In this project, you will use the command line interfaces (CLI) provided by Azure and Amazon Web Services to query, start and stop, and create cloud resources. Since the scope of the command line interfaces is very broad, we will be limiting ourselves to a very small subset of the CLI, to acquire some basic facility with it.
Overview
We have already created several cloud resources using the Azure Portal and AWS Management Console. These user interfaces are useful for beginners because they lay out all of your options in a visual way and guide you through the process of working with cloud resources.
At the other end of the spectrum, we learned how to access cloud resources using the Python SDK on both platforms. This allowed us to automate cloud-related tasks, but the price we paid was to set up a development environment, learn to authenticate from within a program, and learn the required Python APIs.
The Command Line Interfaces represent a middle ground between using the portals to work manually and having to set up a complete development environment. Here are some of the advantages of using the command line interfaces:
- Once you know the commands, provisioning cloud resources can be faster and less error prone than using the portals.
- Repetitive tasks can be automated easily without a heavyweight software installation.
- CLI commands can be integrated into much larger scripts for managing your cloud environment, including scripts with complex logic.
- Commands can be executed with only a terminal interface and do not require a GUI.
In this project we will do three exercises with the command line interface:
- Querying the status of cloud resources and formatting the command output.
- Starting and stopping a virtual machine, all in one script.
- Creating a virtual machine to meet specific requirements.
As with the other projects in this series, there are two parts to the project. You will complete each of the three exercises on both Azure and AWS.
Do the Project on Azure
Here is a link to the detailed instructions for doing the project on Azure:
Do the Project on AWS
Here is a link to the detailed instructions for doing the project on AWS: