In few of my previous articles listed below, we have learned how to create different Virtual Machines in Azure, using the Infrastructure as a Service offering by Microsoft.
You can utilize these Virtual Machines for multiple purposes depending on the requirement that you might have. You might, then, host your different types of workloads on these VMs.
There might be cases where you would like to shut-down the Virtual Machines when they are not in use. For example, Non-business hours, Weekends etc.
Shutting down (deallocating) the Virtual Machines would definitely reduce the costs because it doesn’t make sense to have them up and running when you are sure that your users are not going to use them for the specific set of time.
In one of my previous articles, we have discussed about Shutting down the Virtual Machine that is associated with a Dev/Test lab.
Microsoft Azure team has recently announced a similar Auto-Shut Down for regular Virtual Machines. You can shut-down your Virtual Machine at a specific time based on the time-time that you configure.
Let’s see how to shut down the Virtual Machine.
Log into your Azure account and navigate to the Virtual Machines that you would like to shut down, as shown below.
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Clicking on the Virtual Machine, you will be taken to the following page.
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Click on the “Auto Shut down” menu, as shown below.
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Clicking on the Auto-shutdown, you will be taken to the following blade where you can configure the details for shutting down the Virtual Machine.
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As shown in the above picture, click on the “ON” button of the Enabled field and click on “Save” to save the changes.
That’s it. We have configured the Virtual Machine to get auto shutdown at 10:00 A.M (as per the above screenshot). You can specify any time slot that you would like along with the Time Zone.
Below is the screenshot taken around 10:03 A.M after the VM got shut down.
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Summary
In this article, we have learned how to configure Auto-shutdown for a Virtual Machine that is created using Infrastructure as a Service offering from Microsoft Azure team.
You can read the original article
here.