In today’s rapidly evolving technological landscape, the development of web applications requires flexible solutions. This article explores a successful case in meeting the client’s requirements for expanding application functionality without being tied to deployment.

The key benefit of the solution is the ability to dynamically manage and extend application functionality without compromising performance. The client expressed the following requirements:

• Simplify supporting and managing application functionality to easily add, update, or remove mechanisms, as well as configure limitations for each mechanism;
• Enable users to create custom functionality by providing tools and instructions for adding their elements;
• Maintain application performance and loading speed during functional expansion.

Now let’s discover how to achieve this results in four basic steps.

Step 1: Choosing the Technology Stack

The selection of technology for implementing a dynamic application should consider the main priority – flexibility. Leveraging AWS Lambda functions facilitated application scalability without the need for restarts or deployments. AWS S3 was chosen for storing and deploying builds to AWS Lambda, with seamless integration between these services, triggering Lambda based on events in AWS S3.

Step 2: Library-Builder for Functional Elements

At this stage, we create a unified library-builder, offering a single interface for all application functional elements. This interface served as a contract between the server-side of the application and new functional mechanisms. Overcoming the limitation of having only one “handler” in the Lambda function was achieved by utilizing a higher-order function. The final step in library-builder development was its publication on NPM.

Step 3: Registration of New Application Mechanisms

We achieved dynamic registration of new elements by integrating AWS Lambda with AWS S3. The process of creating, packaging, and uploading new mechanisms was automated through the application’s web interface. The AWS Lambda function processed uploaded builds, created new functions, and updated the project database with a record of the new mechanism.

Step 4: Testing and Concept Validation

We used universal mechanisms to validate the concept, including REST, CODE (supporting multiple programming languages with results returned in JS format), and CLOUD DB. These mechanisms automated data processing and storage, offering the potential for implementing new mechanisms and automating complex processes.

Results and Conclusions

We created serverless architecture, which boosted the project with more opportunities:

• Easy creation of new functional elements;
• Empowering users to create custom elements;
• Automating the process of uploading and registering new elements;
• Expanding application functionality without increasing weight or complicating support.

This experience illustrates how innovative technologies and a meticulous approach can enhance development processes, making the software more flexible and scalable.