Cloud costs: Shut those VM’s down

The public cloud is fantastic for numerous reasons, if you’re not faced with some restriction such as where you data lives or other factors, then my advise is get away from private clouds and get to the public clouds as fast as your legs can carry you!

However once you’re there it’s not all plain sailing, if you let a team of people loose to play with with all these new toys, on the back of your company’s credit card, then costs can start to accumulate very quickly!

Sometimes, your VM’s are not being used for production and what invariably happens, is that these machines get forgotten about or are left running for no good reason, now while there are a few ways to capture such scenarios,  what I’ll show you now is a very quick way of scheduling those known VM’s to shutdown (or start up) as on a predefined schedule,

AWS

For AWS the easiest way of scheduling a single standalone VM to shutdown is to use the AWS Data Pipeline service.

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Lets quickly show the workflow:

1) Create new Pipeline with CLI Command

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2) Enter the Stop EC2 CLI commands

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Note: This field only shows as one line of text vertically in chrome so I modified to styles to show the full command.


You can see that i have two different stop commands, I could combine these into the one command with the two IDs however if one fails then they both fail, this can be problematic if for example an Instance gets terminated.

3) Schedule

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4) Set log file bucket

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5) Select role

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Choose custom and then select the two defaults.
Security Note:  Roles needs to be configured to allow Data Pipeline access to your VM’s, please see here: https://aws.amazon.com/premiumsupport/knowledge-center/stop-start-ec2-instances/

6) Done

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That’s it, you now have a scheduled task that will switch off your vm’s nightly. It should be noted that this will start a micro data pipeline ec2 instance VM with a default run time of 50 minutes, so you need to ensure the end justifies the means, better yet reduce the run time by editing the workflow to e.g. 15 minutes.

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Azure

=== note: The following is much easier as of 2017, Dev/Test automation is integrated in the menu on each VM for scheduling up time ===

In order to achieve the same results with Azure we are going to select Azure automation,

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If you’re familiar with Azure you will know that there are currently two ways of creating VM’s, the classic approach and the RM (resource manager approach). In this post I’ll show you the RM approach, but feel free to substitute classic in it’s place with a nearly identical approach.

1) Open or create an Azure Automation account.

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2) Edit Assets

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Add a variable for the AzureSubscriptionId you’ll be using
Select your service principle account, you’ll have to search for it to appear.

3) Runbook

We have two options now, we can either use some powershell or some graphically defined workflows, let’s do this with a graphical version, we don’t need to create this, we simply import from the gallery.

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After importing choose Edit on the runbook

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4) Set inputs

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Then we set the two Assets we provided earlier and optionally a ResourceGroupName (to stop all vm’s in a resource group) or a VMName The “Auto” you see above isn’t a keyword, it’s my badly named ResourceGroup.

5) Publish

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6) Set schedule

Go back to the Runbook and choose schedule

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With the schedule you can specify any of the input parameters and override the defaults if you so wish.

Security Note: Much the same as Azure you’ll need to ensure you’ve permission to access the VM’s from Azure Automation, the best option is to create a SecurityPrinciple application. See: https://azure.microsoft.com/en-us/documentation/articles/resource-group-create-service-principal-portal/

 

Conclusion:

While it does look like the Azure approach is much more convoluted it is much more powerful, e.g. it is very easy to extend the azure run book to check all VM’s for a “Production” tag and only shutdown vm’s if they are not production (because that would be bad right!); with AWS, we are simply relying on a feature of Data Pipeline that allows us to run simple cli commands.

Pricing is much of a much-ness between each, with Azure you can run for free (to a limit)

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AWS the 15 mins with a micro instance is not even worth worrying about.

Web App deployment to AWS and Azure

As promised, hereby the first instalment of the AWS vs Azure blog post saga, again I’m trying to remain impartial throughout.

What I intend to outline is at this stage is the show to get started deploying a new application to AWS and to Azure from within Visual Studio. I’m sure there are those of you that are shouting, “.NET, Visual Studio, Azure? Of course Azure will do it better!!!” however rest assured this is only the first of a few posts related to Azure App Service and AWS elastic beanstalk and AWS doesn’t fair all that badly.

Sample Application

The sample application in this case is just a File/New ASP MVC5 project using .net 4..6.1, I’m only hitting the home page as a test and not worrying about databases for now (databases will make another interesting series of blog posts!).

AWS Elastic Beanstalk

AWS has a AWS Toolkit plugin for Visual Studio, this allows you to view and manipulate AWS resources

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It also lets you Publish Applications to AWS by right clicking on the solution and choosing “Publish to AWS”

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Once you choose this option you’ll be presented with a dialog that lets you choose your environment or create a new one.
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If you don’t already have one, lets create one, you will choose a name for the environment

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Next you choose your instance size (the underlying VM size, or any custom Amazon Machine Image you’ve created previously), other options of interest are, use non-default VPC, this is basically the network you’ll be running on, all AWS accounts get a default VPC per region (and if you delete it you’ll need to contact AWS to get it back!). The option of single instance environment is selected here as this is just a test. If i wasn’t running in single instance mode, I would be able to Enable Rolling Deployment to keep my app running while it gets updated (more about that here: http://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features.rollingupdates.html)

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Lastly we choose the application settings, I’m just deploying a .net 4 runtime debug application.

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Once you review and finish, you can see your application start deploying on the portal

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Once it’s finished which can take a few minutes after the upload you should see the Health go Green and you can access your application

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Note: If you’re following along and wish to stop this ElasticBeanstalk environment to minimize costs/free tier bandwidth, then please ensure to terminate it from the ElasticBeanstalk section of the console, Stopping the underlying EC2 instance will only serve to signal the autoscaling group it belongs to, to start a new instance and restore the health of this application.

Azure App Service

Now lets deploy this same application to azure. Right click on solution explorer and choose Publish

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Choose to Azure

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Like AWS where we chose a server environment we need to choose an app hosting plan, with Azure you can sign up for a free trial, if you have a subscription you can choose to deploy a free cloud app (you get 10 free per region, there are some limitations which we are not concerned with just now).

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After creating this new hosting plan we arrive back at the publish dialog

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Visual Studio then starts the publish task and opens the application in your default Visual Studio specified web browser.

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You can also see your new application seeding life in the Azure portal http://portal.azure.com

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Summary

So in this blog post I’ve run through how to deploy applications to PaaS offerings on AWS and Azure, in the next post I’m going to drill down and and do some more comparing and contrasting of these two applications, stay tuned!

Recent Tweets

Note: For Customization and Configuration, CheckOut Recent Tweets Documentation

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