Cloud computing has gone beyond an additional choice to a strategic choice for modern software architecture. These days, when it comes to cloud providers, every developer, engineer, and tech entrepreneur needs to make an architectural choice in favor of either Amazon Web Services (AWS) or Microsoft Azure. It is clear, that these are two major players in multi-billion dollar space and they offer an incredible number of computing, networking, storage, and AI services. However, AWS and Azure were born under completely different philosophies.
To start with, AWS pioneered the field of cloud computing back in the mid-2000s as a way to monetize its own infrastructure, used in hyper-scale e-commerce solutions. AWS takes the first place in the market share and is known for its enormous portfolio of services and immense power. Azure, on the other hand, was developed by Microsoft as a response to fierce competition for cloud market, taking advantage of existing infrastructure of enterprises (Windows Server, .NET framework, SQL Servers).
Choosing Between AWS and Azure: What Is Better for Developers
No matter whether it is a startup programmer working in his or her apartment in Austin or a software architect developing complex applications for a Wall Street enterprise, there is an ultimate need for every developer to understand what is the essential difference between AWS and Azure and how to unleash their potential.
What Philosophies Drive AWS and Azure?
As it was mentioned above, Amazon was founded in the spirit of creating the greatest infrastructure-based cloud provider, therefore having a very complex and functional cloud management console. When it comes to interacting with the console, developers have a great number of opportunities to dig into low-level computing, networking, storage, and identity aspects. Despite the incredible amount of functionalities, working with AWS sometimes can be overwhelming even for skilled engineers.
On the contrary, Azure, being somewhat late to the cloud space market, was created by a slightly different philosophy. It can be said that Azure is built as a platform to help developers visualize their resource usage, connections, and interactions inside the cloud environment. Azure resource groups provide users with great possibilities to abstract certain details in their applications making Azure a cohesive environment for development.
AWS vs Azure: CLI & SDK Support for Multiple Languages
As far as cloud-based solutions are concerned, there is Command Line Interface (CLI) and Software Development Kit (SDK) that help developers interact with their applications. As far as both providers go, CLI and SDK support are at the highest level, covering almost every imaginable combination of programming languages and operating systems.
Both AWS SDKs and CLI have great documentation and reputation in the industry for years. Azure provides its own CLI along with powerful PowerShell integration and great SDK support. On the other hand, Azure offers developers native integration with its cloud computing services, directly in Visual Studio Code and Visual Studio IDEs.
Virtual Machines & IaaS Computing Resources: Amazon EC2 vs Azure Virtual Machines
Having discussed developer interfaces, now it is time to look at cloud computing itself. When it comes to cloud-based resources, there is Infrastructure-as-a-Service paradigm. Here, developers have to use AWS Elastic Compute Cloud (EC2) in order to launch and run their virtual machines on top of highly configurable instances, based on Linux or Windows Server operating systems. AWS provides a great number of machine instances types, including Graviton CPUs, offering impressive performance-to-price ratio.
Alternatively, developers can use Platform-as-a-Service paradigm which would allow them to deploy their applications to the cloud without worrying about underlying computing, networking, and storage infrastructure. This way, Azure App Services would allow developers to launch web applications and APIs right from their Github repositories in a fully managed environment. AWS provides similar Elastic Beanstalk service, which, however, is more flexible in configuration.
Serverless Computing Paradigm: AWS Lambda vs Azure Functions
One of the most promising paradigms that was recently introduced to software developers is Serverless functions. AWS Lambda pioneered the field and became an industry standard in terms of serverless functions and microservices. AWS Lambda is capable of processing millions of requests per second without losing performance. Azure Functions, however, can be characterized as a great competitor of AWS Lambdas, being more flexible in terms of development environments.
Container Orchestration: Managed Kubernetes (EKS, AKS)
Another emerging paradigm that has gained a lot of attention lately is Containers. Both cloud providers have spent a fortune to develop robust and flexible container environments. AWS provides two major solutions for managing containers: AWS Elastic Container Service (ECS) and Elastic Kubernetes Service (EKS).
Elastic Container Service (ECS) is a native cloud management service offered by AWS, that would allow developers to quickly start managing containers in a cloud and get familiar with the concept. Another solution offered by AWS is Elastic Kubernetes Service (EKS) which allows developing enterprise-grade Kubernetes clusters.
Meanwhile, Azure offers an interesting service called Azure Kubernetes Service (AKS), which simplifies Kubernetes usage and makes developers’ lives easier. Apart from AKS, Azure also provides its own solution for deploying serverless microservices and containerized apps—Azure Container Apps powered by Kubernetes.
On the other hand, AWS introduces its own highly automated and hassle-free service called AWS Fargate, which greatly simplifies management of EKS & ECS clusters.
Databases & Storage Services
In order to deliver an outstanding product, one needs to pick the right storage solutions. Amazon, having the most extensive set of cloud solutions in the industry, provides a great range of solutions in the field of database infrastructure. First of all, AWS provides Relational Database Service (RDS) managed database service allowing to use different kinds of databases such as PostgreSQL, MySQL, and Oracle. In addition, Amazon provides its proprietary database called Amazon Aurora.
Microsoft, in its turn, provides Azure SQL Database—managed database running on top of SQL Server and offering the whole power of this product. In case, if a corporate environment uses SQL Server for databases, migration to Azure can be a fairly easy and seamless task, offering automation of many processes, performance management, and advanced threat detection.
NoSQL database solution on Azure side is Azure Cosmos DB, providing developers with incredible performance in terms of throughput and latency with guaranteed precise SLAs. AWS also provides a solution in the field of NoSQL databases, called Amazon DynamoDB—a managed, cloud-native, serverless, highly scalable key-value and document database. DynamoDB allows achieving latency in single-digit milliseconds for all applications.
Continuous Integration & Continuous Deployment
Another factor that determines efficient and productive development process is continuous integration and continuous delivery or deployment. When comparing AWS and Azure, one can say that Microsoft has a great advantage in terms of CI/CD and DevOps. This is because of the fact that Microsoft has acquired and successfully integrated the biggest Git provider, Github. In addition to that, Microsoft launched Azure DevOps, providing a variety of CI/CD and DevOps options to developers.
Azure DevOps would allow to develop agile projects with source code in Azure Repositories and deploy applications through Azure CI/CD pipelines or github actions. That way, deployment becomes as easy as possible for developers—developers just have to write workflow in their Github repository and push it to Azure via actions.
On the other hand, AWS uses so-called “building block” approach to provide services that will help developers build their own CI/CD pipeline. Three major services to be used here are:
1. CodeCommit—source control service;
2. CodeBuild—application compile and test;
3. CodeDeploy—deploy the compiled application to the target environment (EC2 instance, containers, etc).
Although AWS approach might seem rather complicated, once configured it would provide great flexibility and possibility to modify or replace some of components of pipeline.
Infrastructure as Code: JSON and YAML Languages
When provisioning cloud-based infrastructure in code, developers have the choice of using Amazon CloudFormation or AWS Cloud Development Kit. CloudFormation is a great declarative cloud management service helping to configure resources in AWS infrastructure using JSON. Also, AWS provides Cloud Development Kit, a powerful tool which allows developers to describe cloud infrastructure using programming language of their preference: Python, TypeScript, JavaScript, etc.
Microsoft, in its turn, introduced its own solution in the field called Azure Bicep—a declarative language based on YAML used in Azure Resource Management.
Machine Learning & Artificial Intelligence
Last but not least, nowadays machine learning and artificial intelligence solutions are extremely popular among software developers in the US. For developing intelligent applications one needs cloud solutions, allowing them to easily train, deploy, and update their machine learning models. Amazon offers AWS SageMaker which helps developers and data scientists preparing data, training their model, and deploying them in AWS infrastructure using web application.
Microsoft, having acquired multi-billion dollar company OpenAI which specializes in Generative AI solutions, became a great partner for developing AI. Microsoft Azure provides developers with Azure OpenAI service, allowing them to easily and quickly deploy their applications powered with OpenAI generative models such as GPT-4.
Moreover, software developers often require basic cognitive services such as computer vision, natural language processing, translation, and speech recognition. Both AWS and Azure provide services in the field that allow developers to simply plug and play them into their applications. While AWS provides separate products such as Rekognition, Comprehend, Amazon Transcribe, and Amazon Translate, Azure, in its turn, uses Azure Cognitive Services—collective name for AI-based services.
Finally, AWS and Azure services guarantee an outstanding level of performance allowing developers to use their services for training and deploying any algorithm without losing its performance.
Conclusion: Which Cloud Provider is Best for You?
In conclusion, it is important to highlight, that choosing AWS or Azure should be done considering the following factors. Neither of cloud providers offers something better—choice should be made depending on specific needs and requirements of your software. Therefore, choose AWS or Azure solely based on your current tech stack, preferences, and business requirements. Here are tips that might be helpful when deciding on which provider to choose.
Choose AWS if:
you are developing a brand-new cloud-based application and require comprehensive ecosystem of services and integrations;
your team requires great flexibility in terms of customization and infrastructure;
your application requires great multi-region scalability of noSQL databases or replication (AWS DynamoDB);
you need portable skills and your proficiency in AWS is highly valued by IT companies.
Choose Microsoft Azure if:
you are using Microsoft technologies and products in your enterprise environment;
you require native integration of cloud services with your favorite IDE and repository system;
you need robust AI/ML solution and access to advanced language models;
you prefer more visualized and structured environment with fewer interactions with low-level components.
Frequently Asked Questions (FAQ)
Is AWS more difficult for developers to learn than Azure?
AWS is known as one of the most complex cloud solutions for developers purely because of its nature. AWS philosophy suggests exposing low-level infrastructure components to developers, therefore giving a developer more control and flexibility in customization. On the contrary, Microsoft Azure is designed to abstract certain details from developers making its ecosystem more visual and cohesive.
Can I deploy non-Microsoft-based applications in Microsoft Azure?
Many people assume, that Azure provides cloud computing services exclusively for Microsoft ecosystem. Nevertheless, this could not be further from the truth. Half of the workloads running in Microsoft Azure are Linux-based and Azure supports many open-source languages such as Node.js, Python, and Java in addition to .NET Core.
How expensive are Azure for enterprises compared to AWS?
At a basic level of cloud services, prices in Azure and AWS are pretty much similar and, in many cases, comparable. Both cloud services providers follow pay-per-use approach with per-minute billing and free-tier services for new customers. Azure, in addition, can offer cheaper solution for enterprises, using Azure Hybrid Benefit, allowing running Windows Server and SQL Servers.
AWS vs Azure: Difference in identity management ?
As far as AWS goes, Amazon Identity and Access Management (IAM) is its core service responsible for managing accesses to all other services provided by AWS. AWS IAM allows fine-grained access policies configuration through JSON files. On the other hand, Microsoft Azure, apart from internal cloud management services, offers complete ecosystem of identities and authentication services (called Azure AD or Microsoft Entra ID).
Which provider provides better AI services?
In terms of advanced AI services, both Azure and AWS offer similar services. However, Azure OpenAI, being integrated with multi-billion dollar company, is better for developers who want to develop AI applications using cutting-edge technology.
