MLOps using GCP

One disadvantage of using Google is that it has fewer certified practitioners. Another disadvantage is that Google is part of surveillance capitalism, in which users’ information is used to predict and to try shape their behaviour. Not only ethics plays a part in decision-making, technology regulation in this regard could also impact their market share. And Google has a reputation for a poor user and customer experience and frequently abandons products.

Pros? Research and development of mind-numbingly complex solutions that work at “planet-scale” is something Google does well. Three of Google’s most successful open source projects show this cultural strength: Kubernetes, the Go language, and the deep learning framework TensorFlow.

The number one advantage of using the Google Cloud may be that its technology is ideal for a multicloud strategy: Exploring GCP for use in MLOps.

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