This is a content of Ansible Labs used in RedHat Summit 2019. We are currently adjusting the content to be usable in any Ansible environment.
This repository contains practical exercises for the Red Hat Summit 2019 Instructor-Led-Lab (ILL)
Deploy and scale Microsoft Azure infrastructures and applications with Red Hat Ansible Automation.
Attendees will have hands-on access to Azure to perform the following tasks which build on one another:
* Working with the Azure Linux CLI
* Connecting Ansible to Microsoft Azure
* Create a Red Hat Enterprise Linux virtual machine in Azure using the Azure Marketplace.
* Create and configure an Azure MySQL PaaS database.
* Deploy an application on the RHEL virtual machine which utilizes the Azure MySQL PaaS database.
* Generalize the RHEL virtual machine image to create a golden image template for group deployments.
* Scale out the application to multiple servers using Azure virtual machine scale sets.
* Create an application gateway & load balancer to front-end the deployed application.
In addition, separate hands-on labs will be available to showcase:
* Big data workloads using Azure HDInsight.
* High-performance computing using Azure virtual machine infiniband interconnects.
* Deploying a private Azure Container Registry
* Hosting an Azure Application Service
* Running a containerized application using Azure Web Apps
* Launching an application in Azure Kubernetes Service (AKS).
* Serverless applications using Azure functions.
Content created by: Stuart Kirk & Zim Kalinowski with assistance from Steve Roach, Sasha Rosenbaum, Harold Wong, Jason De Lorme, Michael Yen-Chi Ho, Patrick Rutledge, Manesh Raveendran and others.
Base implementation for Function App Docker container comes from here:
https://github.com/Azure/azure-functions-docker-python-sample
The content of this program can be re-delivered, on request, to any Microsoft customer seeking to deploy open source workloads on Azure. Please contact [email protected] for additional details and to coordinate delivery of the program.