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Quickstart: Launch Interactive Build Workloads with Connected Ports


This Quickstart is an extension of the Quickstart document: Start and Use Interactive Build Workloads

When starting a container with the Run:ai Command-Line Interface (CLI), it is sometimes needed to expose internal ports to the user. Examples are: accessing a Jupyter notebook, using the container from a development environment such as PyCharm.

Exposing a Container Port

There are three ways to expose ports in Kubernetes: Port Forwarding, NodePort, and LoadBalancer. The first two will always work. The other requires a special setup by your administrator. The four methods are explained here.

The document below provides an example based on Port Forwarding.

Port Forwarding, Step by Step Walkthrough


  • Login to the Projects area of the Run:ai user interface.
  • Add a Project named team-a.

Run Workload

  • At the command-line run:
runai config project team-a
runai submit nginx-test -i zembutsu/docker-sample-nginx --interactive \
  --service-type portforward --port 8080:80 
  • The Job is based on a sample NGINX webserver docker image zembutsu/docker-sample-nginx. Once accessed via a browser, the page shows the container name.
  • Note the interactive flag which means the Job will not have a start or end. It is the Researcher's responsibility to close the Job.
  • In this example, we have chosen the simplest scheme to expose ports which is port forwarding. We temporarily expose port 8080 to localhost as long as the runai submit command is not stopped
  • It is possible to forward traffic from multiple IP addresses by using the "--address" parameter. Check the CLI reference for further details.

The result will be:

The job 'nginx-test-0' has been submitted successfully
You can run `runai describe job nginx-test-0 -p team-a` to check the job status
Waiting for pod to start running...
INFO[0023] Job started
Open access point(s) to service from localhost:8080
Forwarding from -> 80
Forwarding from [::1]:8080 -> 80

Access the Webserver

Open the following in the browser at http://localhost:8080.

You should see a web page with the name of the container.

Stop Workload

Press Ctrl-C in the shell to stop port forwarding. Then delete the Job by running runai delete job nginx-test

See Also