The sample includes a sshserver (05) that exposes a persistent volume (01 and 02). The variables with the access keys are included in a secret K8s object (04) and the service address of the server is registered in a config map (03). The application has different posibilities:
- A Jupyter notebook as a deployment (06) which mounts the the sshfolder and a deployment with a cluster of workers which also mount the filesystem (07). The integrated version is
integrated.yaml
. - A Jupyter notebook as a front-end of a distributed Tensorflow with a parameter server statefulset (08) and a statefulset of worker nodes (09). The configuration of both statefulsets is defined in a ConfigMap (
distribtf_config.yaml
). The integrated version is inintegrated_gpu_tf3.yaml
- An MPI cluster that can be run from the Jupyter Notebook. In this case, the hostfile is defined through a configMap. The integrated version is in
integratedgpumpi.yaml
.