This guide will walk you through the process of deploying a Digital.ai Deploy Docker image to an AWS OpenShift cluster using a Helm chart.
This helm chart automates and simplifies deploying and managing Digital.ai Deploy on an AWS OpenShift cluster by providing the essential features you need to keep your clusters up and running.
- Administrators and DevOps with a working knowledge of Docker, Kubernetes, OpenShift, AWS, and Helm.
- Digital.ai Deploy users with an understanding of Deploy concepts
- What are we going to install?
- Before you begin
- Configuring AWS RDS
- Best practices
- Using an exisitng DB
- Using an existingMQ
- Sample values.yaml file
The Helm chart installs the following components:
- A single instance / pod of PostgreSQL database
- The RabbitMQ in highly available configuration
- Digital.ai Deploy Masters and Workers in a highly available configuration
Note: We recommend that you use an external PostgreSQL (e.g. AWS RDS) instance, for production grade installations. See configuring the AWS RDS instance with Digital.ai Deploy for more details.
- The minimum version of Digital.ai Deploy that is supported for the Deploy Helm chart is 9.6 or higher.
- You must configure the support for a Persistent Volume (PV) provisioner such as the AWS Elastic File System (EFS) in the underlying infrastructure along with a desired StorageClass, which you plan to use with Digital.ai Deploy .
- You will need a license file for Digital.ai Deploy in the base64 encoded format.
- You will need a repository Keystorefile in the base64 encoded format. For more information on keystore, see this article.
- xebialabs/xl-deploy - Docker Hub repository for xl-deploy
- stable/rabbitmq-ha - Github repository for RabbitMQ Helm Chart
- bitnami/postgresql - Github repository for Postgresql Helm Chart
- stable/efs-provisioner - Github repository for EFS Client Provisioner Helm Chart