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Addons Helm chart

The addons chart installs a collection of supporting services and tools for a Pega deployment. The services you need to deploy will depend on your cloud environment - for example you may need a load balancer on Minikube, but not for EKS. These supporting services are deployed once per Kubernetes environment, regardless of how many Pega Infinity instances are deployed. This readme provides a detailed description of possible configurations and their default values as applicable.

Pega does not actively update the dependencies in requirements.yaml. Whether a dependency is enabled or disabled will depend on the service you choose for your environment. For any enabled dependencies listed in the requirements.yaml file, you should update its corresponding version value. Disabled dependencies do not require version updates.

Load balancer

Pega Platform deployments by default assume that clients will use the load balancing tools featured in the Kubernetes environment of the deployment. The table below lists the default load balancer for each environment. Pega supports specifying the use of Traefik as a load balancer for deployments in GKE and AKS environments if you would prefer it; in these cases, use the Addon Helm chart to override the defaults.

Environment Suggested load balancer
Open-source Kubernetes Traefik
Red Hat Openshift HAProxy (Using the roundrobin load balancer strategy)
Amazon Elastic Kubernetes Service (EKS) Amazon Load Balancer (ALB)
Google Kubernetes Engine (GKE) Google Cloud Load Balancer (GCLB)
Pivotal Container Service (PKS) Traefik
Microsoft Azure Kubernetes Service (AKS) Application Gateway Ingress Controller (AGIC)

Traefik

Deploying Pega Platform with more than one Pod typically requires a load balancer to ensure that traffic is routed equally. Some IaaS and PaaS providers supply a load balancer and some do not. If a native load balancer is not provided and configured, or the load balancer does not support cookie based session affinity, Traefik may be used instead. If you do not wish to deploy Traefik, set traefik.enabled to false in the addons values.yaml configuration. For more configuration options available for Traefik, see the Traefik Helm chart.

Example:

traefik:
  enabled: true
  ssl:
    enabled: false
  rbac:
    enabled: true
  service:
    type: NodePort
    nodePorts:
      http: 30080
      https: 30443
  resources:
    requests:
      cpu: 200m
      memory: 200Mi
    limits:
      cpu: 500m
      memory: 500Mi

Amazon ALB

When deploying on AWS EKS, set the parameters, install aws-load-balancer-controller.enabled and metrics-server to true, traefik to false and then fill in the remaining parameters with your EKS environment details.

Configuration Usage
clusterName The name of your EKS cluster. Resources created by the ALB Ingress controller will be prefixed with this string.
region AWS region of the EKS cluster. Required if if ec2metadata is unavailable from the controller Pod.
vpcId VPC ID of EKS cluster, required if ec2metadata is unavailable from controller pod.
serviceAccount.annotations Annotate the service account with eks.amazonaws.com/role-arn IAM Role that provides access to AWS resources.

Example:

aws-load-balancer-controller:
  enabled: true
  clusterName: "YOUR_EKS_CLUSTER_NAME"
  region: "YOUR_EKS_CLUSTER_REGION"
  vpcId: "YOUR_EKS_CLUSTER_VPC_ID"
  serviceAccount:
    annotations:
      eks.amazonaws.com/role-arn: "YOUR_IAM_ROLE_ARN"

Azure AGIC

When deploying on Azure AKS, you can use an Application Gateway Ingress Controller (AGIC) for the deployment load balancer. The AGIC is a pod within your AKS cluster that monitors the Kubernetes Ingress resources, which creates and applies the Application Gateway configuration based on the status of the Kubernetes cluster. For details, see Azure Resource Manager Authentication.

After you create the deployment ingress controller, in the Addons Helm chart, disable Traefik (set traefik.enabled to false), enable AGIC (set ingress-azure.enabled to true) and add the AGIC gateway configuration details from your AKS deployment.

To authenticate with the AGIC in your AKS cluster, generate a kubernetes secret from an Active Directory Service Principal that is based on your AKS subscription ID. You must encode the Service Principal with base64 and add the result to the armAuth.secretJSON field. For details, see the comments in the addons values.yaml or the AKS runbook.

As an authentication alternative, you can configure an AAD Pod Identity to manage authentication access with the AGIC in your cluster via the Azure Resource Manager. For details, see Set up AAD Pod Identity.

It is a recommended best practice to enable RBAC on your AKS cluster and match the setting in the Addons Helm chart.

Example:

ingress-azure:
  enabled: true
    appgw:
      subscriptionId: <YOUR.SUBSCRIPTION_ID>
      resourceGroup: <RESOURCE_GROUP_NAME>
      name: <APPLICATION_GATEWAY_NAME>
      usePrivateIP: true
    armAuth:
    type: servicePrincipal
    secretJSON: <SECRET_JSON_CREATED_USING_ABOVE_COMMAND>
  rbac:
    enabled: true

Google (GCLB)

If deploying on GKE, you can use Google Cloud Load Balancer to route your traffic. In the Addons Helm chart, disable Traefik (set traefik.enabled to false). All other GCLB configurations are automatic.

Aggregated logging

Environment Suggested logging tools
Open-source Kubernetes EFK
Red Hat Openshift Built-in EFK
Amazon Elastic Kubernetes Service (EKS) Built-in EFK
Google Kubernetes Engine (GKE) Google Cloud Operations
Pivotal Container Service (PKS) EFK
Microsoft Azure Kubernetes Service (AKS) Azure Monitor

Logging with Elasticsearch-Fluentd-Kibana (EFK)

EFK is a standard logging stack that is provided as an example for ease of getting started in environments that do not have aggregated logging configured such as open-source Kubernetes. Other IaaS and PaaS providers typically include a logging system out of the box. You may enable the three components of EFK (Elasticsearch,Fluentd, and Kibana) in the addons values.yaml file to deploy EFK automatically. For more configuration options available for each of the components, see their Helm Charts.

Example:

deploy_efk: &deploy_efk true

elasticsearch:
  enabled: *deploy_efk
  fullnameOverride: "elastic-search"

kibana:
  enabled: *deploy_efk
  files:
    kibana.yml:
      elasticsearch.url: http://elastic-search-client:9200
  service:
    externalPort: 80
  ingress:
 
    enabled: true
    # Enter the domain name to access kibana via a load balancer.
    hosts:
      - "YOUR_WEB.KIBANA.EXAMPLE.COM"

fluentd-elasticsearch:
  enabled: *deploy_efk
  elasticsearch:
    host: elastic-search-client
    buffer_chunk_limit: 250M
    buffer_queue_limit: 30

Metrics

Environment Suggested metrics server
Open-source Kubernetes Metrics server
All others Built-in metrics server

Autoscaling in Kubernetes requires the use of a metrics server, a cluster-wide aggregator of resource usage data. Most PaaS and IaaS providers supply a metrics server, but if you wish to deploy into open source kubernetes, you will need to supply your own.

See the metrics-server Helm chart for additional parameters.

Example:

metrics-server:
  enabled: true
  args:
    - --logtostderr