Home
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.
Getting started
You can deploy HCL Workload Automation quickly and easily on Amazon Web Services (AWS) using AWS CloudFormation resources.

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

Getting started

You can deploy HCL Workload Automation quickly and easily on Amazon Web Services (AWS) using AWS CloudFormation resources.

About this task

This topic describes the main steps to complete before deploying the product, such as subscribing to HCL Workload Automation on AWS Marketplace.

You can find the procedure to subscribe to HCL Workload Automation on AWS below.

Procedure

Go to AWS Marketplace and log in.
In the home page, click on View all products.
In the Search field, type HCL Workload Automation and press Enter.
In the result page, select HCL Workload Automation.
In the product page, click Continue to subscribe and proceed with the subscription.

Results

You have now subscribed to HCL Workload Automation on AWS Marketplace.

What to do next

To proceed with the deployment of HCL Workload Automation, you have to create stacks on AWS CloudFormation.