicense into base 64 format, run:
cat <License.lic> | base64 -w 0
RepositoryKeystoreto base64 format, run:
cat <keystore.jks> | base64 -w 0
Note: The above commands are for Linux-based systems. For Windows, there is no built-in command to directly perform Base64 encoding and decoding. But you can use the built-in command
certutil -encode/-decodeto indirectly perform Base64 encoding and decoding.
Update the mandatory parameters as described in the following table:
Note: For deployments on test environments, you can use most of the parameters with their default values in the
Parameter Description AdminPassword Admin password for xl-release KeystorePassphrase The passphrase for the RepositoryKeystore. Persistence.StorageClass The storage class that must be defined as GKE cluster RepositoryKeystore Convert the repository keystore file for Digital.ai Release to the base64 format. ingress.hosts DNS name for accessing UI of Digital.ai Release. postgresql.persistence.storageClass The storage Class that needs to be defined as PostgreSQL rabbitmq.persistence.storageClass The storage class that must be defined as RabbitMQ xlrLicense Release license
Note: For deployments on production environments, you must configure all the relevant/required parameters for your GCP GKE production setup, in the
dairelease_cr.yamlfile. See Default Parameters to know more about the parameters available in the Digital.ai release’s
dairelease_cr.yamlfile and their default values. You must update the default values for the parameters per your requirements.
To configure the Keycloak parameters for OIDC authentication, see Keycloak Configuration for Kubernetes Operator Installer.
Update the relevant/required parameters for your GCP GKE production setup in the
dairelease_cr.yamlfile. See Default Parameters.
If you want to use your own database and messaging queue, refer Using Existing DB and Using Existing MQ topics, and update the
daideploy_cr.yamlfile. For information on how to configure SSL/TLS with Digital.ai Release, see Configuring SSL/TLS.
Check following link for details: Install the XL-CLI
Note: Use the version that matches your product version in the public folder.
You can use any namespace for the installation. By default, digitalai namespace is used.
First you need to create namespace, replace
digitalai with your custom name if you would like to use some other name:
kubectl create namespace digitalai
In case you are not using
digitalai as namespace or if you would like to install multiple release instances on the same cluster you need to use custom namespace setup.
Got to the following document to see how to install the release operator to use custom namespace.
Run the following command to download and start the Digital.ai Deploy instance:
Note: A local instance of Digital.ai Deploy is used to automate the product installation on the Kubernetes cluster.
docker run -d -e "ADMIN_PASSWORD=admin" -e "ACCEPT_EULA=Y" -p 4516:4516 --name xld xebialabs/xl-deploy:22.2.0
Note: Before running the command check if there is already running docker containers with name
xldor the same port with
docker pscommand. Stop and delete the container with commands, for example with name
docker stop xld; doecker rm xld.
- Wait Deploy has started and access the Deploy interface, go to:
http://<host IP address>:4516/
Go to the
release-operator-gcp-gke folder of the extracted ZIP file and run the following command:
xl apply -v -f digital-ai.yaml
Check the deployment job completion using XL CLI.
The deployment job starts the execution of various tasks as defined in the
digital-ai.yamlfile in a sequential manner. If you encounter an execution error while running the scripts, the system displays error messages. The average time to complete the job is around 10 minutes.
Note: The runtime depends on the environment.
To troubleshoot runtime errors, see Troubleshooting Operator Based Installer.
Verify the deployment succeeded, do one of the following:
Open the local Deploy application, go to the Explorer tab, and from Library, click Monitoring > Deployment tasks
Run the following command in a terminal or command prompt:
Open the Release application and perform the required deployment sanity checks.
- After the installation, you must configure the user permissions for OIDC authentication using Keycloak.
- For more information about how to configure the user permissions, see Keycloak Configuration for Kubernetes Operator Installer.
- If you need to update some of the default properties, see apply changes in the CR.