Why I chose Amazon Web Services (AWS) over the other Cloud Providers
Last Updated on December 6, 2021 by Editorial Team
Author(s): Michelangiolo Mazzeschi
Originally published on Towards AI the World’s Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses.
Which Cloud should you go for?
The Cloud is one of the first choices you are going to make in your developer career that you really do not want to get wrong. Most of the time is not up to you, every workspace you will work into will likely have a different choice. My division at Ernst&Young was partly using Microsoft Azure, for example, while the previous employer was using Google Cloud Platform, while many of my friends are using Oracle Cloud Infrastructure.
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It is very unlikely that when working for two different places you are going to use the same Cloud in a row. However, what if you are a developer and still have not found your first serious job as a Data Scientist? One of the best things you can study to improve your skills and make your curriculum more appealing is one of Clouds.
What are the options?
These are the main Cloud options you can pick from:
- Amazon Web Services
- Google Cloud Platform
- Microsoft Azure
- Oracle Cloud Infrastructure
- IBM Cloud
- Alibaba Cloud
When you pick a Cloud, there are several things you may want to consider. In the long-term and with a sufficient level of experience, every Cloud has its pros and cons, but what I will mostly take into account is the fact that, if you are reading this article, you are haven’t made up your mind.
I imagine that the most sensible feature you wish to know immediately about the Cloud is price. To register for any of the Cloud providers you necessarily need to use a credit card, so you can make peace with yourself even before starting. The price is a more sensible argument when scaling, in fact, there might be a difference of millions. When you are small and just need to run a few lines of code to test your ideas and projects, there is almost no difference between Clouds.
However, remember that the first year on any Cloud you can choose from several services that will remain completely Free until your free credits have expired. For example, AWS will give you 750 FREE hours to run a virtual machine.
These are the services that you are likely to experiment with:
- Database (SQL)
- Storage (NoSQL, files)
- Virtual Machines
- Serverless computing
For small projects, you might need to spend less than 1 USD per month for any of those Clouds. For example, I am running my own discord bot 24/7 using an EC2 instance (t2.nano), and it is costing me 4 USD per month, which is the peak of my expense, so far.
I wrote several articles where I am fully against no-code interfaces, as I consider them much more complex compared to raw coding. This is true when you have to use different software for your specific uses (let alone all the registration and signup processes). However, the Cloud is different, mostly because you have all the services available at once.
This is the area where AWS shines: for example, one service which allows you to code directly on AWS instead of sending code from your workspace is AWS Lambda. If you have thousands of lines of code you are necessarily going to send your code using packages, but for simple experimentation, coding on AWS makes everything easier.
Coding to activate and manage Cloud services becomes only necessary when you scale, and whatever you need to manage cannot be done with manual activation. Again, if you scale you are likely spending thousands, even millions of dollars for your project, which is definitely not the case. No beginner starts interacting with the Cloud by raw code, don’t you worry about that.
It Keeps evolving
We can say that every Cloud is expanding. The race now sees AWS as a leader. Microsoft has made heavy investments in its Cloud, especially to improve its Machine Learning services, but no one knows if it will be enough to surpass AWS.
Still, Azure lacks most no-code interfaces that make AWS accessible to all beginners. While time passes, especially due to the pressure from the competition, every Cloud is trying to increase its size, diminish its price, and include more content and services into its service package. A few years ago, for example, text recognition SAAS was introduced in every Cloud and can be available with a few clicks.
Which Cloud is the easiest to learn? I will go with AWS, not only because it is the Cloud that I am learning at the moment, but compared to Google Cloud Platform, for example, it provides you with a very intuitive interface.
This is something you want to consider to avoid becoming frustrated quite often when learning new things.
When you are scaling and you need to spend millions, there might be very precise reasons on which Cloud you may want to choose, but when you are starting, all factors can point you in the same direction: choose the cheapest and the user-friendliest Cloud.
Why I chose Amazon Web Services (AWS) over the other Cloud Providers was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.
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