Optimized Jupyter Notebooks on AWS

Kubeflow Notebook Images

Currently, we add AWS optimized Kubeflow Notebook Images and make them default options in notebook server.

527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-1.15.2-notebook-cpu:1.1.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-1.15.2-notebook-gpu:1.1.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-2.1.0-notebook-cpu:1.1.0
527798164940.dkr.ecr.us-west-2.amazonaws.com/tensorflow-2.1.0-notebook-gpu:1.1.0

The ECR image provides:

AWS Deep Learning Containers as base image

The reason we take AWS Deep Learning Containers as base image, is that AWS Deep Learning Containers provides optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries on AWS.

Extra pre-installed packages

• docker-client
• kubeflow-metadata
• kfp
• kfserving

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