AlexIoannides/kubernetes-mlops
A tutorial for deploying SciKit Learn and Keras ML models as production RESTful API services on Kubernetes using Docker containers and Seldon Core.
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This repository demonstrates how to turn ML models into production-grade RESTful prediction APIs using Docker containerization and Kubernetes orchestration. It covers deploying ML models trained with SciKit Learn or Keras as microservices, configuring fault-tolerance, auto-scaling, and rolling updates in a cloud-agnostic manner. The tutorial includes Seldon Core configuration for model serving on Google Cloud Platform.
Frequently asked
- What is AlexIoannides/kubernetes-mlops?
- A tutorial for deploying SciKit Learn and Keras ML models as production RESTful API services on Kubernetes using Docker containers and Seldon Core.
- Is kubernetes-mlops open source?
- Yes — AlexIoannides/kubernetes-mlops is open source, released under the MIT license.
- What language is kubernetes-mlops written in?
- AlexIoannides/kubernetes-mlops is primarily written in Python.
- How popular is kubernetes-mlops?
- AlexIoannides/kubernetes-mlops has 415 stars on GitHub.
- Where can I find kubernetes-mlops?
- AlexIoannides/kubernetes-mlops is on GitHub at https://github.com/AlexIoannides/kubernetes-mlops.