Sunday, September 26, 2021

MLOps with TensorFlow and Kubernetes Powered by RabbitMQ and FastAPI

I show how to run TensorFlow model training and data processing containers in a single Pod in Kubernetes. Model training container runs as a main container and data processing as a sidecar. Running both containers in a single Pod, allow to share files in common storage. I'm using persistence volume to store TensorFlow model and stats data from the data processing container. This video shows a walk through the complete use case of data processing, model training and ML microservices communication.


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