Introduction to CloudOps for Azure

important

CloudOps for Kubernetes replaces CloudOps for Azure. CloudOps for Kubernetes is a re-engineering of CloudOps for Azure to add support for both Azure and AWS (Amazon Web Services) deployments using cloud agnostic tooling.

Elastic Path CloudOps for Azure is Elastic Path’s automated approach to run Elastic Path Commerce in a developer ready fashion. It utilizes the Microsoft Azure Kubernetes Service (AKS), which runs Docker containers in a Kubernetes cluster supported by the Azure Database for MySQL. Helm deploys and manages the cloud native services.

By utilizing CloudOps for Azure, users are able to have a stock version of the Elastic Path Commerce solution running in Azure in a short period of time. With Kubernetes’ tooling, developers can customize and deploy developer ready stacks where they can debug code running in Azure. Given the broad adoption and standardization on Kubernetes, Ops teams have a solution to which they trust and that adapts to their needs.

Build and Deployment Features

CloudOps for Azure provides a way to build and run a developer-ready deployment of the Elastic Path Commerce stack. With CloudOps for Azure, you can:

Bootstrap an auto-scaling, load balancing Kubernetes cluster using Azure’s AKS service and HAProxy based Ingress Controllers
Use the included Jenkins server to build Docker images from the ep-commerce source and push them into an ACR (Azure Container Registry) repository
Create and populate an Azure Database for MySQL server with catalog content
Deploy the Elastic Path stack using the built Docker images

Note: Elastic Path CloudOps for Azure does not test any of the artifacts, do production-grade monitoring, or logging infrastructure for the deployment.

Production Usage

For users evaluating CloudOps for Azure, a best practice for all deployments is to ensure that the scaling of nodes in an AKS cluster provisioned and managed by Microsoft is thoroughly tested. As a result, it is encouraged for anyone evaluating CloudsOps for Azure to thoroughly test scaling of the AKS cluster in different production-like scenarios.