Installing Deploy Using Kubernetes Operator

This section describes how to install the Deploy application on various Kubernetes platforms.

Supported Platforms

Intended Audience

This guide is intended for administrators with cluster administrator credentials who are responsible for application deployment.

Before You Begin

The following are the prerequisites required to migrate to the operator-based deployment:

  • Docker version 17.03 or later
  • The kubectl command-line tool
  • Access to a Kubernetes cluster version 1.17 or later
  • Kubernetes cluster configuration
  • If you are installing Deploy on OpenShift cluster, you will need:

    • The OpenShift oc tool
    • Access to an OpenShift cluster version 4.5 or later

Installing Deploy on Amazon EKS

Follow the steps below to install Deploy on Amazon Elastic Kubernetes Service (EKS).

Step 1—Create a folder for installation tasks

Create a folder on your workstation from where you will execute the installation tasks, for example, DeployInstallation.

Step 2—Download the Operator ZIP

  1. Download the deploy-operator-aws-eks-10.3.zip file from the Deploy/Release Software Distribution site.
  2. Extract the ZIP file to the DeployInstallation folder.

Step 3—Update the Amazon EKS cluster information

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 (Amazon EKS 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 Amazon EKS Kubernetes Cluster Configuration File Parameters Parameter Value
apiServerURL server Enter the server details of the cluster.
caCert certificate-authority-data Before updating the parameter value, decode to base64 format.
regionName Region Enter the AWS Region.
clusterName cluster-name Enter the name of the cluster.
accessKey NA This parameter defines the access key that allows the Identity and Access (IAM) user to access the AWS using CLI.
Note: This parameter is not available in the Kubernetes configuration file.
accessSecret NA This parameter defines the secret password that the IAM user must enter to access the AWS using.
Note: This parameter is not available in the Kubernetes configuration file.

Step 4—Update the default Custom Resource Definitions

  1. Run the following command to get the storage class list:

    kubectl get sc
  2. Run the keytool command below to generate the RepositoryKeystore:

    keytool -genseckey {-alias alias} {-keyalg keyalg} {-keysize keysize} [-keypass keypass] {-storetype storetype} {-keystore keystore} [-storepass storepass]

    Example

    keytool -genseckey -alias deployit-passsword-key -keyalg aes -keysize128 -keypass deployit -keystore /tmp/repository-keystore.jceks -storetype jceks -storepass test123
  3. Convert the Release license and the repository keystore files to the base64 format:

    • To convert the xldLicense into base64 format, run:

      cat <License.lic> | base64 -w 0
    • To convert RepositoryKeystore to base64 format, run:

      cat <repository-keystore.jceks> | 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. However, you can use the built-in command certutil -encode/-decode to indirectly perform Base64 encoding and decoding.

  4. Update daideploy_cr file with 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 daideploy_cr.yaml file.

    Parameter Description
    KeystorePassphrase The passphrase for the RepositoryKeystore.
    Persistence.StorageClass The storage class that must be defined as Amazon EKS cluster
    RepositoryKeystore Convert the repository keystore file for Digital.ai Deploy to the base64 format.
    ingress.hosts DNS name for accessing UI of Digital.ai Deploy.
    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
    xldLicense Deploy license

    Note: For deployments on production environments, you must configure all the parameters required for your Amazon EKS production setup in the daideploy_cr.yaml file. The table in Step 4.5 lists these parameters and their default values, which can be overridden as per your setup requirements and workload. You can override the default parameters, and specify the parameter values as per your requirements.

  5. Update the default parameters as described in the Default Parameters table:

    Note: The following table describes the default parameters in the Digital.ai daideploy_cr.yaml file. 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.yaml file. For information on how to configure SSL/TLS with Digital.ai Deploy, see Configuring SSL/TLS.

Click to expand the Default Parameters table
Parameter Description Default
K8sSetup.Platform The platform on which you install the chart. Allowed values are PlainK8s and AWSEKS AWSEKS
XldMasterCount Number of master replicas 3
XldWorkerCount Number of worker replicas 3
ImageRepository Image name xebialabs/xl-deploy
ImageTag Image tag 10.2
ImagePullPolicy Image pull policy, Defaults to Always if image tag is latest, set to IfNotPresent Always
ImagePullSecret Specify docker-registry secret names. Secrets must be manually created in the namespace None
haproxy-ingress.install Install haproxy subchart. If you have haproxy already installed, set install to false FALSE
haproxy-ingress.controller.kind Type of deployment, DaemonSet or Deployment Deployment
haproxy-ingress.controller.service.type Kubernetes Service type for haproxy. It can be changed to LoadBalancer or NodePort LoadBalancer
ingress.Enabled Exposes HTTP and HTTPS routes from outside the cluster to services within the cluster TRUE
ingress.annotations Annotations for Ingress controller kubernetes.io/ingress.class: nginx
nginx.ingress.kubernetes.io/affinity: cookie
nginx.ingress.kubernetes.io/proxy-connect-timeout: “60”
nginx.ingress.kubernetes.io/proxy-read-timeout: “60”
nginx.ingress.kubernetes.io/proxy-send-timeout: “60”
nginx.ingress.kubernetes.io/rewrite-target: /$2
nginx.ingress.kubernetes.io/session-cookie-name: SESSION_XLD
nginx.ingress.kubernetes.io/ssl-redirect: “false”
ingress.path You can route an Ingress to different Services based on the path /xl-deploy(/|$)(.*)
ingress.hosts DNS name for accessing ui of Digital.ai Deploy None
AdminPassword Admin password for xl-deploy admin
xldLicense Convert xl-deploy.lic files content to base64 None
RepositoryKeystore Convert repository-keystore.jceks files content to base64 None
KeystorePassphrase Passphrase for repository-keystore.jceks file None
Resources CPU/Memory resource requests/limits. User can change the parameter accordingly. None
postgresql.install postgresql chart with single instance. Install postgresql chart. If you have an existing database deployment, set install to false. TRUE
postgresql.postgresqlUsername PostgreSQL user (creates a non-admin user when postgresqlUsername is not specified as postgres) postgres
postgresql.postgresqlPassword PostgreSQL user password postgres
postgresql.postgresqlExtendedConf.listenAddresses Specifies the TCP/IP address(es) on which the server is to listen for connections from client applications *
postgresql.postgresqlExtendedConf.maxConnections Maximum total connections 500
postgresql.initdbScriptsSecret Secret with initdb scripts contain sensitive information
Note: This parameter can be used with initdbScriptsConfigMap or initdbScripts. The value is evaluated as a template.
postgresql-init-sql-xld
postgresql.service.port PostgreSQL port 5432
postgresql.persistence.enabled Enable persistence using PVC TRUE
postgresql.persistence.size PVC Storage Request for PostgreSQL volume 50Gi
postgresql.persistence.existingClaim Provide an existing PersistentVolumeClaim, the value is evaluated as a template. None
postgresql.resources.requests CPU/Memory resource requests requests: memory: 250m memory: cpu: 256m
postgresql.nodeSelector Node labels for pod assignment {}
postgresql.affinity Affinity labels for pod assignment {}
postgresql.tolerations Toleration labels for pod assignment []
UseExistingDB.Enabled If you want to use an existing database, change postgresql.install to false. FALSE
UseExistingDB.XLDBURL Database URL for xl-deploy None
UseExistingDB.XLDBUSERNAME Database User for xl-deploy None
UseExistingDB.XLDBPASSWORD Database Password for xl-deploy None
rabbitmq.install Install rabbitmq chart. If you have an existing message queue deployment, set install to false. TRUE
rabbitmq.extraPlugins Additional plugins to add to the default configmap rabbitmqjmstopic_exchange
rabbitmq.replicaCount Number of replica 3
rabbitmq.rbac.create If true, create and use RBAC resources TRUE
rabbitmq.service.type Type of service to create ClusterIP
UseExistingMQ.Enabled If you want to use an existing Message Queue, change rabbitmq-ha.install to false FALSE
UseExistingMQ.XLDTASKQUEUE_USERNAME Username for xl-deploy task queue None
UseExistingMQ.XLDTASKQUEUE_PASSWORD Password for xl-deploy task queue None
UseExistingMQ.XLDTASKQUEUE_URL URL for xl-deploy task queue None
UseExistingMQ.XLDTASKQUEUEDRIVERCLASS_NAME Driver Class Name for xl-deploy task queue None
HealthProbes Would you like a HealthProbes to be enabled TRUE
HealthProbesLivenessTimeout Delay before liveness probe is initiated 60
HealthProbesReadinessTimeout Delay before readiness probe is initiated 60
HealthProbeFailureThreshold Minimum consecutive failures for the probe to be considered failed after having succeeded 12
HealthPeriodScans How often to perform the probe 10
nodeSelector Node labels for pod assignment {}
tolerations Toleration labels for pod assignment []
Persistence.Enabled Enable persistence using PVC TRUE
Persistence.StorageClass PVC Storage Class for volume None
Persistence.Annotations Annotations for the PVC {}
Persistence.AccessMode PVC Access Mode for volume ReadWriteOnce
Persistence. XldMasterPvcSize XLD Master PVC Storage Request for volume. For production grade setup, size must be changed 10Gi
Persistence. XldWorkerPvcSize XLD Worker PVC Storage Request for volume. For production grade setup, size must be changed 10Gi

Step 5—Download and set up the XL CLI

  1. Download the XL-CLI binaries.

    wget https://dist.xebialabs.com/public/xl-cli/$VERSION/linux-amd64/xl

    Note: For $VERSION, substitute with the version that matches your product version in the public folder.

  2. Enable execute permissions.

    chmod +x xl
  3. Copy the XL binary in a directory that is on your PATH.

    echo $PATH

    Example

    cp xl /usr/local/bin
  4. Verify the release version.

    xl version

Step 6—Set up the XL Deploy Container instance

  1. Run the following command to download and start the Digital.ai Deploy instance:

    docker run -d -e "ADMIN_PASSWORD=admin" -e "ACCEPT_EULA=Y" -p 4516:4516 --name xld xebialabs/xl-deploy:10.2
  2. To access the Deploy interface, go to:
    http://<host IP address>:4516/

Step 7—Activate the deployment process

Go to the root of the extracted file and run the following command:

xl apply -v -f digital-ai.yaml

Step 8—Verify the deployment status

  1. Check the deployment job completion using XL CLI.
    The deployment job starts the execution of various tasks as defined in the digital-ai.yaml file 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.

Deployment Status

To troubleshoot runtime errors, see Troubleshooting Operator Based Installer.

Step 9—Verify if the deployment was successful

To verify the deployment succeeded, do one of the following:

  • Open the Deploy application, go to the Explorer tab, and from Library, click Monitoring > Deployment tasks

Successful Deploy Deployment

  • Run the following command in a terminal or command prompt:

Deployment Verification Using CLI Command

Step 10—Perform sanity checks

Open the newly installed Deploy application and perform the required sanity checks.

Installing Deploy on Azure Kubernetes Service

Follow the steps below to install Deploy on Azure Kubernetes Service (AKS) cluster.

Step 1—Create a folder for installation tasks

Create a folder on your workstation from where you will execute the installation tasks, for example, DeployInstallation.

Step 2—Download the Operator ZIP

  1. Download the deploy-operator-azure-aks-10.3.zip from the Deploy/Release Software Distribution site.
  2. Extract the ZIP file to the DeployInstallation folder.

Step 3—Update the Azure AKS Cluster Information

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 (AWS EKS 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 Azure AKS 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.
tlsCert client-certificate-data Before updating the parameter value, decode to base 64 format.
tlsPrivateKey client-key-data Before updating the parameter value, decode to base 64 format.

Step 4—Update the default Digitial.ai Deploy Custom Resource Definitions.

  1. Run the following command to get the storage class list:

    kubectl get sc
  2. Run the keytool command below to generate the RepositoryKeystore:

    keytool -genseckey {-alias alias} {-keyalg keyalg} {-keysize keysize} [-keypass keypass] {-storetype storetype} {-keystore keystore} [-storepass storepass]

    Example

    keytool -genseckey -alias deployit-passsword-key -keyalg aes -keysize128 -keypass deployit -keystore /tmp/repository-keystore.jceks -storetype jceks -storepass test123
  3. Convert the Release license and the repository keystore files to the base64 format:

    • To convert the xldLicense into base64 format, run:

      cat <License.lic> | base64 -w 0
    • To convert RepositoryKeystore to base64 format, run:

      cat <repository-keystore.jceks> | 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. However, you can use the built-in command certutil -encode/-decode to indirectly perform Base64 encoding and decoding.

  4. 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 daideploy_cr.yaml file.

    Parameter Description
    KeystorePassphrase The passphrase for the RepositoryKeystore.
    Persistence.StorageClass The storage class that must be defined as Azure AKS cluster.
    ingress.hosts DNS name for accessing UI of Digital.ai Deploy.
    RepositoryKeystore Convert the license file for Digital.ai Deploy to the base64 format.
    postgresql.persistence.storageClass Storage Class to be defined as PostgreSQL.
    rabbitmq.persistence.storageClass Storage Class to be defined as RabbitMQ.
    xldLicense Deploy license

    Note: For deployments on production environments, you must configure all the parameters required for your Azure AKS production setup in the daideploy_cr.yaml file. The table in Step 4.5 lists these parameters and their default values, which can be overridden as per your setup requirements and workload. You must override the default parameters, and specify the parameter values with those from the custom resource file. The following table describes the parameters and their default values.

  5. Update the default parameters as described in the Default Parameters table:

    Note: The following table describes the default parameters in the Digital.ai daideploy_cr.yaml file. 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.yaml file. For information on how to configure SSL/TLS with Digital.ai Deploy, see Configuring SSL/TLS.

Click to expand the Default Parameters table
Parameter
Description Default
K8sSetup.Platform Platform on which to install the chart. Allowed values are PlainK8s and AzureAKS AzureAKS
XldMasterCount Number of master replicas 3
XldWorkerCount Number of worker replicas 3
ImageRepository Image name xebialabs/xl-deploy
ImageTag Image tag 10.2
ImagePullPolicy Image pull policy, Defaults to Always if image tag is latest,set to IfNotPresent Always
ImagePullSecret Specify docker-registry secret names. Secrets must be manually created in the namespace NA
haproxy-ingress.install Install haproxy subchart. If you have haproxy already installed, set install to false FALSE
haproxy-ingress.controller.kind Type of deployment, DaemonSet or Deployment Deployment
haproxy-ingress.controller.service.type Kubernetes Service type for haproxy. It can be changed to LoadBalancer or NodePort LoadBalancer
ingress.Enabled Exposes HTTP and HTTPS routes from outside the cluster to services within the cluster TRUE
ingress.annotations Annotations for ingress controller kubernetes.io/ingress.class: nginx
nginx.ingress.kubernetes.io/affinity: cookie
nginx.ingress.kubernetes.io/proxy-connect-timeout: “60”
nginx.ingress.kubernetes.io/proxy-read-timeout: “60”
nginx.ingress.kubernetes.io/proxy-send-timeout: “60”
nginx.ingress.kubernetes.io/rewrite-target: /$2
nginx.ingress.kubernetes.io/session-cookie-name: SESSION_XLD
nginx.ingress.kubernetes.io/ssl-redirect: “false”
ingress.path You can route an Ingress to different Services based on the path /xl-deploy(/
AdminPassword Admin password for xl-deploy Admin
resources CPU/Memory resource requests/limits. User can change the parameter accordingly NA
postgresql.install postgresql chart with single instance. Install postgresql chart. If you have an existing database deployment, set install to false. TRUE
postgresql.postgresqlUsername PostgreSQL user (creates a non-admin user when postgresqlUsername is not postgres) postgres
postgresql.postgresqlPassword PostgreSQL user password postgres
postgresql.postgresqlExtendedConf.listenAddresses Specifies the TCP/IP address(es) on which the server is to listen for connections from client applications *
postgresql.postgresqlExtendedConf.maxConnections Maximum total connections 500
postgresql.initdbScriptsSecret Secret with initdb scripts contain sensitive information
Note: This parameter can be used with initdbScriptsConfigMap or initdbScripts. The value is evaluated as a template.
postgresql-init-sql-xld
postgresql.service.port PostgreSQL port 5432
postgresql.persistence.enabled Enable persistence using PVC TRUE
postgresql.persistence.size PVC Storage Request for PostgreSQL volume. 50 Gi
postgresql.persistence.existingClaim Provides an existing PersistentVolumeClaim, the value is evaluated as a template. NA
postgresql.resources.requests CPU/Memory resource requests requests: memory: 250m memory: cpu: 256m
postgresql.nodeSelector Node labels for pod assignment {}
postgresql.affinity Affinity labels for pod assignment {}
postgresql.tolerations Toleration labels for pod assignment []
UseExistingDB.Enabled If you want to use an existing database, change postgresql.install to false. FALSE
UseExistingDB.XL_DB_URL Database URL for xl-deploy NA
UseExistingDB.XL_DB_USERNAME Database User for xl-deploy NA
UseExistingDB.XL_DB_PASSWORD Database Password for xl-deploy NA
rabbitmq.install Install rabbitmq chart. If you have an existing message queue deployment, set install to false. TRUE
rabbitmq.extraPlugins Additional plugins to add to the default configmap rabbitmqjmstopic_exchange
rabbitmq.replicaCount Number of replicas 3
rabbitmq.rbac.create If true, create and use RBAC resources TRUE
rabbitmq.service.type Type of service to create ClusterIP
UseExistingMQ.Enabled If you want to use an existing Message Queue, change rabbitmq.install to false FALSE
UseExistingMQ.XLD_TASK_QUEUE_USERNAME Username for xl-deploy task queue NA
UseExistingMQ.XLD_TASK_QUEUE_PASSWORD Password for xl-deploy task queue NA
UseExistingMQ.XLD_TASK_QUEUE_NAME URL for xl-deploy task queue NA
UseExistingMQ.XLDTASKQUEUEDRIVERCLASS_NAME Driver Class Name for xl-deploy task queue NA
HealthProbes Would you like a HealthProbes to be enabled TRUE
HealthProbesLivenessTimeout Delay before liveness probe is initiated 60
HealthProbesReadinessTimeout Delay before readiness probe is initiated 60
HealthProbeFailureThreshold Minimum consecutive failures for the probe to be considered failed after having succeeded 12
HealthPeriodScans How often to perform the probe 10
nodeSelector Node labels for pod assignment {}
Tolerations Toleration labels for pod assignment []
Persistence.Enabled Enable persistence using PVC TRUE
Persistence.Annotations Annotations for the PVC {}
Persistence.AccessMode PVC Access Mode for volume ReadWriteOnce
Persistence.XldExportPvcSize XLD Master PVC Storage Request for volume. For production grade setup, size must be changed 10Gi
Persistence. XldWorkPvcSize XLD Worker PVC Storage Request for volume. For production grade setup, size must be changed 10Gi

Step 5—Download and set up the XL CLI

  1. Download the XL-CLI binaries.

    wget https://dist.xebialabs.com/public/xl-cli/$VERSION/linux-amd64/xl

    Note: For $VERSION, substitute with the version that matches your product version in the public folder.

  2. Enable execute permissions.

    chmod +x xl
  3. Copy the XL binary in a directory that is on your PATH.

    echo $PATH

    Example

    cp xl /usr/local/bin
  4. Verify the release version.

    xl version

Step 6—Set up the XL Deploy Container instance

  1. 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:10.2
  2. To access the Deploy interface, go to:
    http://<host IP address>:4516/

Step 7—Activate the deployment process

Go to the root of the extracted file and run the following command:

xl apply -v -f digital-ai.yaml

Step 8—Verify the deployment status

  1. Check the deployment job completion using XL CLI.
    The deployment job starts the execution of various tasks as defined in the digital-ai.yaml file 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 running time depends on the environment.

    Deployment Status

    To troubleshoot runtime errors, see Troubleshooting Operator Based Installer.

Step 9—Verify if the deployment was successful

To verify the deployment succeeded, do one of the following:

  • Open the Deploy application, go to the Explorer tab, and from Library, click Monitoring > Deployment tasks

    Deployment Verification

  • Run the following command in a terminal or command prompt:

    Deployment Verification Using CLI Command

Step 10—Perform sanity checks

Open the Deploy application and perform the required deployment sanity checks.

Installing Deploy on Kubernetes On-premise Platform

Follow the steps below to install Deploy on Kubernetes On-premise cluster.

Step 1—Create a folder for installation tasks

Create a folder on your workstation from where you will execute the installation tasks, for example, DeployInstallation.

Step 2—Download the Operator ZIP

  1. Download the deploy-operator-onprem-10.3.zip file from the Deploy/Release Software Distribution site.
  2. Extract the ZIP file to the DeployInstallation folder.

Step 3—Update the Kubernetes On-premise Cluster Information

To deploy the Deploy application on the Kubernetes cluster, update the Infrastructure file parameters (infrastructure.yaml) in the location where you extracted the ZIP file with the parameters corresponding to the Kubernetes On-premise Kubernetes Cluster Configuration (kubeconfig) file as described in the table. 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 Kubernetes On-premise Kubernetes Cluster Configuration File Parameters Parameter Value
apiServerURL server Enter the server details of the cluster.
caCert certificate-authority-data Before updating the parameter value, decode to base64 format.
tlsCert client-certificate-data Before updating the parameter value, decode to base64 format.
tlsPrivateKey client-key-data Before updating the parameter value, decode to base64 format.

Step 4—Update the default Digitial.ai Deploy Custom Resource Definitions.

  1. Update daideploy_cr file in the \digitalai-deploy\kubernetes path of the extracted zip file.
  2. 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 daideploy_cr.yaml file.

    Parameter Description
    K8sSetup.Platform Platform on which to install the chart. For the Kubernetes on-premise cluster, you must set the value to PlainK8s
    ingress.hosts DNS name for accessing UI of Digital.ai Deploy
    xldLicense Convert the license file for Digital.ai Deploy to the base64 format.
    RepositoryKeystore Convert the license file for Digital.ai Deploy to the base64 format.
    KeystorePassphrase The passphrase for the RepositoryKeystore.
    postgresql.persistence.storageClass Storage Class to be defined for PostgreSQL
    rabbitmq.persistence.storageClass Storage Class to be defined for RabbitMQ
    Persistence.StorageClass The storage class that must be defined as Kubernetes On-premise platform

    Note: For deployments on production environments, you must configure all the parameters required for your Kubernetes On-premise production setup, in the daideploy_cr.yaml file. The table in Step 4.4 lists these parameters and their default values, which can be overridden as per your setup requirements and workload. You must override the default parameters, and specify the parameter values with those from the custom resource file.

  3. Update the daideploy_cr.yaml file with the license and keystore details.

    1. Convert the Deploy license and the repository keystore files to the base 64 format.
    2. Run the following commands:

      • To convert the xldLicense into base 64 format, run:

        cat <License.lic> | base64 -w 0
      • To convert RepositoryKeystore to 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/-decode to indirectly perform Base64 encoding and decoding.

  4. Update the default parameters as described in the Default Parameters table:

    Note: The following table describes the default parameters in the Digital.ai daideploy_cr.yaml file. 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.yaml file. For information on how to configure SSL/TLS with Digital.ai Deploy, see Configuring SSL/TLS.

Click to expand the Default Parameters table
Parameter Description Default
K8sSetup.Platform Platform on which to install the chart. Allowed values are PlainK8s and AWSEKS PlainK8s
XldMasterCount Number of master replicas 3
XldWorkerCount Number of worker replicas 3
ImageRepository Image name Truncated
ImageTag Image tag 10.1
ImagePullPolicy Image pull policy, Defaults to ’Always’ if image tag is ’latest’,set to ’IfNotPresent’ Always
ImagePullSecret Specify docker-registry secret names. Secrets must be manually created in the namespace nil
haproxy-ingress.install Install haproxy subchart. If you have haproxy already installed, set ’install’ to ’false’ true
haproxy-ingress.controller.kind Type of deployment, DaemonSet or Deployment DaemonSet
haproxy-ingress.controller.service.type Kubernetes Service type for haproxy. It can be changed to LoadBalancer or NodePort NodePort
nginx-ingress-controller.install Install nginx subchart to false, as we are using haproxy as a ingress controller false (for HAProxy)
nginx-ingress.controller.install Install nginx subchart. If you have nginx already installed, set ’install’ to ’false’ true
nginx-ingress.controller.image.pullSecrets pullSecrets name for nginx ingress controller myRegistryKeySecretName
nginx-ingress.controller.replicaCount Number of replica 1
nginx-ingress.controller.service.type Kubernetes Service type for nginx. It can be changed to LoadBalancer or NodePort NodePort
haproxy-ingress.install Install haproxy subchart to false as we are using nginx as a ingress controller false (for NGINX)
ingress.Enabled Exposes HTTP and HTTPS routes from outside the cluster to services within the cluster true
ingress.annotations Annotations for ingress controller ingress.kubernetes.io/ssl-redirect: ”false”kubernetes.io/ingress.class: haproxyingress.kubernetes.io/rewrite-target: /ingress.kubernetes.io/affinity: cookieingress.kubernetes.io/session-cookie-name: JSESSIONIDingress.kubernetes.io/session-cookie-strategy: prefixingress.kubernetes.io/config-backend:
ingress.path You can route an Ingress to different Services based on the path /xl-deploy/
ingress.hosts DNS name for accessing ui of Digital.ai Deploy example.com
ingress.tls.secretName Secret file which holds the tls private key and certificate example-secretsName
ingress.tls.hosts DNS name for accessing ui of Digital.ai Deploy using tls example.com
AdminPassword Admin password for xl-deploy If user does not provide password, random 10 character alphanumeric string will be generated
xldLicense Convert xl-deploy.lic files content to base64 nil
RepositoryKeystore Convert keystore.jks files content to base64 nil
KeystorePassphrase Passphrase for keystore.jks file nil
resources CPU/Memory resource requests/limits. User can change the parameter accordingly nil
postgresql.install postgresql chart with single instance. Install postgresql chart. If you have an existing database deployment, set ’install’ to ’false’. true
postgresql.postgresqlUsername PostgreSQL user (creates a non-admin user when postgresqlUsername is not postgres) postgres
postgresql.postgresqlPassword PostgreSQL user password random 10 character alphanumeric string
postgresql.postgresqlExtendedConf.listenAddresses Specifies the TCP/IP address(es) on which the server is to listen for connections from client applications ’*’
postgresql.postgresqlExtendedConf.maxConnections Maximum total connections 500
postgresql.initdbScriptsSecret Secret with initdb scripts that contain sensitive information (Note: can be used with initdbScriptsConfigMap or initdbScripts). The value is evaluated as a template. postgresql-init-sql-xld
postgresql.service.port PostgreSQL port 5432
postgresql.persistence.enabled Enable persistence using PVC true
postgresql.persistence.size PVC Storage Request for PostgreSQL volume 50Gi
postgresql.persistence.existingClaim Provide an existing PersistentVolumeClaim, the value is evaluated as a template. nil
postgresql.resources.requests CPU/Memory resource requests requests: memory: 1Gi memory: cpu: 250m
postgresql.resources.limits Limits limits: memory: 2Gi, limits: cpu: 1
postgresql.nodeSelector Node labels for pod assignment {}
postgresql.affinity Affinity labels for pod assignment {}
postgresql.tolerations Toleration labels for pod assignment []
UseExistingDB.Enabled If you want to use an existing database, change ’postgresql.install’ to ’false’. false
UseExistingDB.XL_DB_URL Database URL for xl-deploy nil
UseExistingDB.XL_DB_USERNAME Database User for xl-deploy nil
UseExistingDB.XL_DB_PASSWORD Database Password for xl-deploy nil
rabbitmq-ha.install Install rabbitmq chart. If you have an existing message queue deployment, set ’install’ to ’false’. true
rabbitmq-ha.rabbitmqUsername RabbitMQ application username guest
rabbitmq-ha.rabbitmqPassword RabbitMQ application password random 24 character long alphanumeric string
rabbitmq-ha.rabbitmqErlangCookie Erlang cookie DEPLOYRABBITMQCLUSTER
rabbitmq-ha.rabbitmqMemoryHighWatermark Memory high watermark 500MB
rabbitmq-ha.rabbitmqNodePort Node port 5672
rabbitmq-ha.extraPlugins Additional plugins to add to the default configmap rabbitmq_shovel,rabbitmq_shovel_management,rabbitmq_federation,rabbitmq_federation_management,rabbitmq_jms_topic_exchange,rabbitmq_management,
rabbitmq-ha.replicaCount Number of replica 3
rabbitmq-ha.rbac.create If true, create & use RBAC resources true
rabbitmq-ha.service.type Type of service to create ClusterIP
rabbitmq-ha.persistentVolume.enabled If true, persistent volume claims are created false
rabbitmq-ha.persistentVolume.size Persistent volume size 20Gi
rabbitmq-ha.persistentVolume.annotations Persistent volume annotations {}
rabbitmq-ha.persistentVolume.resources Persistent Volume resources {}
rabbitmq-ha.persistentVolume.requests CPU/Memory resource requests requests: memory: 250Mi memory: cpu: 100m
rabbitmq-ha.persistentVolume.limits Limits limits: memory: 550Mi, limits: cpu: 200m
rabbitmq-ha.definitions.policies HA policies to add to definitions.json {”name”: ”ha-all”,”pattern”: ”.*”,”vhost”: ”/”,”definition”: {”ha-mode”: ”all”,”ha-sync-mode”: ”automatic”,”ha-sync-batch-size”: 1}}
rabbitmq-ha.definitions.globalParameters Pre-configured global parameters {”name”: ”cluster_name”,”value”: ””}
rabbitmq-ha.prometheus.operator.enabled Enabling Prometheus Operator false
UseExistingMQ.Enabled If you want to use an existing Message Queue, change ’rabbitmq-ha.install’ to ’false’ false
UseExistingMQ.XLD_TASK_QUEUE_USERNAME Username for xl-deploy task queue nil
UseExistingMQ.XLD_TASK_QUEUE_PASSWORD Password for xl-deploy task queue nil
UseExistingMQ.XLD_TASK_QUEUE_URL URL for xl-deploy task queue nil
UseExistingMQ.XLD_TASK_QUEUE_DRIVER_CLASS_NAME Driver Class Name for xl-deploy task queue nil
HealthProbes Would you like a HealthProbes to be enabled true
HealthProbesLivenessTimeout Delay before liveness probe is initiated 90
HealthProbesReadinessTimeout Delay before readiness probe is initiated 90
HealthProbeFailureThreshold Minimum consecutive failures for the probe to be considered failed after having succeeded 12
HealthPeriodScans How often to perform the probe 10
nodeSelector Node labels for pod assignment {}
tolerations Toleration labels for pod assignment []
affinity Affinity labels for pod assignment {}
Persistence.Enabled Enable persistence using PVC true
Persistence.StorageClass PVC Storage Class for volume nil
Persistence.Annotations Annotations for the PVC {}
Persistence.AccessMode PVC Access Mode for volume ReadWriteOnce
Persistence.XldExportPvcSize XLD Master PVC Storage Request for volume. For production grade setup, size must be changed 10Gi
Persistence. XldWorkPvcSize XLD Worker PVC Storage Request for volume. For production grade setup, size must be changed 5Gi
satellite.Enabled Enable the satellite support to use it with Deploy false

Step 5—Download and set up the XL CLI

Download the XL-CLI binaries.

wget https://dist.xebialabs.com/public/xl-cli/$VERSION/linux-amd64/xl

Note: For $VERSION, substitute with the version that matches your product version in the public folder.

  1. Enable execute permissions.

    chmod +x xl
  2. Copy the XL binary in a directory that is on your PATH.

    echo $PATH

    Example

    cp xl /usr/local/bin
  3. Verify the Deploy version.

    xl version

Step 6—Set up the XL Deploy Container instance

  1. Run the following command to download and start the Digital.ai Deploy instance:

    docker run -d -e "ADMIN_PASSWORD=admin" -e "ACCEPT_EULA=Y" -p 4516:4516 --name xld xebialabs/xl-deploy:10.2
  2. To access the Deploy interface, go to:‘http://< host IP address >:4516/’

Step 7—Activate the deployment process

Go to the root of the extracted file and run the following command:

xl apply -v -f digital-ai.yaml

Step 8—Verify the deployment status

  1. Check the deployment job completion using XL CLI.
    The deployment job starts the execution of various tasks as defined in the digital-ai.yaml file 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 running time depends on the environment.

    Deployment Status

    To troubleshoot runtime errors, see Troubleshooting Operator Based Installer).

Step 9—Verify if the deployment was successful

To verify the deployment succeeded, do one of the following:

  • Open the Deploy application, go to the Explorer tab, and from Library, click Monitoring > Deployment tasks

    Deployment Verification

  • Run the following commands in a terminal or command prompt:

    Deployment Verification Using CLI Command

Step 10—Perform sanity checks

Open the Deploy application and perform the required deployment sanity checks.

Installing Deploy on OpenShift Cluster

You can install Deploy on the following platforms:

  • OpenShift cluster on AWS
  • OpenShift cluster on VMWare vSphere

Follow the steps below to install Deploy on one of the platforms.

Step 1—Create a folder for installation tasks

Create a folder on your workstation from where you will execute the installation tasks, for example, DeployInstallation.

Step 2—Download the Operator ZIP

  1. Download the deploy-operator-openshift-10.3.zip file from the Deploy/Release Software Distribution site.
  2. Extract the ZIP file to the DeployInstallation folder.

Step 3—Update the platform information

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 (OpenShift 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 fail if the infrastructure.yaml is updated with wrong details.

Infrastructure File Parameters OpenShift Cluster Configuration File Parameters Parameter Value
ServerUrl server Enter the server details of the cluster.
openshiftToken NA This parameter defines the access token to access your OpenShift cluster.

Step 4—Update the Custom Resource Definitions (daideploy_cr.yaml)

  1. Run the following command to retrieve StorageClass values for Server, Postgres and Rabbitmq:

    oc get sc
  2. Run the keytool command below to generate the RepositoryKeystore:

    keytool -genseckey {-alias alias} {-keyalg keyalg} {-keysize keysize} [-keypass keypass] {-storetype storetype} {-keystore keystore} [-storepass storepass]

    Example

    keytool -genseckey -alias deployit-passsword-key -keyalg aes -keysize 128 -keypass deployit -keystore /tmp/repository-keystore.jceks -storetype jceks -storepass test123
  3. Convert the Deploy license and the repository keystore files to the base64 format:

    • To convert the xldLicense into base64 format, run:
    cat <License.lic> | base64 -w 0
    • To convert RepositoryKeystore to base64 format, run:
    cat <repository-keystore.jceks> | base64 -w 0
  4. 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 daideploy_cr.yaml file.

    Parameters Description
    KeystorePassphrase The passphrase for repository-keystore file
    Persistence.StorageClass PVC Storage Class for volume
    RepositoryKeystore Convert the repository-keystore file content to Base 64 format.
    ingress.hosts DNS name for accessing UI of Digital.ai Deploy.
    postgresql.Persistence.StorageClass PVC Storage Class for Postgres
    rabbitmq.Persistence.StorageClass PVC Storage Class for Rabbitmq
    xldLicense Deploy license

    Note: For deployments on production environments, you must configure all the parameters required for your Openshift production setup in the daideploy_cr.yaml file. The table in Step 4.5 lists these parameters and their default values, which can be overridden as per your setup requirements and workload. You must override the default parameters, and specify the parameter values with those from the custom resource file.

  5. Update the default parameters as described in the Default Parameters based on your requirements:

    Note: The following table describes the default parameters in the Digital.ai daideploy_cr.yaml file. 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.yaml file. For information on how to configure AWS RDS with Digital.ai Deploy, see Configuring AWS RDS.

Click to expand the Default Parameters table
Fields to be updated in daideploy_cr.yaml Description Default Values
ImageRepository Image name xebialabs/xl-deploy
ImageTag Image tag 10.2
AdminPassword The administrator password for Deploy admin
Resources CPU/Memory resource requests/limits. User can change the parameter accordingly. NA
postgresql.install postgresql chart with single instance. Install postgresql chart. If you have an existing database deployment, set install to false. TRUE
postgresql.postgresqlUsername PostgreSQL user (creates a non-admin user when postgresqlUsername is not postgres) postgres
postgresql.postgresqlPassword PostgreSQL user password postgres
postgresql.replication.enabled Enable replication false
postgresql.postgresqlExtendedConf.listenAddresses Specifies the TCP/IP address(es) on which the server is to listen for connections from client applications *
postgresql.postgresqlExtendedConf.maxConnections Maximum total connections 500
postgresql.initdbScriptsSecret Secret with initdb scripts contain sensitive information
Note: This paramete can be used with initdbScriptsConfigMap or initdbScripts. The value is evaluated as a template.
postgresql-init-sql-xld
postgresql.service.port PostgreSQL port 5432
postgresql.persistence.enabled Enable persistence using PVC TRUE
postgresql.persistence.size PVC Storage Request for PostgreSQL volume 50Gi
postgresql.persistence.existingClaim Provide an existing PersistentVolumeClaim, the value is evaluated as a template. NA
postgresql.resources.requests CPU/Memory resource requests/limits. User can change the parameter accordingly. cpu: 250m
Memory: 256Mi
postgresql.nodeSelector Node labels for pod assignment {}
postgresql.affinity Affinity labels for pod assignment {}
postgresql.tolerations Toleration labels for pod assignment []
UseExistingDB.Enabled If you want to use an existing database, change postgresql.install to false. false
UseExistingDB.XL_DB_URL Database URL for xl-deploy NA
UseExistingDB.XL_DB_USERNAME Database User for xl-deploy NA
UseExistingDB.XL_DB_PASSWORD Database Password for xl-deploy NA
rabbitmq.install Install rabbitmq chart. If you have an existing message queue deployment, set install to false. TRUE
rabbitmq.extraPlugins Additional plugins to add to the default configmap rabbitmqjmstopic_exchange
rabbitmq.replicaCount Number of replica 3
rabbitmq.rbac.create If true, create & use RBAC resources TRUE
rabbitmq.service.type Type of service to create ClusterIP
rabbitmq.persistence.enabled If true, persistent volume claims are created TRUE
rabbitmq.persistence.size Persistent volume size 8Gi
UseExistingMQ.Enabled If you want to use an existing Message Queue, change rabbitmq-ha.install to false false
UseExistingMQ.XLD_TASK_QUEUE_USERNAME Username for xl-deploy task queue NA
UseExistingMQ.XLD_TASK_QUEUE_PASSWORD Password for xl-deploy task queue NA
UseExistingMQ.XLD_TASK_QUEUE_URL URL for xl-deploy task queue NA
UseExistingMQ.XLD_TASK_QUEUE_DRIVER_CLASS_NAME Driver Class Name for xl-deploy task queue NA
HealthProbes Would you like a HealthProbes to be enabled TRUE
HealthProbesLivenessTimeout Delay before liveness probe is initiated 60
HealthProbesReadinessTimeout Delay before readiness probe is initiated 60
HealthProbeFailureThreshold Minimum consecutive failures for the probe to be considered failed after having succeeded 12
HealthPeriodScans How often to perform the probe 10
nodeSelector Node labels for pod assignment {}
tolerations Toleration labels for pod assignment []
Persistence.Enabled Enable persistence using PVC TRUE
Persistence.Annotations Annotations for the PVC {}
Persistence.AccessMode PVC Access Mode for volume ReadWriteOnce
Persistence.XldMasterPvcSize XLD Master PVC Storage Request for volume. For production grade setup, size must be changed 10Gi
Persistence. XldWorkPvcSize XLD Worker PVC Storage Request for volume. For production grade setup, size must be changed 10Gi
satellite.Enabled Enable the satellite support to use it with Deploy false

Step 5—Set up the CLI

  1. Download the XL-CLI libraries.

    wget https://dist.xebialabs.com/public/xl-cli/$VERSION/linux-amd64/xl

    Note: For $VERSION, substitute with the version that matches your product version in the public folder.

  2. Enable execute permissions.

    chmod +x xl
  3. Copy the XL binary to a directory in your PATH.

    echo $PATH
    cp xl /usr/local/bin
  4. Verify the Deploy application release version.

    xl version

Step 6—Set up the Deploy container instance

  1. Run the following command to download and run the Digital.ai Deploy instance:

    docker run -d -e "ADMIN_PASSWORD=admin" -e "ACCEPT_EULA=Y" -p 4516:4516 --name xld xebialabs/xl-deploy:10.0
  2. Go the following URL to access the Deploy application:
    http://_host IP address_:4516/

Step 7— Activate the Deploy Deployment process

  1. Go to the root of the extracted file and run the following command to activate the deployment process:
xl apply -v -f digital-ai.yaml

Step 8—Verify the deployment status

  1. Check the deployment job completion using XL CLI.
    The deployment job starts the execution of various tasks as defined in the digital-ai.yaml file 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 running time depends on the environment.

Step 9—Verify if the deployment was successful

To 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:

    kubectl get pod

To check the deployment status using CLI, run the following command:

```
oc get pod
```

Step 10—Perform sanity checks

Open the Deploy application and perform the required deployment sanity checks.

Installing Deploy on GCP GKE

Follow the steps below to install Deploy on Google Cloud Platform (GCP) Google Kubernetes Engine (GKE)

Step 1—Create a folder for installation tasks

Create a folder on your workstation from where you will execute the installation tasks, for example, DeployInstallation.

Step 2—Download the Operator ZIP

  1. Download the deploy-operator-gcp-gke-10.3.zip from the Deploy/Release Software Distribution site.
  2. Extract the ZIP file to the DeployInstallation folder.

Step 3—Update the GCP GKE Cluster Information

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 parameter value.
caCert certificate-authority-data Before updating the parameter value, decode to base 64 format.
token access token Enter the access token details.

Step 3—Update the default Digitial.ai Deploy Custom Resource Definitions.

  1. Go to \digitalai-deploy\kubernetes and open the daideploy_cr.yaml file.
  2. 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 daideploy_cr.yaml file.

    Parameter Description
    K8sSetup.Platform Platform on which to install the chart. For the GKE cluster, set the value to GoogleGKE.
    haproxy-ingress.controller.service.type The Kubernetes Service type for haproxy. Or nginx-ingress.controller.service.type: The Kubernetes Service type for nginx. The default value is NodePort. You must set the value to LoadBalancer for the GKE cluster.
    ingress.hosts DNS name for accessing UI of Digital.ai Deploy.
    xldLicense Deploy license
    RepositoryKeystore Convert the license file for Digital.ai Deploy to the base64 format.
    KeystorePassphrase The passphrase for the RepositoryKeystore.
    postgresql.persistence.storageClass Storage Class to be defined as PostgreSQL.
    rabbitmq.persistence.storageClass Storage Class to be defined as RabbitMQ.
    Persistence.StorageClass The storage class that must be defined as GCP GKE cluster.

    Note: For deployments on production environments, you must configure all the parameters required for your GCP GKE production setup in the daideploy_cr.yaml file. The table in Step 4.5 lists these parameters and their default values, which can be overridden as per your setup requirements and workload. You must override the default parameters, and specify the parameter values with those from the custom resource file. The following table describes the parameters and their default values.

  3. Update the daideploy_cr.yaml file with the license and keystore details:

    1. Convert the Deploy license and the repository keystore files to the base64 format:
    2. To convert the xldLicense into base64 format, run:

      cat <License.lic> | base64 -w 0
    3. To convert RepositoryKeystore to base64 format, run:

      cat <repository-keystore.jceks> | 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. However, you can use the built-in command certutil -encode/-decode to indirectly perform Base64 encoding and decoding.

  4. Update the default parameters as described in the Default Parameters table:

    Note: The following table describes the default parameters in the Digital.ai daideploy_cr.yaml file. 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.yaml file. For information on how to configure SSL/TLS with Digital.ai Deploy, see Configuring SSL/TLS.

Click to expand the Default Parameters table |
**Parameter**
| **Description** | **Default** | | --- | --- | --- | | K8sSetup.Platform | Platform on which to install the chart. Allowed values are PlainK8s, AWSEKS, AzureAKS, and GoogleGKE | GoogleGKE | | XldMasterCount | Number of master replicas | 3 | | XldWorkerCount | Number of worker replicas | 3 | | ImageRepository | Image name | Truncated| | ImageTag | Image tag | 10.1 | | ImagePullPolicy | Image pull policy, Defaults to ’Always’ if image tag is ’latest’,set to ’IfNotPresent’ | Always | | ImagePullSecret | Specify docker-registry secret names. Secrets must be manually created in the namespace | nil | | haproxy-ingress.install | Install haproxy subchart. If you have haproxy already installed, set 'install' to 'false' | true | | haproxy-ingress.controller.kind | Type of deployment, DaemonSet or Deployment | DaemonSet | | haproxy-ingress.controller.service.type | Kubernetes Service type for haproxy. It can be changed to LoadBalancer or NodePort | NodePort | | nginx-ingress-controller.install | Install nginx subchart to false, as we are using haproxy as a ingress controller | false (for HAProxy) | | nginx-ingress.controller.install | Install nginx subchart. If you have nginx already installed, set 'install' to 'false' | true | | nginx-ingress.controller.image.pullSecrets | pullSecrets name for nginx ingress controller | myRegistryKeySecretName | | nginx-ingress.controller.replicaCount | Number of replica | 1 | | nginx-ingress.controller.service.type | Kubernetes Service type for nginx. It can be changed to LoadBalancer or NodePort | NodePort | | haproxy-ingress.install | Install haproxy subchart to false as we are using nginx as a ingress controller | false (for NGINX) | | ingress.Enabled | Exposes HTTP and HTTPS routes from outside the cluster to services within the cluster | true | | ingress.annotations | Annotations for ingress controller | ingress.kubernetes.io/ssl-redirect: ”false”kubernetes.io/ingress.class: haproxyingress.kubernetes.io/rewrite-target: /ingress.kubernetes.io/affinity: cookieingress.kubernetes.io/session-cookie-name: JSESSIONIDingress.kubernetes.io/session-cookie-strategy: prefixingress.kubernetes.io/config-backend: option httpchk GET /ha/health HTTP/1.0 | | ingress.path | You can route an Ingress to different Services based on the path | /xl-deploy/ | | ingress.hosts | DNS name for accessing ui of Digital.ai Deploy | example.com | | ingress.tls.secretName | Secret file which holds the tls private key and certificate | example-secretsName | | ingress.tls.hosts | DNS name for accessing ui of Digital.ai Deploy using tls. See [configuring TLS SSL](/deploy/how-to/AzureAKS/azure-configuring-tls-deploy) | example.com | | AdminPassword | Admin password for xl-| If user does not provide password, random 10 character alphanumeric string will be generated | | xldLicense | Convert xl-deploy.lic files content to base64 | nil | | RepositoryKeystore | Convert repository-keystore.jceks files content to base64 | nil | | KeystorePassphrase | Passphrase for repository-keystore.jceks file | nil | | resources | CPU/Memory resource requests/limits. User can change the parameter accordingly | nil | | postgresql.install | postgresql chart with single instance. Install postgresql chart. If you have an existing database deployment, set ’install’ to ’false’. | true | | postgresql.postgresqlUsername | PostgreSQL user (creates a non-admin user when postgresqlUsername is not postgres) | postgres | | postgresql.postgresqlPassword | PostgreSQL user password | random 10 character alphanumeric string | | postgresql.replication.enabled | Enable replication | false | | postgresql.postgresqlExtendedConf.listenAddresses | Specifies the TCP/IP address(es) on which the server is to listen for connections from client applications | ’*’ | | postgresql.postgresqlExtendedConf.maxConnections | Maximum total connections | 500 | | postgresql.initdbScriptsSecret | Secret with initdb scripts that contain sensitive information (Note: can be used with initdbScriptsConfigMap or initdbScripts). The value is evaluated as a template. | postgresql-init-sql-xld | | postgresql.service.port | PostgreSQL port | 5432 | | postgresql.persistence.enabled | Enable persistence using PVC | true | | postgresql.persistence.storageClass | PVC Storage Class for postgresql volume | nil | | postgresql.persistence.size | Provide an existing PersistentVolumeClaim, the value is evaluated as a template. | nil | | postgresql.resources.requests | CPU/Memory resource requests | requests: memory: 1Gi memory: cpu: 250m | | postgresql.resources.limits | Limits | limits: memory: 2Gi, limits: cpu: 1 | | postgresql.nodeSelector | Node labels for pod assignment | {} | | postgresql.affinity | Affinity labels for pod assignment | {} | | postgresql.tolerations | Toleration labels for pod assignment | [] | | UseExistingDB.Enabled | If you want to use an existing database, change ’postgresql.install’ to ’false’. | false | | UseExistingDB.XL\_DB\_URL | Database URL for xl-deploy | nil | | UseExistingDB.XL\_DB\_USERNAME | Database User for xl-deploy | nil | | UseExistingDB.XL\_DB\_PASSWORD | Database Password for xl-deploy | nil | | rabbitmq.install | Install rabbitmq chart. If you have an existing message queue deployment, set ’install’ to ’false’. | true | | rabbitmq.replicaCount | Number of RabbitMQ nodes | 3 | | rabbitmq.auth.username | RabbitMQ application username | guest | | rabbitmq.auth.password | RabbitMQ application password | guest | | rabbitmq.auth.erlangCookie | Erlang cookie | RABBITMQCLUSTER | | rabbitmq.extraPlugins | Extra plugins to enable (single string containing a space-separated list) | 'rabbitmq_amqp1_0' | | rabbitmq.extraSecrets | Optionally specify extra secrets to be created by the chart. | {} (evaluated as a template) | | rabbitmq.loadDefinition.enabled | Enable loading a RabbitMQ definitions file to configure RabbitMQ | true | | rabbitmq.loadDefinition.existingSecret | Existing secret with the load definitions file | load-definition | | rabbitmq.extraConfiguration | Extra configuration to be appended to RabbitMQ configuration | Check daideploy_cr.yaml file | | rabbitmq.persistence.enabled | Enable RabbitMQ data persistence using PVC | true | | rabbitmq.persistence.storageClass | PVC Storage Class for RabbitMQ data volume | nil | | rabbitmq. persistence.size | PVC Storage Request for RabbitMQ data volume | 8Gi | | rabbitmq.service.type | Kubernetes Service type | ClusterIP | | rabbitmq.volumePermissions.enabled | Persistent Volume resources | {} | | UseExistingMQ.Enabled | If you want to use an existing Message Queue, change ’rabbitmq.install’ to ’false’ | false | | UseExistingMQ.XLD\_TASK\_QUEUE\_USERNAME | Username for xl-deploy task queue | nil | | UseExistingMQ.XLD\_TASK\_QUEUE\_PASSWORD | Password for xl-deploy task queue | nil | | UseExistingMQ.XLD\_TASK\_QUEUE\_NAME | URL for xl-deploy task queue | nil | | UseExistingMQ.XLD_TASK_QUEUE_DRIVER_CLASS_NAME | Driver Class Name for xl-deploy task queue | nil | | HealthProbes | Would you like a HealthProbes to be enabled | true | | HealthProbesLivenessTimeout | Delay before liveness probe is initiated | 90 | | HealthProbesReadinessTimeout | Delay before readiness probe is initiated | 90 | | HealthProbeFailureThreshold | Minimum consecutive failures for the probe to be considered failed after having succeeded | 12 | | HealthPeriodScans | How often to perform the probe | 10 | | nodeSelector | Node labels for pod assignment | {} | | tolerations | Toleration labels for pod assignment | [] | | affinity | Affinity labels for pod assignment | {} | | Persistence.Enabled | Enable persistence using PVC | true | | Persistence.StorageClass | PVC Storage Class for volume | nil | | Persistence.Annotations | Annotations for the PVC | {} | | Persistence.AccessMode | PVC Access Mode for volume | ReadWriteOnce | | Persistence.XldExportPvcSize | XLD Master PVC Storage Request for volume. For production grade setup, size must be changed | 10Gi | | Persistence. XldWorkPvcSize | XLD Worker PVC Storage Request for volume. For production grade setup, size must be changed | 10Gi | | satellite.Enabled | Enable the satellite support to use it with Deploy | false |

Step 4—Download and set up the XL CLI

  1. Download the XL-CLI binaries.

    wget https://dist.xebialabs.com/public/xl-cli/$VERSION/linux-amd64/xl

    Note: For $VERSION, substitute with the version that matches your product version in the public folder.

  2. Enable execute permissions.

    chmod +x xl
  3. Copy the XL binary in a directory that is on your PATH.

    echo $PATH

    Example

    cp xl /usr/local/bin
  4. Verify the release version.

    xl version

Step 5—Set up the XL Deploy Container instance

  1. 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:10.0
  2. To access the Deploy interface, go to:
    http://<host IP address>:4516/

Step 6—Activate the deployment process

Go to the root of the extracted file and run the following command:

xl apply -v -f digital-ai.yaml

Step 7—Verify the deployment status

  1. Check the deployment job completion using XL CLI.
    The deployment job starts the execution of various tasks as defined in the digital-ai.yaml file 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 running time depends on the environment.

    Deployment Status

    To troubleshoot runtime errors, see Troubleshooting Operator Based Installer.

Step 8—Verify if the deployment was successful

To verify the deployment succeeded, do one of the following:

  • Open the Deploy application, go to the Explorer tab, and from Library, click Monitoring > Deployment tasks

    Successful Deploy Deployment

  • Run the following command in a terminal or command prompt:

    Deployment Verification Using CLI Command

Step 9—Perform sanity checks

Open the Deploy application and perform the required deployment sanity checks.