About three months ago I took part in a challenge that excited me and I decided to document the development process, the technical decisions made and the lessons learned during those intense days.
Note the project is just beginning and what I share reflects what was built in a 3 to 4 day challenge, there is still a lot to develop.
The challenge consisted of creating a complete application with frontend and backend, authentication, data persistence, observability and messaging, all in a distributed architecture and with project documentation.
Starting point I chose to build a live streaming application since it allowed me to explore real-time communication and design clear modules even though time did not allow replicating all the complexities of a production streaming system.
Architecture I thought about the key functionalities, organized them into modules and aligned them with the challenge requirements. The architecture focused on a PostgreSQL database to centralize data and four main modules: auth for authentication, channels for channel CRUD, user for user CRUD and broadcast for stream communication.
To simulate real-time communication I used messaging with RabbitMQ instead of implementing a real video stream, a decision that fit the scope and time constraints of the challenge.
About the modules the modules were developed with Fastify whose syntax is very familiar to those who know Express. Messaging was solved with RabbitMQ and communication relied on HTTP and WebSocket protocols depending on the need of each interaction.
Data modeling in the database I defined the relationships between users and channels, between channels and streams and the link between streams and their logs. This structure allows tracking the status of each stream and maintaining a change history for auditing and observability.
Tools used among the tools and technologies used were Draw.io for diagrams, Fastify for APIs, RabbitMQ for messaging and PostgreSQL for persistence, along with basic observability and event traceability.
Lessons and next steps learning to prioritize functionalities, designing clear boundaries between services and choosing tools that allow rapid iteration was key. In future phases I plan to enrich real-time communication, strengthen security, add advanced metrics and scale the solution.
At Q2BSTUDIO we are a software development company that creates custom applications and custom software for companies looking for scalable and secure solutions. We are specialists in artificial intelligence, AI for businesses, AI agents and we offer cybersecurity services to protect applications and critical data.
We also offer AWS and Azure cloud services to deploy flexible and managed infrastructures, business intelligence services and solutions with Power BI to turn data into actionable decisions. Our approach combines custom application development with artificial intelligence and cybersecurity solutions to drive our clients' digital transformation.
If you are interested in delving deeper into the implementation of each module, orchestration between services or how to integrate AI agents and Power BI into enterprise solutions, at Q2BSTUDIO we can help you design and implement a custom solution tailored to your needs.
If you have questions, suggestions or want professional support to take this prototype to a production solution, contact Q2BSTUDIO and let's talk about how to apply distributed architectures, custom software, artificial intelligence, cybersecurity and AWS and Azure cloud services for your project.
