Introduction
When I developed a small portfolio application, I wanted a fully serverless backend so I wouldn't have to worry about server management. I also took the opportunity to practice AWS SAA exam concepts and chose to try AWS SAM as a framework. Below I share my experience and how tools like SAM can fit into custom application and custom software projects we develop at Q2BSTUDIO.
What is AWS SAM
AWS SAM is a framework that lets you define serverless infrastructures in a single YAML file and deploy Lambda, API Gateway, EventBridge, S3, and other resources with a single command. This approach makes it easier to maintain infrastructure as code, version it in Git, and automate deployments—something essential when we deliver custom software solutions and AWS and Azure cloud services at Q2BSTUDIO.
Why I chose it
I chose SAM because I was looking for operational simplicity and traceability. I wanted a serverless backend, less maintenance, and the ability to test endpoints and triggers locally before uploading them to the cloud. For a studio that offers custom applications and integrates business intelligence and Power BI services, being able to control API Gateway and EventBridge from a single file brings clarity and reproducibility.
What I learned
Getting started with SAM is very fast thanks to the official tutorial and the initial sam init tool. I was able to move configurations I previously did from the console into code, keep everything in repositories, and collaborate better with the team. Local testing increased confidence in deployments. Additionally, Python support and dependency management through requirements.txt made the packaging process simple. These practices are especially useful if you integrate artificial intelligence or AI agents into your solutions, or if you need to incorporate AI capabilities for businesses with cybersecurity controls.
Who AWS SAM is useful for
I recommend SAM to teams that create more than a few Lambdas, to those who value clean and versioned infrastructure, and to those who want to test locally before deploying. In consultancies like Q2BSTUDIO, which develop custom software and custom applications and offer AWS and Azure cloud services, SAM speeds up delivery and reduces errors in production.
How it fits with Q2BSTUDIO services
At Q2BSTUDIO, we combine custom development with expertise in artificial intelligence, cybersecurity, and business intelligence services. We use serverless architectures for projects that require scalability and cost efficiency, and we complement them with Power BI solutions for visualization and analytics. We implement AI agents and AI integrations for businesses to automate processes and improve decision-making, always with cybersecurity and compliance controls.
Final reflection
AWS SAM simplified my portfolio project and brought order to the development cycle. If you're learning AWS or looking to explore serverless applications in custom software projects, I recommend trying SAM. At Q2BSTUDIO, we can help you integrate solutions with artificial intelligence, AI agents, business intelligence services, Power BI, and secure cloud architectures with AWS and Azure cloud services so your project is scalable, secure, and efficient.
