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Contributing

Welcome dear open source colleague! As this is a Jupyter project please start by looking at the Jupyter contributor guide, and follow Project Jupyter's Code of Conduct to help us sustain a warm and welcoming collaborative environment.

If you don't have git already, install it and clone this repository.

git clone https://github.com/jupyterhub/zero-to-jupyterhub-k8s

Setting up for documentation development

See doc/README.md.

Setting up for Helm chart development

1: Prerequisites

This needs to be installed:

You can check if you have it all like this:

docker --version
kubectl version --client
helm version
pytest --version
chartpress --version

2: Setup a Kubernetes cluster

We need a Kubernetes cluster to work against. If you are using Linux you can either install k3s or k3d. For all other operating systems install k3d.

Linux only: Kubernetes setup with k3s

With k3s we can quickly create a Kubernetes cluster, and we don't have to transfer docker images built on our computer to make them available in the Kubernetes cluster.

Install

# Installs a ~50 MB k3s binary, setups and starts a systemctl service called
# k3s which is also enabled to run on startup, provides a k3s-uninstall.sh
# script, disables not needed functionality. You will be asked for sudo rights.
curl -sfL https://get.k3s.io | sh -s - \
    --write-kubeconfig-mode=644 \
    --disable metrics-server \
    --disable traefik \
    --disable local-storage \
    --disable-network-policy \
    --docker

# Ensure kubectl will work with our k3s cluster
export KUBECONFIG=/etc/rancher/k3s/k3s.yaml

Start/Stop and Enable/Disable

With systemctl you can start and stop the service named k3s representing the cluster, as well as enable and disable the service's automatic startup with your computer.

At the moment, there is a workaround making us need to run docker stop due to this issue to fully stop.

sudo systemctl stop k3s
docker stop $(docker container list --quiet --filter "name=k8s_")

Debug

# what is the status of the k3s service?
sudo systemctl status k3s

# what logs have the k3s service generated recently?
journalctl -u k3s --since "1 hour ago"

# what containers are running?
docker container list --filter "name=k8s_"

Uninstall

When k3s was installed with the installation script, an uninstallation script is made available as well.

At the moment, there is a workaround needed while uninstalling.

k3s-uninstall.sh
# ... and a temporary workaround of https://github.com/rancher/k3s/issues/1469
docker stop $(docker container list --all --quiet --filter "name=k8s_") | xargs docker rm

Linux, Mac, and possibly Windows: Kubernetes setup with k3d

k3d encapsulates k3s in containers. It is less mature than k3s and will require locally built docker images to be pushed to a dedicated registry before they can be accessed by the pods in the Kubernetes cluster, until this issue is resolved.

For this setup to work, make registry.local point to 127.0.0.1 (localhost) by adding an entry in /etc/hosts or its equivalent in Windows.

Install

k3d create --publish 30443:30443 --publish 32444:32444 --wait 60 \
   --enable-registry --registry-name local.jovyan.org \
   --server-arg --no-deploy=metrics-server \
   --server-arg --no-deploy=traefik \
   --server-arg --no-deploy=local-storage \
   --server-arg --disable-network-policy \
   --server-arg --flannel-backend=none

# For Linux/Mac:
export KUBECONFIG="$(k3d get-kubeconfig --name='k3s-default')"
. ci/common    # provides the setup_calico function
setup_calico

# For Windows:
# These instructions aren't maintained, you need to figure it out yourself =/

About the published ports

  • 30443: This port exposes the proxy-public service. It will route to the autohttps pod for TLS termination, then onwards to the proxy pod that routes to the hub pod or individual user pods depending on paths (/hub vs /user) and how JupyterHub dynamically has configured it.
  • 32444: This port exposes the pebble service which which accepts two ports, and this specific port will route to the pebble pod's management API where we can access paths like /roots/0. For more details about Pebble which we use as a local ACME server, see the section below and https://github.com/jupyterhub/pebble-helm-chart.

Stop

k3d delete

3: Install a local ACME server

Testing automatic TLS certificate acquisition with an ACME server like Let's Encrypt from a local Kubernetes cluster is tricky. First you need a public domain name registered and pointing to some public IP, and you need traffic to that IP end up inside your Kubernetes cluster. In our Travis CI setup we must install a local ACME server instead, and that is also recommended for local development.

Pebble is a an ACME server like Let's Encrypt solely meant for testing purposes. For more information, see jupyterhub/pebble-helm-chart.

Install Pebble

helm repo add jupyterhub https://jupyterhub.github.io/helm-chart/
helm repo update
helm install pebble jupyterhub/pebble --values dev-config-pebble.yaml

4: Build images, update values, install chart

This repository contains various Dockerfiles that are used to build docker images required by the Helm chart. To help us build these docker images only when needed, and to update the Helm chart's values.yaml file to use the most recent image, we rely on a command line tool called chartpress that is installed as part of dev-requirements.txt.

Chartpress is configured through chartpress.yaml, and will only rebuild images if their dependent files in their respective directories or chartpress.yaml itself has changed.

  1. Ensure the latest git tags are available locally, as chartpress uses them.

    git fetch origin --tags

  2. Use chartpress to rebuild images that need to be rebuilt and update the chart's values.yaml file with the appropriate image tags.

    # run this if you are using k3s, or generally when your Kubernetes cluster
# can make direct use of your locally built images
chartpress

# run this if you are using k3d
chartpress --image-prefix=local.jovyan.org:5000/ --push

  3. Use helm to upgrade (or install) your local JupyterHub Helm chart.

    helm upgrade --install jupyterhub ./jupyterhub --cleanup-on-fail --values dev-config.yaml

    Note that --cleanup-on-fail is a very good practice to avoid <resource name> already exist errors in future upgrades following a failed upgrade.

5: Visit the JupyterHub

After all your pods are running and the autohttps pod succesfully has acquired a certificate from the pebble pod acting as an ACME server, you should be able to access https://local.jovyan.org:30443. Your browser will probably require you to accept the TLS certificate as its signed an untrusted certificate authority.

Note that local.jovyan.org and its subdomains are Project Jupyter managed domains pointing to the localhost IP of 127.0.0.1, we use them to avoid needing to add entries to /etc/hosts.

6: Run tests

The test suite runs outside your Kubernetes cluster.

pytest -vx ./tests

Debugging

Various things can go wrong while working with the local development environment, here are some typical issues and what to do about them.

Basic debugging strategy in Kubernetes

A good debugging strategy is to start with the following steps.

  1. Inspect the status of pods with kubectl get pods.
  2. Inspect events and status of some pod with kubectl describe pod <name>.
  3. Inspect a pod's container's logs with kubectl logs .... Sometimes you need to specify -c <container name> or --all-containers. And sometimes you may want to specify the --previous flag to see the logs from the previous container run.

HTTPS errors

Your browser is expected to complain about the TLS certificate when visiting https://local.jovyan.org:30443 as its signed by an untrusted certificate authority and shouldn't be trusted unless it is solely for testing purposes.

But if for example Chrome presents ERR_SSL_PROTOCOL_ERROR or Firefox presents SSL_ERROR_INTERNARROR_ALERT, then the autohttps pod has probably failed to acquire a TLS certificate from the ACME server.

# the certificate should be available here
kubectl exec -it deploy/autohttps -c traefik -- cat /etc/acme/acme.json

# these logs should contain "Register..."
kubectl logs deploy/autohttps -c traefik

# these logs should contain "Issued certificate"
kubectl logs deploy/pebble -c pebble

If the ACME client library used by Traefik in the autohttps pod attempted to acquire the certificate from our ACME server (Pebble) before the Kubernetes cluster's DNS server or Pebble and it's DNS server had started fully, it would fail to acquire a certificate. For this situation, a restart of the autohttps pod by kubectl delete pod -l component=autohttps will hopefully resolve the issue. To avoid this in our CI system, we run the await_dns and await_pebble scripts in ci/common before we install the JupyterHub Helm chart which will startup the autohttps pod.

Hub restarts

Have you seen the hub pod get a restart count > 0? JupyterHub 1.1.0 is typically crashing after 20 seconds if it started up without the configurable proxy pod available. This harmless error can be confirmed by doing a kubectl logs deploy/hub --previous if you spot a message about a timeout after ~20 seconds in the logs.

Network errors

Did you get an error like one of these below?

# while running apt-get install while building a docker image with chartpress
E: Failed to fetch http://archive.ubuntu.com/ubuntu/pool/main/r/rtmpdump/librtmp1_2.4+20151223.gitfa8646d.1-1_amd64.deb  Could not connect to archive.ubuntu.com:80 (91.189.88.174). - connect (113: No route to host) Could not connect to archive.ubuntu.com:80 (91.189.88.31). - connect (113: No route to host) [IP: 91.189.88.174 80]
# [...]
subprocess.CalledProcessError: Command '['docker', 'build', '-t', 'jupyterhub/k8s-hub:0.9-217f798', 'images/hub', '--build-arg', 'JUPYTERHUB_VERSION=git+https://github.com/jupyterhub/jupyterhub@master']' returned non-zero exit status 100.

# while installing a dependency for our k8s cluster
Unable to connect to the server: dial tcp: lookup docs.projectcalico.org on 127.0.0.53:53: read udp 127.0.0.1:56409->127.0.0.53:53: i/o timeout

Network and DNS issues are typically symptoms of unreliable internet. You can recognize such issues if you get errors like the ones above.

As you may notice, typical keywords associated with network errors are:

  • resolve host
  • name resolution
  • timeout
  • no route to host