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Everyone I tell this to, thinks it’s cutting edge, but I see it as a stitched together mess. Regardless:
A micro-service based application that stages machine learning tasks, and is meant to be deployed on 4+ machines. Running with two message queues at its heart and several workers, each worker configured to run optimally for either heavy cpu or gpu tasks.
The technology stack includes rabbitmq, Redis, Postgres, tensorflow, torch and the services are written in nodejs, lua and python. All packaged as a Kubernetes application.
Worked on this for 9 months now. I was the only constant on the project, and the architecture design has been basically re-engineered by myself. Since the last guy underestimated the ask.
rant
machine learning
wk215
distributed systems