KeyCloak Installation and Configuration for Deploy on Amazon EKS

Introduction

KeyCloak is an identity and access management solution that can be used with the Digital.ai Deploy and Digital.ai Release products. KeyCloak characteristics that may not be present in your current identity server include:

• secure solutions for Multi-Factor Authentication (MFA), One-Time Passwords in both HOTP (Hash-based) and TOTP (Time-based) variants.
• advanced user and rights management services such as system access processes, password rules, and creation of role-based access controls (RBAC) that provide greater flexibility and simpler ways of specifying complex user permissions.
• KeyCloak is open-source software that implements standard protocols (e.g., OIDC 1.0 and OAuth 2.0) with a higher level of security.

For additional details about KeyCloak, please see the KeyCloak Server Administration Guide.

After completing installation and integration of KeyCloak, you will be able to connect KeyCloak with Digital.ai Deploy, allowing users authenticated by KeyCloak to log in to Deploy.

note

In this how-to, KeyCloak is not deployed in an AWS

Elastic Kubernetes Service (EKS) cluster using Operator. KeyCloak may be installed manually inside or outside of AWS EKS.

Overview of Steps and Prerequisites

Installation and configuration of KeyCloak is documented below. Specific steps describe how to:

1. use Operator to deploy Digital.ai Deploy Docker images to Amazon EKS
2. install KeyCloak manually
3. integrate KeyCloak with OpenID Connect (OIDC) and Deploy
4. verify that you successfully added KeyCloak to your Deploy environment

Prerequisites for successfully comepleting those steps:

• Deploy running in AWS EKS as instructed in the Operator document
• Credentials to connect to the identity provider
• Credentials for the users who will use KeyCloak to gain access to Digital.ai Deploy

Use Operator to Install Deploy in Amazon's Elastic Kubernetes Service (AWS EKS)

Operator is a customer Kubernetes Controller that allows you to package, deploy, and manage the Digital.ai Docker image on various platforms (On-Premises, AWS, Azure, OpenShift). Kubernetes Operators help simplify complex deployments by automating tasks that otherwise would require manual intervention or some form of automation. For more thorough introduction to Operator, please see Introduction to Kubernetes Operator.

Use Operator to deploy the Docker image, containing Deploy, to AWS EKS.

Prerequisites that must be satisfied before using Operator are:

• Installation of Docker version 17.03 or later, Docker server running
• Installation of the kubectl command-line tool
• Access to an AWS Kubernetes cluster (version 1.17 or later), with the accessKey and accessSecret available
• Configuration of the Kubernetes cluster

To add Deploy to your pre-existing AWS EKS cluster, please follow all the steps below.

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 file

Download the Operator ZIP file from the dist repository by navigating your browser to:

https://dist.xebialabs.com/customer/operator/deploy/deploy-operator-aws-eks-22.0.0.zip

Step 3: Update the AWS EKS cluster information

To deploy the Deploy application on the Kubernetes cluster, update the Infrastructure file parameters (infrastructure.yaml) in the folder where you extracted the ZIP file with the parameters corresponding to the AWS EKS 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.

Specific values that must be copied from the ~/.kube/config file (see figure 1) to the infrastructure.yaml file (see figure 2) are as follows:

apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: 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
    server: **https://43199B751054CC18BEB9DED348204A4D.gr7.us-east-1.eks.amazonaws.com**
  name: eks-cluster-2.us-east-1.eksctl.io
contexts:
- context:
    cluster: eks-cluster-2.us-east-1.eksctl.io
    user: eks@eks-cluster-2.us-east-1.eksctl.io
  name: eks@eks-cluster-2.us-east-1.eksctl.io
current-context: eks@eks-cluster-2.us-east-1.eksctl.io
kind: Config
preferences: {}
users:
- name: eks@eks-cluster-2.us-east-1.eksctl.io
  user:
    exec:
      apiVersion: client.authentication.k8s.io/v1alpha1
      args:
      - eks
      - get-token
      - --cluster-name
      - **eks-cluster-2**
      - --region
      - **us-east-1**
      command: aws
      env:
      - name: AWS_STS_REGIONAL_ENDPOINTS
        value: regional
      provideClusterInfo: false

Figure 1. ~/.kube/config file

apiVersion: xl-deploy/v1
kind: Infrastructure
spec:
  - name: k8s-infra
    type: core.Directory
    children:
    - name: xld
      type: k8s.Master
      apiServerURL: **< Update using server info from the kubeconfig file >**
      skipTLS: true
      debug: true
      caCert: |-
        <certificate-authority-data in base64 decoded>
        -----BEGIN CERTIFICATE-----
        
        -----END CERTIFICATE-----
      isEKS: true
      useGlobal: true
      regionName: < Update using  region info from the kubeconfig file
      clusterName: <Update using cluster-name field from the kubeconfig file>
      accessKey: <Update the AWS accessKey details >
      accessSecret: <Update the AWS accessSecret details >
      children:
        - name: default
          type: k8s.Namespace
          namespaceName: default

Figure 2. DeployInstallation/deploy-operator-aws-eks/digitalai-deploy/infrastructure.yaml

1. Copy the value of the 'server' field in ~/.kube/config to the 'apiServerURL' field in the infrastructure.yaml file.
2. Copy the value of the 'region' field in ~/.kube/config to the 'regionName' field in the infrastructure.yaml file.
3. Copy the value of the 'cluster-name' field in ~/.kube/config to the 'clusterName' field
   in the infrastructure.yaml file.
4. Update the 'accessKey' and 'accessSecret' fields in the infrastructure.yaml file with the accessKey and accessSecret values. Those values can be found in the AWS IAM information.

Note: The deployment will not proceed further if the infrastructure.yaml is updated with incorrect details.

Infrastructure File Parameters	AWS EKS Kubernetes Cluster Configuration File Parameters	Parameter Value
apiServerURL	server	Enter the server parameter value.
caCert	certificate-authority-data	Before updating the parameter value, decode the certificate-authority-data in the Kubernetes cluster configuration file to base64 format.
regionName	Region	Enter the Region parameter value.
clusterName	cluster-name	Enter the cluster-name parameter value.
accessKey	NA	This parameter defines the access key that allows the Identity and Access (IAM) user to access the AWS using CLI. Note: This value can be found in the AWS IAM information.
accessSecret	NA	This parameter defines the secret password that the IAM user must enter to access the AWS. Note: This value can be found in the AWS IAM information.

Step 4: Update the default Custom Resource Definitions

First, prepare information to 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 -keysize 128 -keypass deployit -keystore /tmp/repository-keystore.jceks -storetype jceks -storepass test123

3. Decode the Deploy license and the repository keystore files to the base64 format:

• To decode the xldLicense into base64 format, run:

cat <xl-deploy.lic> | base64 -w 0

• To decode 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. Edit the daideploy_cr file in the /digitalai-deploy/kubernetes path of the extracted zip file.

5. Update all (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	For an AWS EKS cluster this value must be 'AWSEKS'
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. For an AWS EKS cluster this value must be 'LoadBalancer'
ingress.hosts	DNS name for accessing UI of Digital.ai Deploy. The DNS name should be configured in the AWS Route 53 console hosted zones (please see AWS EKS).
xldLicense	Insert the base64 format of the license file for Digital.ai Deploy.
RepositoryKeystore	Insert the base64 format of the repository keystore file for Digital.ai Deploy.
KeystorePassphrase	The passphrase for the RepositoryKeystore. Note: the example creation of the RepositoryKeystore above used the KeystorePassphrase of "test123".
postgresql.persistence.storageClass	The AWS storage Class must be defined for 'PostgreSQL'
rabbitmq.persistence.storageClass	The AWS storage class must be defined for 'Rabbitmq'
Persistence.StorageClass	The AWS storage class must be defined for 'Deploy'

note

For deployments on production environments, you must configure all the parameters required for your AWS EKS production setup, in the daideploy_cr.yaml file. The table in the next point 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.

note

For storage class creation reference, please see Elastic File System for AWS Elastic Kubernetes Service (EKS) cluster.

6. Update the default parameters as described in the following 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.

note

The domain name digitalai_in_AWS_EKS.com used below stands for the domain name for the Digital.ai Deploy running in AWS EKS.

Parameter	Description	Default
K8sSetup.Platform	Platform on which to 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	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	Deployment
haproxy-ingress.controller.service.type	Kubernetes Service type for haproxy. It can be changed to LoadBalancer or NodePort	LoadBalancer
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	digitalai_in_AWS_EKS.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	digitalai_in_AWS_EKS.com
AdminPassword	Admin password for xl-deploy	If user does not provide password, random 10 character alphanumeric string will be generated
xldLicense	Decode xl-deploy.lic files content to base64	nil
RepositoryKeystore	Decode 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

1. Download the XL-CLI binaries. Packages of the XL-CLI binaries are available for Apple Darwin, Linux, and Microsoft Windows. Visit https://dist.xebialabs.com/public/xl-cli/ to view available versions (if there is a version newer than 10.3.6, then substitute it for the "10.3.6" in the following wget commands. Select the download below that matches your operating system:

wget https://dist.xebialabs.com/public/xl-cli/10.3.6/darwin-amd64/xl

wget https://dist.xebialabs.com/public/xl-cli/10.3.6/linux-amd64/xl

wget https://dist.xebialabs.com/public/xl-cli/10.3.6/windows-amd64/xl.exe

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 Digital.ai 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:22.0

2. To access the Deploy interface, go to:'http://<_host-IP-address_>:4516/'

Install KeyCloak

Install KeyCloak manually by following these instructions:

1. Run this command to create a keycloak container in kubernetes:

kubectl create -f https://raw.githubusercontent.com/keycloak/keycloak-quickstarts/latest/kubernetes-examples/keycloak.yaml

1. After keycloak creation, add the keycloak external IP address to the AWS Route 53 console hosted zone to access the keycloak UI by hostname. Please see AWS EKS for details.

Configuring OpenID Connect (OIDC) Authentication with KeyCloak

Follow these instructions to configure Keycloak as an Identity provider for OpenId Connect (OIDC), enabling users who are properly configured in KeyCloak to log into Deploy, and protect REST APIs using Bearer Token Authorization.

Set up a realm

First, we will create a new realm. On the top left, navigate to Master, open the drop down menu, and click Add realm.

Add a new digitalai-platform realm as shown below.

Add roles

We will add different roles in Keycloak as shown below.

Add users

We will now add new users in Keycloak. Fill in all fields, such as Username, Email, First Name, and Last Name.

Select appropriate role mappings for a user.

Set up a client

The next step is to create a client in our realm, as shown below.

Fill in all of the mandatory fields in the client form. Pay attention to Direct Grant Flow and set its value to direct grant. Change Access Type to confidential.

Select builtin mappers for newly created client.

Make sure that username and groups mapping are present in both id token and access token.

Using Keycloak in Kubernetes Operator-based Deployment

You must set the oidc.enabled to True, and configure the value for the OIDC parameters in the cr.yaml file as described in the following table:

Note: If KeyCloak's verison is 17.0.0 or greater, then remove the auth in all URLs of OIDC configuration.

Description	Configuration
Client credentials from Deploy to Keycloak	clientId="deploy" clientSecret="ab2088f6-2251-4233-9b22-e24db6a67483”
User property mappings	userNameClaim="preferred_username" rolesClaim="groups"
URLs from Browser to Keycloak	issuer="http://xldkeycloak.digitalai-testing.com:8080/auth/realms/digitalai-platform" userAuthorizationUri="http://xldkeycloak.digitalai-testing.com:8080/auth/realms/digitalai-platform/protocol/openid-connect/auth" logoutUri="http://xldkeycloak.digitalai-testing.com:8080/auth/realms/digitalai-platform/protocol/openid-connect/logout"
URLs from Browser to Deploy	redirectUri="http://xld.digitalai-testing.com/login/external-login" postLogoutRedirectUri="http://xld.digitalai-testing.com/oauth2/authorization/xl-deploy"
URLs from Deploy to Keycloak	keyRetrievalUri="http://xldkeycloak.digitalai-testing.com:8080/auth/realms/digitalai-platform/protocol/openid-connect/certs" accessTokenUri="http://xldkeycloak.digitalai-testing.com:8080/auth/realms/digitalai-platform/protocol/openid-connect/token"

Note: Set the external property to "true" (external=true), which allows oidc to be configured to external keycloak.

Note: The path-based routing will not work if you use OIDC authentication. To enable path-based routing, you must modify the ingress specification in the cr.yaml file as follows:

• Set ingress.nginx.ingress.kubernetes.io/rewrite-target: /$2 to /
• Set ingress.path: /xl-deploy(/|$)(.*) to /

For more information about Kubernetes Operator, see Kubernetes Operator.

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.

   

   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

  

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

  

Add the dai-xld-nginx-ingress-controller external IP to AWS Route 53 console hosted zone to access the Deploy UI by hostname. Please see AWS EKS for details.

Test your set up

First we need to assign appropriate permissions in Deploy for users present in Keycloak. The OIDC users and roles are used as principals in Deploy that can be mapped to Deploy roles. Login with internal user and map roles with OIDC roles, as shown below.

Assign appropriate global permissions, as shown below.

Open your deploy url in browser and you should be redirected to Keycloak login page.

Now, Enter the credentials of any user created on keycloak.