AWS AI or Azure AI - Which Cloud Is Better? Critical Factors To Consider

Cloud computing has proven its worth in the world of business and personal computing. However, the inclusion of AI has become pivotal in the way we do business in the Digital Age. With plenty of cloud service providers on the market, Amazon Web Services (AWS) and Microsoft Azure are among the top two options that lead the way.

So the question we must ask in this guide is the following: AWS AI or Azure AI - Which Cloud Is Better? Further, we’ll discuss the critical factors that you’ll want to consider before making a decision. Let’s take a look at the following list below so you can be able to decide based on your own personal needs and preferences.

Comparison of AI services

Both AWS and Azure offer AI services that are highly rated. Each one has a wide variety of tools and services that aim to serve its users. AWS is known for its robust features including machine and deep learning systems. 

It also possesses natural language processing services. AWS has SageMaker and Rekognition, both are machine learning tools that have proven themselves to be versatile and easy to use. SageMaker can be great for deploying machine learning models while making it useful for building and training purposes.

Meanwhile, Rekognition uses image and video analysis. This tool in particular has been useful for clients both in business and even government applications. It has been instrumental in recognizing different types of movements, objects, and even detecting inappropriate content in video files stored in S3 or video streams. 

Now, let’s take a look at Azure. It offers its own machine learning capabilities as well. On top of that, it also offers cognitive services. This includes their speech-to-text, text-to-speech, speaker recognition, and speech translation services. 

Finally, Azure AI as a whole has the ability to create applications that are intelligent, market-ready, and responsive from start to finish. It uses customizable APIs that are pre-built to help make the entire process easier.

Infrastructure and scalability

One of the best considerations to look over is the infrastructure and scalability of each platform. That’s because it will be important in how much of a role it can play for AI applications. During their development, both AWS and Azure have focused heavily on making sure their infrastructure is easily scalable for supporting AI-based workloads.

AWS has Elastic Compute Cloud or EC2 while Azure offers Virtual machines. So how do the two stand out? AWS has auto scaling that is powered by machine learning while Azure will utilize metrics based on both host and applications that are used.

AWS uses predictive scaling, which Azure lacks. If you hold scalability automation to a high standard, it’s clear what would be the best choice here.

Cost consideration

Even though the capabilities and infrastructure are worth considering, the financial aspect of your decision cannot be ignored. Rather than see it as a “cost”, consider it as an “investment” for your business. Both AWS and Azure offer different pricing models for their AI services.

To begin, AWS operates on a pay-as-you-go-model. This is considered a great model for those who don’t want to spend too much upfront. For example, the price of SageMaker is based on the training and inference usage.

With AWS, you get excellent flexibility. However, it is important that you monitor your usage carefully to avoid any unwanted costs. 

Azure operates on the same pay-as-you-go framework for their services. When it comes to total pricing, AWS seems to have the edge in terms of affordability. At the end of the day, it’s more than just the price you’re investing in.

It’s a matter of what you’re actually paying for. Is it worth spending money on something that is satisfying your needs and preferences?

Optimizing the costs involves understanding what your specific requirements are for using AI workloads. This means you’ll want to choose the right instances and services that best fit you. To make the determination based on your budget, you can use a cost calculator that both providers offer, which can help you make informed decisions based on how much you intend to spend.

Integration with development tools

You want the integration of your preferred development tools and frameworks to be seamless. Thus, you want every AI project to be smooth when it comes to implementation. As such, both platforms offer a wide variety of libraries, frameworks, and programming languages that are used in AI development.

Specifically, AWS supports the TensorFlow and PyTorch frameworks. Meanwhile, Azure’s Machine Learning services can easily integrate with Jupyter Notebooks. Ease of integration into existing workflows should also not be overlooked.

AWS’s CodeStar and Azure DevOps are great for currently existing AI projects so you can be able to integrate into a much broader software development process.

Security and compliance

If there is one consideration that is the most critical - security and compliance should be addressed. Sensitive data can be handled on cloud platforms with AI compatibility. Thus, it is important to find a platform that offers a wide selection of security features to provide excellent protection for AI applications and data.

AWS has Identity and Access Management or IAM while Azure utilizes the Active Directory for managing your identity along with Key Vault to manage your keys accordingly. It is important to utilize a platform that also has the ability to follow compliance standards like GDPR and ISO 27001 - making it easier for businesses to utilize a platform without having to worry about violating such data management regulations.

Let Oamii Tech Handle Your Cloud Needs?

Whether it’s AWS or Azure AI, Oamii Tech will help you decide which platform will be the best fit for your business. We hope that this list of critical factors has helped you get a good idea of what to choose. If you have any questions, Oamii Tech can answer them so you can have peace of mind knowing how to handle an AI-compatible cloud that handles all of your needs.

Don’t wait - contact us today and we’ll point you in the right direction.