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HCL Workload Automation
Welcome to the HCL Workload Automation documentation, where you can find information about how to install, maintain, and use HCL Workload Automation. The documentation has been updated for HCL Workload Automation Version 10.2.
Planning and Installation
Installing HCL Workload Automation
Available installation methods
Deploying with containers
Deploy HCL Workload Automation quickly and easily with containers.
Deploying from Amazon Web Services (AWS) Marketplace
This publication provides detailed information about how to find, subscribe and deploy HCL Workload Automation directly on AWS Marketplace. A cloud deployment ensures access anytime anywhere and is a fast and efficient way to get up and running quickly.
Creating stacks on AWS CloudFormation
In this topic you can find the prerequisites and the steps to create stacks on AWS CloudFormation.

HCL Workload Automation
Welcome to the HCL Workload Automation documentation, where you can find information about how to install, maintain, and use HCL Workload Automation. The documentation has been updated for HCL Workload Automation Version 10.2.
- Planning and Installation
  - Planning
  - Installing HCL Workload Automation
    Available installation methods
    - Installing from the CLI
    - Deploying with containers
      Deploy HCL Workload Automation quickly and easily with containers.
      - Considerations about deploying with containers
        Some considerations about your HCL Workload Automation environments when the product components are deployed using containers.
      - Deploying with Docker compose
        Getting started with Docker compose
      - Deploying HCL Workload Automation components using helm charts
        Deploy the HCL Workload Automation product component containers on a Red Hat OpenShift, V4.x environment by using helm charts.
      - Deploying from Amazon Web Services (AWS) Marketplace
        This publication provides detailed information about how to find, subscribe and deploy HCL Workload Automation directly on AWS Marketplace. A cloud deployment ensures access anytime anywhere and is a fast and efficient way to get up and running quickly.
        Getting started
        You can deploy HCL Workload Automation quickly and easily on Amazon Web Services (AWS) using AWS CloudFormation resources.
        Creating stacks on AWS CloudFormation
        In this topic you can find the prerequisites and the steps to create stacks on AWS CloudFormation.
        Accessing the cluster environment and getting credentials
        In this topic you can find information about how to access your HCL Workload Automation environment and how to get user credentials.
        Downloading packages from the Dynamic Workload Console
        To integrate HCL Workload Automation agent and Orchestration CLI in your environment, you can download the packages from the Dynamic Workload Console.
        Integrating AI Data Advisor (AIDA)
        In this topic you can find information about how to integrate AIDA in your environment.
        Upgrading
        After completing the deployment process of HCL Workload Automation, you can upgrade or customize the chart.
        Uninstalling
        In this topic you can find information about how to uninstall the chart, clean up the orphaned Persistent Volumes and deprovision AWS resources.
      - Deploying on Amazon EKS
        You can use Amazon Elastic Kubernetes Service (EKS) to run HCL Workload Automation containers on Amazon Web Services (AWS) EKS.
      - Deploying on Azure AKS
        You can deploy and manage HCL Workload Automation containers on Azure Kubernetes Service (AKS).
      - Deploying on Google GKE
        You can deploy and manage HCL Workload Automation containers on Google GKE.
      - Workload Automation on HCL SoFy
        An easy way to deploy HCL Workload Automation product components as Docker containers to a cloud-native environment.
      - Using the HCL Workload Automation managed service on Now
        Using the HCL Workload Automation managed service on Now.
      - Customizing container parameters
        The document describes how to avoid the overwriting of the customized parameters added in the container configuration files, such as the datasource.xml file.
      - Deploying AI Data Advisor
        You can deploy AI Data Advisor (AIDA) by using Docker or Kubernetes.
      - Troubleshooting
    - Post-installation configuration
      The most common configuration steps to be performed after completing the installation.
  - Configuring
    Configuring HCL Workload Automation components after installation.
  - Upgrading
    How to upgrade HCL Workload Automation to the current version.
  - Moving from on-premises to cloud
    A quick procedure to move your workload from an on-premises to a cloud environment
  - Troubleshooting installation, migration, and uninstallation
    An overview on troubleshooting installation, migration, and uninstallation of the HCL Workload Automation.
  - Uninstalling
    An overview on how to uninstall the product.
  - Reference
- User's Guide and Reference
- Administration Guide
- Scheduling with the Agent for z/OS
- Database Views
- High Availability Cluster Environment
- Driving HCL Workload Automation
- Extending HCL Workload Automation

Creating stacks on AWS CloudFormation

In this topic you can find the prerequisites and the steps to create stacks on AWS CloudFormation.

Before you begin

After having subscribed to HCL Workload Automation on AWS Marketplace, you can start the stack creation process on AWS CloudFormation.

To deploy HCL Workload Automation, your environment needs to meet the following prerequisites:

An IAM identity, whether role or user, with admin permission on your AWS account.
Helm 3.0
kubectl command-line tool to control Kubernetes clusters.
AWS Command Line Interface (AWS CLI) tool.

Note: If you have an existing cluster, make sure that you have AWS admin roles to deploy Kubernetes resources and HCL Workload Automation Helm Chart resources.

Resources required

The following resources correspond to the default values required to manage a production environment. These numbers might vary depending on the environment.


Component	Container resource limit	Container memory request
Server	CPU: 4, Memory: 16Gi	CPU: 1, Memory: 6Gi, Storage: 10Gi
Console	CPU: 4, Memory: 16Gi	CPU: 1, Memory: 4Gi, Storage: 5Gi
Dynamic Agent	CPU: 1, Memory: 2Gi	CPU: 200m, Memory: 200Mi, Storage size: 2Gi
File Proxy	CPU: 100m, Memory: 128Mi	CPU: 100m, Memory: 128Mi

About this task

You can create stacks on AWS CloudFormation using two templates. The first template deploys the EKS cluster, while the second template deploys the product prerequisites, the resources and the HCL Workload Automation Helm Chart.

Follow the procedure for each template.

Note: If you already have an existing cluster that meets the prerequisites, you can follow the procedure for the second template only.

Procedure

Go to Amazon Web Services and log in.

Note: By default, the time zone on the AWS CloudFormation home page is set on N. Virginia. You can edit the time zone by selecting the time zone that you want from the menu on the right side of the home page.
Select the template corresponding to the stack you want to create.
Click Next.
In the Specify stack details page, type a stack name and complete all the fields with the required information.
Click Next.
In the Configure stack options page, in the Permissions sections type the IAM role or IAM user name.
Click Next.
In the Review page, review the details of the stack.
Click Submit.

Results

AWS CloudFormation constructs and configures the stack resources specified in the templates.

What to do next

Next, you have to access the environment and get the user credentials.

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