Azure Virtual Machine : Pricing myth and Create one in minutes
Credit: Microsoft Azure [https://azure.microsoft.com/en-us]

Azure Virtual Machine : Pricing myth and Create one in minutes

The problems of traditional physical server

Ever wonder running your server computer 24/7/365 without bothering about the power and connectivity issue? Have you ever thought about dumping your years old (almost obsolete) server hardware which was super costly when you bought it just a year or two ago? Cloud based Virtual Machines give you the opportunity to leverage their infrastructure in a very minimum price. You can rent their hardware for a time you want and run your own software in the operating system you choose. This type of rented machine is generally known as Cloud based Virtual Machine. Like other cloud vendors, Microsoft Azure also offers Virtual Machine. Azure Virtual Machines (AVM) is one of several types of on-demand, scalable computing resources that Azure offers.

Whenever I give any talk on Cloud based Virtual Machines (VM), the immediate response I always receive from the audience is "But isn't it very costly?" So I try to explain, what do we actually mean by "Cost"? Is it just the cost of hardware we buy? What about the Software? What about the Server's huge bandwidth allocation cost we pay every month to ISP? How about the other infrastructure (electricity / power backup, fiber optics cable etc.) and maintenance cost to keep the server running? Have we ever considered the depreciation cost of the purchased hardware? In every couple of months computing power is getting higher with lower price, so what should we do with the newly bought super costly hardware after 1 year? In which Account should we put the salaries of the big network administration team? Obviously server maintenance consumes a big chunk of their time which translates into as Salary. After buying a server, even if we shut down it for 8 hours per day, it doesn't cost us less, because we already spent the money on it.

If you are well aware of operating company finance then you already know there are a lot of more areas of expenditure which is consumed by the 'Server' passively. Like discussion/meeting between the top management personnel (who has very high salary) about the purchasing and upgrading of the hardware/server in office time (meeting time should be also translated as Salary). Changing the size of the server according to the need (upgrade when needed or downgrade when we don't need) supposed to be super costly in physical servers.

So, in my personal opinion, if the Network / Server Team is enough knowledgeable, transparent, and honest with the Finance team, then there is no reason the company management doesn't want to take the blessings of the modern cloud infrastructure. And that's why most of the companies of all types in the world is rushing towards Cloud Infrastructure.

So, you are convinced. But, now what? How can you decide the size of the VM you need? Where should you put it? How can you make it up and running? Let me help you to get you started in shortest possible time.

You can see a lot of folks talking about the placement of the VM to a region. You may think that placing the VM nearest to you is the most important factor, but it isn't. Most of the business applications of the current world doesn't get massive traffic like Facebook, LinkedIn, Salesforce etc. Targeting medium or below medium traffic base doesn't have a need for a nearest VM. Instead, the architect should focus on the cost, and region's other service reputations like Blob Storage, CDN, App Service, Database Server etc. I want to show you a real pricing difference below.

Spin up a Azure VM

The price you see here is not equal the price you see in the public pricing page. Interesting, isn't it? It seems Microsoft is more focusing on the serious costumers who are ready to spin up a VM instead of the general visitors. :)

In the Southeast Asia (Singapore Data Center) the pricing is much higher than the same in the West US 2 (California Data Center) region.

For example, let's create VM in Southeast Asia region. This datacenter is located in Singapore.

The price of DS2_V2 instance is more than 117 USD.

On the other hand, if we choose West US 2 (California) region, the VM price reduced significantly.

It is less than 85 USD.

A difference of $32, and it is huge.

While creating you may also consider what type of disk type you choose. We have selected SSD for the above price.

There are some other things we need to add beside choosing the Server's size. For example, we need to create a network (virutal) by which the PC will be accessed by Azure's main infrastucture.

And we need to specify the Ports we want to open for the VM.

Even we can add extensions which will be installed by Azure in inside of the VM.

We need to create a storage drive where the VM will be placed. You can think it like a external hard disk and drives and folders.

And we can specify a Public IP so that we can access this VM from outer world (aka. web).

After completing the above configuration, we are good to create our own Virtual Machine.

But that's not it. To complete the server setup, we should do something more inside of the VM. To do those, download the rdp file by pressing connect button.

Go inside of the vm by opening the rdp file and providing your username and password.

We need to install some couple of more services / features inside of the VM. Like below. Select Role-Based or feature-based installation.

Keep it as it is you get in your machine.

Add IIS

Check the below options.

Enable the below features in your machine.

And these also.


So, after completing the above steps, if we want to browse the URL, we should see the below image of Default IIS page.


Thats it. We will talk on Azure VM again. Till then, happy #clouding

Send me email at [email protected] to let me know if you have any question.

[??? ?? ??????? ?????? ???? ???, ??? ??? ?????? ????]

Kabita Roy

Technical Project Manager at DataSoft Systems Bangladesh Limited

7 年

Vaia, It will be helpful if u please write an article on Azure machine learning and how can we use it ..

Prof Md Adnan KIBER , PhD

Higher Education Professional

7 年

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