Thanks for this interesting point of view about Kubernetes. As far as I'm concerned I struggled a lot setting it up. So much that I eventually gave up...
I'm now using Docker Swarm instead and I'm very happy about it as it's both simple and powerful. I decided to switch when I read this article: https://juliensalinas.com/en/container-orchestration-docker-swarm-nlpcloud/
The author explains how he is successfully using Docker Swarm behind nlpcloud.io . It's interesting because many people tend to think that Docker Swarm is for small websites and Kubernetes is for big ones. But it seems it's definitely not the case...
Thanks again for this good article though!
Interesting article thanks, especially as these 2 terms seem to be the new buzzwords today but few people might really know what they mean.
Now that machine learning (and especially NLP) is democratizing (many open source frameworks like spaCy, NLTK, etc. are really helping), it's still hard to really test and deploy the models to production. The following recent services really help from an MLOps perspective:
- https://dvc.org/ : a sort of CI for your ML projects
- https://nlpcloud.io : a way to easily deploy NLP models to production
- https://cloud.google.com/automl : Google's AutoML feature
Thanks again for this nice article.