Empowering Software Development through Cloud Platforms: Comprehensive Guide to AWS, Azure, and GCP

Contemporary software development inevitably involves the use of cloud technologies. They offer a slew of important benefits, including flexibility, scalability, accessibility, and resource savings—all of which are vital for the effective digital transformation of business.

Cloud technologies vary in type and purpose, so choosing the right tools is also very important. For example, when working on the Gorde platform for Superior Memorials, an important step was the transition from Heroku services to Amazon Web Services, which increased system stability while reducing costs (we wrote about this in the corresponding case study).

Amazon Web Services (AWS)

• EC2 (Elastic Compute Cloud) — virtual servers that can be scaled depending on the need.
• S3 (Simple Storage Service) — a service for storing large volumes of data.
• Lambda — a service that allows you to run code in response to specific events without the need to manage servers.
• RDS (Relational Database Service) — a managed service for working with relational databases.

We used AWS to create the ecosystem TAS Platform (read the case study) for the company NextMed. Amazon Web Services power the application Xtract One (more about it in this case study), commissioned by XLabh Innovations. However, these are just a couple of examples — in fact, we use Amazon Web Services in most of our projects (we talk about them in the Case Studies section).

Microsoft Azure

• Virtual Machines — virtual machines that can be configured and scaled depending on the need.
• Azure Functions — a tool that allows you to create and run small pieces of code (functions) in the cloud without the need to manage entire applications or servers.
• Azure SQL Database — a managed SQL database that automatically scales depending on the load.

Google Cloud Platform (GCP)

• Compute Engine — virtual machines that can be configured and scaled depending on the needs.
• Cloud Functions — allows you to create and run functions in response to specific events without the need to manage servers.
• BigQuery — a fast and powerful service for analyzing large volumes of data.

It seems that all these cloud platforms have a fairly similar set of capabilities, and they duplicate each other quite a lot. However, they differ in minor nuances and the orientation of the entire infrastructure as a whole, so choosing a platform is also an important stage in planning development.

Cloud platforms play a key role in modern software development. AWS, Azure, and GCP are three of the most popular and widely used cloud platforms in the world, each offering its own set of unique capabilities and tools. However, sometimes their capabilities are not enough, but that is a completely different story.

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