Add notes from the video (PRs are welcome)
- same use case as in the session before: classifying images of clothes
- using tensorflow serving, written in C++, with focus on inference
- gRPC binary protocol
- deploying to kubernetes
- 1st component: gateway (download image, resize, turn into numpy array - computationally not expensive - can be done with CPU)
- 2nd component: model (matrix multiplications - computationally expensive - thus use GPU)
- scaling the two components independently: i.e. 5 gateways handing images to 1 model
- two components in two different docker container (lesson four)
- kubernetes main concepts (lesson five)
- running kubernetes on your local machine (lesson six)
- deploy the two services to kubernetes (lesson seven)
- move from local to cloud (lesson eight)
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