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-commercesource 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.
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.
Note: CloudOps for Azure deploys Cluster Autoscaler, which is the standard for autoscaling virtual machines in a Kubernetes cluster. Microsoft shows Cluster Autoscaler as being in a Preview state. For production workloads, remove Cluster Autoscaler and manually scale the virtual machines in an AKS cluster until Cluster Autoscaler is no longer in Preview.