When I initially started this project, I wanted to dig deeper in the audio manipulation of sounds. Then I wanted to add a scalable infrastructure layer using Kubernetes and a distributed filesystem.
This project is a kind of training for deploying a complex kubernetes application with several microservices powered by several languages like Go, C (coming soon for the rapgenration service), Python and Reactjs for the frontend services.
For now, the src/rapgeneratorservice/lib which is the core of the application is a bit simple and the results are very far from being audible. However, I'm improving this core library over the time to create a better user experience.
To learn more about the architecture of rapGO.io, please refer to the docs section.
The demo (available here) ha been tested with the test/alpha version on docker-compose. This is very far from being perfect (especially the core algorithm), but the global infrastructure is working.
For the ingestion engine, wa can have a idea of what it will look like on this video. I'm still working on it and also on the ingestion service backend.
The docker images used for this project are :
rapgoio/frontend:alpharapgoio/bucketserv:alpharapgoio/convertserv:alpharapgoio/heartbeatserv:alpharapgoio/rapserv:alpha
For the ingestion engine, the available images are :
rapgoio/ingest-frontend:alpha