External access to Containers

Introduction¶

Researchers working with containers. many times need to remotely access the container. Some examples:

Using a Jupyter notebook that runs within the container
Using PyCharm to run python commands remotely.
Using TensorBoard to view machine learning visualizations

This requires exposing container ports. When using docker, the way Researchers expose ports is by declaring them when starting the container. Run:ai has similar syntax.

Run:ai is based on Kubernetes. Kubernetes offers an abstraction of the container's location. This complicates the exposure of ports. Kubernetes offers several options:

Method	Description	Prerequisites
Port Forwarding	Simple port forwarding allows access to the container via local and/or remote port.	None
NodePort	Exposes the service on each Node’s IP at a static port (the NodePort). You’ll be able to contact the NodePort service from outside the cluster by requesting `<NODE-IP>:<NODE-PORT>` regardless of which node the container actually resides in.	None
LoadBalancer	Exposes the service externally using a cloud provider’s load balancer.	Only available with cloud providers

See https://kubernetes.io/docs/concepts/services-networking/service for further details on these four options.

External access to Containers

Introduction¶

See Also¶