Configuration Reference

The JupyterHub Helm chart is configurable by values in your config.yaml. In this way, you can extend user resources, build off of different Docker images, manage security and authentication, and more.

Below is a description of many but not all of the configurable values for the Helm chart. To see all configurable options, inspect their default values defined here.

For more guided information about some specific things you can do with modifications to the helm chart, see the Customization Guide.

imagePullSecret

This is configuration to create a k8s Secret resource of type: kubernetes.io/dockerconfigjson, with credentials to pull images from a private image registry. If you opt to do so, it will be available for use by all pods in their respective spec.imagePullSecrets alongside other k8s Secrets defined in imagePullSecrets or the pod respective ...image.pullSecrets configuration.

In other words, using this configuration option can automate both the otherwise manual creation of a k8s Secret and the otherwise manual configuration to reference this k8s Secret in all the pods of the Helm chart.

# you won't need to create a k8s Secret manually...
kubectl create secret docker-registry image-pull-secret \
  --docker-server=<REGISTRY> \
  --docker-username=<USERNAME> \
  --docker-email=<EMAIL> \
  --docker-password=<PASSWORD>

If you just want to let all Pods reference an existing secret, use the imagePullSecrets configuration instead.

To learn the username and password fields to access a gcr.io registry from a Kubernetes cluster not associated with the same google cloud credentials, look into this guide and read the notes about the password.

imagePullSecret.create

Toggle the creation of the k8s Secret with provided credentials to access a private image registry.

imagePullSecret.automaticReferenceInjection

Toggle the automatic reference injection of the created Secret to all pods’ spec.imagePullSecrets configuration.

imagePullSecret.registry

Name of the private registry you want to create a credential set for. It will default to Docker Hub’s image registry.

Examples:

  • https://index.docker.io/v1/

  • quay.io

  • eu.gcr.io

  • alexmorreale.privatereg.net

imagePullSecret.username

Name of the user you want to use to connect to your private registry.

For external gcr.io, you will use the _json_key.

Examples:

  • alexmorreale

  • alex@pfc.com

  • _json_key

imagePullSecret.password

Password for the private image registry’s user.

Examples:

  • plaintextpassword

  • abc123SECRETzyx098

For gcr.io registries the password will be a big JSON blob for a Google cloud service account, it should look something like below.

password: |-
  {
    "type": "service_account",
    "project_id": "jupyter-se",
    "private_key_id": "f2ba09118a8d3123b3321bd9a7d6d0d9dc6fdb85",
    ...
  }

Learn more in this guide.

imagePullSecrets

Chart wide configuration to append k8s Secret references to all its pod’s spec.imagePullSecrets configuration.

This will not override or get overridden by pod specific configuration, but instead augment the pod specific configuration.

You can use both the k8s native syntax, where each list element is like {"name": "my-secret-name"}, or you can let list elements be strings naming the secrets directly.

hub

hub.command

A list of strings to be used to replace the JupyterHub image’s ENTRYPOINT entry. Note that in k8s lingo, the Dockerfile’s ENTRYPOINT is called command. The list of strings will be expanded with Helm’s template function tpl which can render Helm template logic inside curly braces ({{... }}).

This could be useful to wrap the invocation of JupyterHub itself in some custom way.

For more details, see the Kubernetes documentation.

hub.args

A list of strings to be used to replace the JupyterHub image’s CMD entry as well as the Helm chart’s default way to start JupyterHub. Note that in k8s lingo, the Dockerfile’s CMD is called args. The list of strings will be expanded with Helm’s template function tpl which can render Helm template logic inside curly braces ({{... }}).

Warning

By replacing the entire configuration file, which is mounted to /etc/jupyterhub/jupyterhub_config.py by the Helm chart, instead of appending to it with hub.extraConfig, you expose your deployment for issues stemming from getting out of sync with the Helm chart’s config file.

These kind of issues will be significantly harder to debug and diagnose, and can due to this could cause a lot of time expenditure for both the community maintaining the Helm chart as well as yourself, even if this wasn’t the reason for the issue.

Due to this, we ask that you do your _absolute best to avoid replacing the default provided jupyterhub_config.py file. It can often be possible. For example, if your goal is to have a dedicated .py file for more extensive additions that you can syntax highlight and such and feel limited by passing code in hub.extraConfig which is part of a YAML file, you can use this trick instead.

hub:
  args:
    - "jupyterhub"
    - "--config"
    - "/etc/jupyterhub/jupyterhub_config.py"
    - "--debug"
    - "--upgrade-db"

For more details, see the Kubernetes documentation.

hub.cookieSecret

A 32-byte cryptographically secure randomly generated string used to sign values of secure cookies set by the hub. If unset, jupyterhub will generate one on startup and save it in the file jupyterhub_cookie_secret in the /srv/jupyterhub directory of the hub container. A value set here will make JupyterHub overwrite any previous file.

You do not need to set this at all if you are using the default configuration for storing databases - sqlite on a persistent volume (with hub.db.type set to the default sqlite-pvc). If you are using an external database, then you must set this value explicitly - or your users will keep getting logged out each time the hub pod restarts.

Changing this value will all user logins to be invalidated. If this secret leaks, immediately change it to something else, or user data can be compromised

# to generate a value, run
openssl rand -hex 32

hub.image

Set custom image name, tag, pullPolicy, or pullSecrets for the pod.

hub.image.name

The name of the image, without the tag.

# example name
gcr.io/my-project/my-image

hub.image.tag

The tag of the image to pull. This is the value following : in complete image specifications.

# example tags
v1.11.1
zhy270a

hub.image.pullPolicy

Configures the Pod’s spec.imagePullPolicy.

See the Kubernetes docs for more info.

hub.image.pullSecrets

A list of references to existing Kubernetes Secrets with credentials to pull the image.

This Pod’s final imagePullSecrets k8s specification will be a combination of:

  1. This list of k8s Secrets, specific for this pod.

  2. The list of k8s Secrets, for use by all pods in the Helm chart, declared in this Helm charts configuration called imagePullSecrets.

  3. A k8s Secret, for use by all pods in the Helm chart, if conditionally created from image registry credentials provided under imagePullSecret if imagePullSecret.create is set to true.

# example - k8s native syntax
pullSecrets:
  - name: my-k8s-secret-with-image-registry-credentials

# example - simplified syntax
pullSecrets:
  - my-k8s-secret-with-image-registry-credentials

hub.networkPolicy

This configuration regards the creation and configuration of a k8s NetworkPolicy resource.

hub.networkPolicy.enabled

Toggle the creation of the NetworkPolicy resource for this pod.

hub.networkPolicy.ingress

Additional ingress rules to add except those that is known to be needed by the respective pods in the Helm chart.

hub.networkPolicy.egress

Additional egress rules to add except those that is known to be needed by the respective pods in the Helm chart.

The default value of this egress is to allow all traffic, except for the singleuser.networkPolicy.egress, which is also limiting access to a metadata server that can be exploited.

If you want to restrict egress, you can override this permissive default to be an empty list.

hub.networkPolicy.interNamespaceAccessLabels

This configuration option determines if both namespaces and pods in other namespaces, that have specific access labels, should be accepted to allow ingress (set to accept), or, if the labels are to be ignored when applied outside the local namespace (set to ignore).

The available access labels for respective NetworkPolicy resources are:

  • hub.jupyter.org/network-access-hub: "true" (hub)

  • hub.jupyter.org/network-access-proxy-http: "true" (proxy.chp, proxy.traefik)

  • hub.jupyter.org/network-access-proxy-api: "true" (proxy.chp)

  • hub.jupyter.org/network-access-singleuser: "true" (singleuser)

hub.networkPolicy.allowedIngressPorts

A rule to allow ingress on these ports will be added no matter what the origin of the request is. The default setting for proxy.chp and proxy.traefik’s networkPolicy configuration is [http, https], while it is [] for other networkPolicies.

Note that these port names or numbers target a Pod’s port name or number, not a k8s Service’s port name or number.

hub.db

hub.db.type

Type of database backend to use for the hub database.

The Hub requires a persistent database to function, and this lets you specify where it should be stored.

The various options are:

  1. sqlite-pvc

    Use an sqlite database kept on a persistent volume attached to the hub.

    By default, this disk is created by the cloud provider using dynamic provisioning configured by a storage class. You can customize how this disk is created / attached by setting various properties under hub.db.pvc.

    This is the default setting, and should work well for most cloud provider deployments.

  2. sqlite-memory

    Use an in-memory sqlite database. This should only be used for testing, since the database is erased whenever the hub pod restarts - causing the hub to lose all memory of users who had logged in before.

    When using this for testing, make sure you delete all other objects that the hub has created (such as user pods, user PVCs, etc) every time the hub restarts. Otherwise you might run into errors about duplicate resources.

  3. mysql

    Use an externally hosted mysql database.

    You have to specify an sqlalchemy connection string for the mysql database you want to connect to in hub.db.url if using this option.

    The general format of the connection string is:

    mysql+pymysql://<db-username>:<db-password>@<db-hostname>:<db-port>/<db-name>
    

    The user specified in the connection string must have the rights to create tables in the database specified.

    Note that if you use this, you must also set hub.cookieSecret.

  4. postgres

    Use an externally hosted postgres database.

    You have to specify an sqlalchemy connection string for the postgres database you want to connect to in hub.db.url if using this option.

    The general format of the connection string is:

    postgres+psycopg2://<db-username>:<db-password>@<db-hostname>:<db-port>/<db-name>
    

    The user specified in the connection string must have the rights to create tables in the database specified.

    Note that if you use this, you must also set hub.cookieSecret.

hub.db.pvc

Customize the Persistent Volume Claim used when hub.db.type is sqlite-pvc.

hub.db.pvc.annotations

Annotations to apply to the PVC containing the sqlite database.

See the Kubernetes documentation for more details about annotations.

hub.db.pvc.selector

Label selectors to set for the PVC containing the sqlite database.

Useful when you are using a specific PV, and want to bind to that and only that.

See the Kubernetes documentation for more details about using a label selector for what PV to bind to.

hub.db.pvc.storage

Size of disk to request for the database disk.

hub.db.url

Connection string when hub.db.type is mysql or postgres.

See documentation for hub.db.type for more details on the format of this property.

hub.db.password

Password for the database when hub.db.type is mysql or postgres.

hub.labels

Extra labels to add to the hub pod.

See the Kubernetes docs to learn more about labels.

hub.initContainers

list of initContainers to be run with hub pod. See Kubernetes Docs

hub:
  initContainers:
    - name: init-myservice
      image: busybox:1.28
      command: ['sh', '-c', 'command1']
    - name: init-mydb
      image: busybox:1.28
      command: ['sh', '-c', 'command2']

hub.extraEnv

Extra environment variables that should be set for the hub pod.

Environment variables are usually used to:

  • Pass parameters to some custom code in hub.extraConfig.

  • Configure code running in the hub pod, such as an authenticator or spawner.

String literals with $(ENV_VAR_NAME) will be expanded by Kubelet which is a part of Kubernetes.

hub:
  extraEnv:
    # basic notation (for literal values only)
    MY_ENV_VARS_NAME1: "my env var value 1"

    # explicit notation (the "name" field takes precedence)
    HUB_NAMESPACE:
      name: HUB_NAMESPACE
      valueFrom:
        fieldRef:
          fieldPath: metadata.namespace

    # implicit notation (the "name" field is implied)
    PREFIXED_HUB_NAMESPACE:
      value: "my-prefix-$(HUB_NAMESPACE)"
    SECRET_VALUE:
      valueFrom:
        secretKeyRef:
          name: my-k8s-secret
          key: password

For more information, see the Kubernetes EnvVar specification.

hub.extraConfig

Arbitrary extra python based configuration that should be in jupyterhub_config.py.

This is the escape hatch - if you want to configure JupyterHub to do something specific that is not present here as an option, you can write the raw Python to do it here.

extraConfig is a dict, so there can be multiple configuration snippets under different names. The configuration sections are run in alphabetical order.

Non-exhaustive examples of things you can do here:

  • Subclass authenticator / spawner to do a custom thing

  • Dynamically launch different images for different sets of images

  • Inject an auth token from GitHub authenticator into user pod

  • Anything else you can think of!

Since this is usually a multi-line string, you want to format it using YAML’s | operator.

For example:

hub:
  extraConfig:
    myConfig.py: |
      c.JupyterHub.something = 'something'
      c.Spawner.somethingelse = 'something else'

No validation of this python is performed! If you make a mistake here, it will probably manifest as either the hub pod going into Error or CrashLoopBackoff states, or in some special cases, the hub running but… just doing very random things. Be careful!

hub.uid

The UID the hub process should be running as. Use this only if you are building your own image & know that a user with this uid exists inside the hub container! Advanced feature, handle with care! Defaults to 1000, which is the uid of the jovyan user that is present in the default hub image.

hub.fsGid

The gid the hub process should be using when touching any volumes mounted. Use this only if you are building your own image & know that a group with this gid exists inside the hub container! Advanced feature, handle with care! Defaults to 1000, which is the gid of the jovyan user that is present in the default hub image.

hub.service

Object to configure the service the JupyterHub will be exposed on by the Kubernetes server.

hub.service.type

The Kubernetes ServiceType to be used.

The default type is ClusterIP. See the Kubernetes docs to learn more about service types.

hub.service.ports

Object to configure the ports the hub service will be deployed on.

hub.service.ports.nodePort

The nodePort to deploy the hub service on.

hub.service.annotations

Kubernetes annotations to apply to the hub service.

hub.pdb

Set the Pod Disruption Budget for the hub pod.

See the Kubernetes documentation for more details about disruptions.

hub.pdb.enabled

Whether PodDisruptionBudget is enabled for the hub pod.

hub.pdb.minAvailable

Minimum number of pods to be available during the voluntary disruptions.

hub.existingSecret

Name of the existing secret in the kubernetes cluster, typically the hub-secret.

This secret should represent the structure as otherwise generated by this chart:

apiVersion: v1
data:
  proxy.token: < FILL IN >
  values.yaml: < FILL IN >
kind: Secret
metadata:
  name: hub-secret

NOTE: if you choose to manage the secret yourself, you are in charge of ensuring the secret having the proper contents.

hub.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

hub.tolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

proxy

proxy.chp

Configure the configurable-http-proxy (chp) pod managed by jupyterhub to route traffic both to itself and to user pods.

proxy.chp.networkPolicy

This configuration regards the creation and configuration of a k8s NetworkPolicy resource.

proxy.chp.networkPolicy.enabled

Toggle the creation of the NetworkPolicy resource for this pod.

proxy.chp.networkPolicy.ingress

Additional ingress rules to add except those that is known to be needed by the respective pods in the Helm chart.

proxy.chp.networkPolicy.egress

Additional egress rules to add except those that is known to be needed by the respective pods in the Helm chart.

The default value of this egress is to allow all traffic, except for the singleuser.networkPolicy.egress, which is also limiting access to a metadata server that can be exploited.

If you want to restrict egress, you can override this permissive default to be an empty list.

proxy.chp.networkPolicy.interNamespaceAccessLabels

This configuration option determines if both namespaces and pods in other namespaces, that have specific access labels, should be accepted to allow ingress (set to accept), or, if the labels are to be ignored when applied outside the local namespace (set to ignore).

The available access labels for respective NetworkPolicy resources are:

  • hub.jupyter.org/network-access-hub: "true" (hub)

  • hub.jupyter.org/network-access-proxy-http: "true" (proxy.chp, proxy.traefik)

  • hub.jupyter.org/network-access-proxy-api: "true" (proxy.chp)

  • hub.jupyter.org/network-access-singleuser: "true" (singleuser)

proxy.chp.networkPolicy.allowedIngressPorts

A rule to allow ingress on these ports will be added no matter what the origin of the request is. The default setting for proxy.chp and proxy.traefik’s networkPolicy configuration is [http, https], while it is [] for other networkPolicies.

Note that these port names or numbers target a Pod’s port name or number, not a k8s Service’s port name or number.

proxy.chp.extraCommandLineFlags

A list of strings to be added as command line options when starting configurable-http-proxy that will be expanded with Helm’s template function tpl which can render Helm template logic inside curly braces ({{ ... }}).

proxy:
  chp:
    extraCommandLineFlags:
      - "--auto-rewrite"
      - "--custom-header {{ .Values.myCustomStuff }}"

Note that these will be appended last, and if you provide the same flag twice, the last flag will be used, which mean you can override the default flag values as well.

proxy.chp.extraEnv

Extra environment variables that should be set for the chp pod.

Environment variables are usually used here to:

  • override HUB_SERVICE_PORT or HUB_SERVICE_HOST default values

  • set CONFIGPROXY_SSL_KEY_PASSPHRASE for setting passphrase of SSL keys

String literals with $(ENV_VAR_NAME) will be expanded by Kubelet which is a part of Kubernetes.

proxy:
  chp:
    extraEnv:
      # basic notation (for literal values only)
      MY_ENV_VARS_NAME1: "my env var value 1"

      # explicit notation (the "name" field takes precedence)
      CHP_NAMESPACE:
        name: CHP_NAMESPACE
        valueFrom:
          fieldRef:
            fieldPath: metadata.namespace

      # implicit notation (the "name" field is implied)
      PREFIXED_CHP_NAMESPACE:
        value: "my-prefix-$(CHP_NAMESPACE)"
      SECRET_VALUE:
        valueFrom:
          secretKeyRef:
            name: my-k8s-secret
            key: password

For more information, see the Kubernetes EnvVar specification.

proxy.chp.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

proxy.chp.tolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

proxy.secretToken

A 32-byte cryptographically secure randomly generated string used to secure communications between the hub and the configurable-http-proxy.

# to generate a value, run
openssl rand -hex 32

Changing this value will cause the proxy and hub pods to restart. It is good security practice to rotate these values over time. If this secret leaks, immediately change it to something else, or user data can be compromised

proxy.service

Configuration of the k8s Service proxy-public which either will point to the autohttps pod running Traefik for TLS termination, or the proxy pod running ConfigurableHTTPProxy. Incoming traffic from users on the internet should always go through this k8s Service.

When this service targets the autohttps pod which then routes to the proxy pod, a k8s Service named proxy-http will be added targeting the proxy pod and only accepting HTTP traffic on port 80.

proxy.service.type

Default LoadBalancer. See hub.service.type for supported values.

proxy.service.labels

Extra labels to add to the proxy service.

See the Kubernetes docs to learn more about labels.

proxy.service.annotations

Annotations to apply to the service that is exposing the proxy.

See the Kubernetes documentation for more details about annotations.

proxy.service.nodePorts

Object to set NodePorts to expose the service on for http and https.

See the Kubernetes documentation for more details about NodePorts.

proxy.service.nodePorts.http

The HTTP port the proxy-public service should be exposed on.

proxy.service.nodePorts.https

The HTTPS port the proxy-public service should be exposed on.

proxy.service.extraPorts

Extra ports the k8s Service should accept incoming traffic on, which will be redirected to either the autohttps pod (treafik) or the proxy pod (chp).

See the Kubernetes documentation for the structure of the items in this list.

proxy.service.loadBalancerIP

The public IP address the proxy-public Kubernetes service should be exposed on. This entry will end up at the configurable proxy server that JupyterHub manages, which will direct traffic to user pods at the /user path and the hub pod at the /hub path.

Set this if you want to use a fixed external IP address instead of a dynamically acquired one. This is relevant if you have a domain name that you want to point to a specific IP and want to ensure it doesn’t change.

proxy.service.loadBalancerSourceRanges

A list of IP CIDR ranges that are allowed to access the load balancer service. Defaults to allowing everyone to access it.

proxy.https

Object for customizing the settings for HTTPS used by the JupyterHub’s proxy. For more information on configuring HTTPS for your JupyterHub, see the HTTPS section in our security guide

proxy.https.enabled

Indicator to set whether HTTPS should be enabled or not on the proxy. Defaults to true if the https object is provided.

proxy.https.type

The type of HTTPS encryption that is used. Decides on which ports and network policies are used for communication via HTTPS. Setting this to secret sets the type to manual HTTPS with a secret that has to be provided in the https.secret object. Defaults to letsencrypt.

proxy.https.letsencrypt

proxy.https.letsencrypt.contactEmail

The contact email to be used for automatically provisioned HTTPS certificates by Let’s Encrypt. For more information see Set up automatic HTTPS. Required for automatic HTTPS.

proxy.https.manual

Object for providing own certificates for manual HTTPS configuration. To be provided when setting https.type to manual. See Set up manual HTTPS

proxy.https.manual.key

The RSA private key to be used for HTTPS. To be provided in the form of

key: |
  -----BEGIN RSA PRIVATE KEY-----
  ...
  -----END RSA PRIVATE KEY-----
proxy.https.manual.cert

The certificate to be used for HTTPS. To be provided in the form of

cert: |
  -----BEGIN CERTIFICATE-----
  ...
  -----END CERTIFICATE-----

proxy.https.secret

Secret to be provided when setting https.type to secret.

proxy.https.secret.name

Name of the secret

proxy.https.secret.key

Path to the private key to be used for HTTPS. Example: 'tls.key'

proxy.https.secret.crt

Path to the certificate to be used for HTTPS. Example: 'tls.crt'

proxy.https.hosts

You domain in list form. Required for automatic HTTPS. See Set up automatic HTTPS. To be provided like:

hosts:
  - <your-domain-name>

proxy.pdb

Set the Pod Disruption Budget for the proxy pod.

See the Kubernetes documentation for more details about disruptions.

proxy.pdb.enabled

Whether PodDisruptionBudget is enabled for the proxy pod.

proxy.pdb.minAvailable

Minimum number of pods to be available during the voluntary disruptions.

proxy.traefik

Configure the traefik proxy used to terminate TLS when ‘autohttps’ is enabled

proxy.traefik.labels

Extra labels to add to the traefik pod.

See the Kubernetes docs to learn more about labels.

proxy.traefik.networkPolicy

This configuration regards the creation and configuration of a k8s NetworkPolicy resource.

proxy.traefik.networkPolicy.enabled

Toggle the creation of the NetworkPolicy resource for this pod.

proxy.traefik.networkPolicy.ingress

Additional ingress rules to add except those that is known to be needed by the respective pods in the Helm chart.

proxy.traefik.networkPolicy.egress

Additional egress rules to add except those that is known to be needed by the respective pods in the Helm chart.

The default value of this egress is to allow all traffic, except for the singleuser.networkPolicy.egress, which is also limiting access to a metadata server that can be exploited.

If you want to restrict egress, you can override this permissive default to be an empty list.

proxy.traefik.networkPolicy.interNamespaceAccessLabels

This configuration option determines if both namespaces and pods in other namespaces, that have specific access labels, should be accepted to allow ingress (set to accept), or, if the labels are to be ignored when applied outside the local namespace (set to ignore).

The available access labels for respective NetworkPolicy resources are:

  • hub.jupyter.org/network-access-hub: "true" (hub)

  • hub.jupyter.org/network-access-proxy-http: "true" (proxy.chp, proxy.traefik)

  • hub.jupyter.org/network-access-proxy-api: "true" (proxy.chp)

  • hub.jupyter.org/network-access-singleuser: "true" (singleuser)

proxy.traefik.networkPolicy.allowedIngressPorts

A rule to allow ingress on these ports will be added no matter what the origin of the request is. The default setting for proxy.chp and proxy.traefik’s networkPolicy configuration is [http, https], while it is [] for other networkPolicies.

Note that these port names or numbers target a Pod’s port name or number, not a k8s Service’s port name or number.

proxy.traefik.extraEnv

Extra environment variables that should be set for the traefik pod.

Environment Variables here may be used to configure traefik.

String literals with $(ENV_VAR_NAME) will be expanded by Kubelet which is a part of Kubernetes.

proxy:
  traefik:
    extraEnv:
      # basic notation (for literal values only)
      MY_ENV_VARS_NAME1: "my env var value 1"

      # explicit notation (the "name" field takes precedence)
      TRAEFIK_NAMESPACE:
        name: TRAEFIK_NAMESPACE
        valueFrom:
          fieldRef:
            fieldPath: metadata.namespace

      # implicit notation (the "name" field is implied)
      PREFIXED_TRAEFIK_NAMESPACE:
        value: "my-prefix-$(TRAEFIK_NAMESPACE)"
      SECRET_VALUE:
        valueFrom:
          secretKeyRef:
            name: my-k8s-secret
            key: password

For more information, see the Kubernetes EnvVar specification.

proxy.traefik.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

proxy.traefik.tolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

auth

auth.state

auth.state.enabled

Enable persisting auth_state (if available). See: the documentation on authenticators

auth.state.cryptoKey

auth_state will be encrypted and stored in the Hub’s database. This can include things like authentication tokens, etc. to be passed to Spawners as environment variables. Encrypting auth_state requires the cryptography package. It must contain one (or more, separated by ;) 32-byte encryption keys. These can be either base64 or hex-encoded. The JUPYTERHUB_CRYPT_KEY environment variable for the hub pod is set using this entry.

# to generate a value, run
openssl rand -hex 32

If encryption is unavailable, auth_state cannot be persisted.

singleuser

Options for customizing the environment that is provided to the users after they log in.

singleuser.networkPolicy

This configuration regards the creation and configuration of a k8s NetworkPolicy resource.

singleuser.networkPolicy.enabled

Toggle the creation of the NetworkPolicy resource for this pod.

singleuser.networkPolicy.ingress

Additional ingress rules to add except those that is known to be needed by the respective pods in the Helm chart.

singleuser.networkPolicy.egress

Additional egress rules to add except those that is known to be needed by the respective pods in the Helm chart.

The default value of this egress is to allow all traffic, except for the singleuser.networkPolicy.egress, which is also limiting access to a metadata server that can be exploited.

If you want to restrict egress, you can override this permissive default to be an empty list.

singleuser.networkPolicy.interNamespaceAccessLabels

This configuration option determines if both namespaces and pods in other namespaces, that have specific access labels, should be accepted to allow ingress (set to accept), or, if the labels are to be ignored when applied outside the local namespace (set to ignore).

The available access labels for respective NetworkPolicy resources are:

  • hub.jupyter.org/network-access-hub: "true" (hub)

  • hub.jupyter.org/network-access-proxy-http: "true" (proxy.chp, proxy.traefik)

  • hub.jupyter.org/network-access-proxy-api: "true" (proxy.chp)

  • hub.jupyter.org/network-access-singleuser: "true" (singleuser)

singleuser.networkPolicy.allowedIngressPorts

A rule to allow ingress on these ports will be added no matter what the origin of the request is. The default setting for proxy.chp and proxy.traefik’s networkPolicy configuration is [http, https], while it is [] for other networkPolicies.

Note that these port names or numbers target a Pod’s port name or number, not a k8s Service’s port name or number.

singleuser.podNameTemplate

Template for the pod name of each user, such as jupyter-{username}{servername}.

singleuser.cpu

Set CPU limits & guarantees that are enforced for each user. See: https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/

singleuser.cpu.limit

singleuser.cpu.guarantee

singleuser.memory

Set Memory limits & guarantees that are enforced for each user.

See the Kubernetes docs for more info.

singleuser.memory.limit

singleuser.memory.guarantee

Note that this field is referred to as requests by the Kubernetes API.

singleuser.image

Set custom image name, tag, pullPolicy, or pullSecrets for the pod.

singleuser.image.name

The name of the image, without the tag.

# example name
gcr.io/my-project/my-image

singleuser.image.tag

The tag of the image to pull. This is the value following : in complete image specifications.

# example tags
v1.11.1
zhy270a

singleuser.image.pullPolicy

Configures the Pod’s spec.imagePullPolicy.

See the Kubernetes docs for more info.

singleuser.image.pullSecrets

A list of references to existing Kubernetes Secrets with credentials to pull the image.

This Pod’s final imagePullSecrets k8s specification will be a combination of:

  1. This list of k8s Secrets, specific for this pod.

  2. The list of k8s Secrets, for use by all pods in the Helm chart, declared in this Helm charts configuration called imagePullSecrets.

  3. A k8s Secret, for use by all pods in the Helm chart, if conditionally created from image registry credentials provided under imagePullSecret if imagePullSecret.create is set to true.

# example - k8s native syntax
pullSecrets:
  - name: my-k8s-secret-with-image-registry-credentials

# example - simplified syntax
pullSecrets:
  - my-k8s-secret-with-image-registry-credentials

singleuser.initContainers

list of initContainers to be run every singleuser pod. See Kubernetes Docs

singleuser:
  initContainers:
    - name: init-myservice
      image: busybox:1.28
      command: ['sh', '-c', 'command1']
    - name: init-mydb
      image: busybox:1.28
      command: ['sh', '-c', 'command2']

singleuser.profileList

For more information about the profile list, see KubeSpawner’s documentation as this is simply a passthrough to that configuration.

NOTE: The image-pullers are aware of the overrides of images in singleuser.profileList but they won’t be if you configure it in JupyterHub’s configuration of ‘c.KubeSpawner.profile_list.

singleuser:
  profileList:
    - display_name: "Default: Shared, 8 CPU cores"
      description: "Your code will run on a shared machine with CPU only."
      default: True
    - display_name: "Personal, 4 CPU cores & 26GB RAM, 1 NVIDIA Tesla K80 GPU"
      description: "Your code will run a personal machine with a GPU."
      kubespawner_override:
        extra_resource_limits:
          nvidia.com/gpu: "1"

singleuser.schedulerStrategy

Deprecated and no longer does anything. Use the user-scheduler instead in order to accomplish a good packing of the user pods.

singleuser.extraEnv

Extra environment variables that should be set for the user pods.

String literals with $(ENV_VAR_NAME) will be expanded by Kubelet which is a part of Kubernetes. Note that the user pods will already have access to a set of environment variables that you can use, like JUPYTERHUB_USER and JUPYTERHUB_HOST. For more information about these inspect this source code.

singleuser:
  extraEnv:
    # basic notation (for literal values only)
    MY_ENV_VARS_NAME1: "my env var value 1"

    # explicit notation (the "name" field takes precedence)
    USER_NAMESPACE:
      name: USER_NAMESPACE
      valueFrom:
        fieldRef:
          fieldPath: metadata.namespace

    # implicit notation (the "name" field is implied)
    PREFIXED_USER_NAMESPACE:
      value: "my-prefix-$(USER_NAMESPACE)"
    SECRET_VALUE:
      valueFrom:
        secretKeyRef:
          name: my-k8s-secret
          key: password

For more information, see the Kubernetes EnvVar specification.

singleuser.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

singleuser.extraTolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

singleuser.extraNodeAffinity

Affinities describe where pods prefer or require to be scheduled, they may prefer or require a node where they are to be scheduled to have a certain label (node affinity). They may also require to be scheduled in proximity or with a lack of proximity to another pod (pod affinity and anti pod affinity).

See the Kubernetes docs for more info.

singleuser.extraNodeAffinity.required

Pass this field an array of NodeSelectorTerm objects.

singleuser.extraNodeAffinity.preferred

Pass this field an array of PreferredSchedulingTerm objects.

singleuser.extraPodAffinity

See the description of singleuser.extraNodeAffinity.

singleuser.extraPodAffinity.required

Pass this field an array of PodAffinityTerm objects.

singleuser.extraPodAffinity.preferred

Pass this field an array of WeightedPodAffinityTerm objects.

singleuser.extraPodAntiAffinity

See the description of singleuser.extraNodeAffinity.

singleuser.extraPodAntiAffinity.required

Pass this field an array of PodAffinityTerm objects.

singleuser.extraPodAntiAffinity.preferred

Pass this field an array of WeightedPodAffinityTerm objects.

scheduling

Objects for customizing the scheduling of various pods on the nodes and related labels.

scheduling.userScheduler

The user scheduler is making sure that user pods are scheduled tight on nodes, this is useful for autoscaling of user node pools.

scheduling.userScheduler.enabled

Enables the user scheduler.

scheduling.userScheduler.replicas

You can have multiple schedulers to share the workload or improve availability on node failure.

scheduling.userScheduler.image

Set custom image name, tag, pullPolicy, or pullSecrets for the pod.

scheduling.userScheduler.image.name

The name of the image, without the tag.

# example name
gcr.io/my-project/my-image
scheduling.userScheduler.image.tag

The tag of the image to pull. This is the value following : in complete image specifications.

# example tags
v1.11.1
zhy270a
scheduling.userScheduler.image.pullPolicy

Configures the Pod’s spec.imagePullPolicy.

See the Kubernetes docs for more info.

scheduling.userScheduler.image.pullSecrets

A list of references to existing Kubernetes Secrets with credentials to pull the image.

This Pod’s final imagePullSecrets k8s specification will be a combination of:

  1. This list of k8s Secrets, specific for this pod.

  2. The list of k8s Secrets, for use by all pods in the Helm chart, declared in this Helm charts configuration called imagePullSecrets.

  3. A k8s Secret, for use by all pods in the Helm chart, if conditionally created from image registry credentials provided under imagePullSecret if imagePullSecret.create is set to true.

# example - k8s native syntax
pullSecrets:
  - name: my-k8s-secret-with-image-registry-credentials

# example - simplified syntax
pullSecrets:
  - my-k8s-secret-with-image-registry-credentials

scheduling.userScheduler.pdb

Set the Pod Disruption Budget for the user scheduler.

See the Kubernetes documentation for more details about disruptions.

scheduling.userScheduler.pdb.enabled

Whether PodDisruptionBudget is enabled for the user scheduler.

scheduling.userScheduler.pdb.minAvailable

Minimum number of pods to be available during the voluntary disruptions.

scheduling.userScheduler.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

scheduling.userScheduler.tolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

scheduling.podPriority

Pod Priority is used to allow real users evict placeholder pods that in turn triggers a scale up by a cluster autoscaler. So, enabling this option will only make sense if the following conditions are met:

  1. Your Kubernetes cluster has at least version 1.11

  2. A cluster autoscaler is installed

  3. user-placeholer pods is configured to get a priority equal or higher than the cluster autoscaler’s priority cutoff

  4. Normal user pods have a higher priority than the user-placeholder pods

Note that if the default priority cutoff if not configured on cluster autoscaler, it will currently default to 0, and that in the future this is meant to be lowered. If your cloud provider is installing the cluster autoscaler for you, they may also configure this specifically.

Recommended settings for a cluster autoscaler…

… with a priority cutoff of -10 (GKE):

podPriority:
  enabled: true
  globalDefault: false
  defaultPriority: 0
  userPlaceholderPriority: -10

… with a priority cutoff of 0:

podPriority:
  enabled: true
  globalDefault: true
  defaultPriority: 10
  userPlaceholderPriority: 0

scheduling.podPriority.enabled

scheduling.podPriority.globalDefault

Warning! This will influence all pods in the cluster.

The priority a pod usually get is 0. But this can be overridden with a PriorityClass resource if it is declared to be the global default. This configuration option allows for the creation of such global default.

scheduling.podPriority.defaultPriority

The actual value for the default pod priority.

scheduling.podPriority.userPlaceholderPriority

The actual value for the user-placeholder pods’ priority.

scheduling.userPlaceholder

User placeholders simulate users but will thanks to PodPriority be evicted by the cluster autoscaler if a real user shows up. In this way placeholders allow you to create a headroom for the real users and reduce the risk of a user having to wait for a node to be added. Be sure to use the the continuous image puller as well along with placeholders, so the images are also available when real users arrive.

To test your setup efficiently, you can adjust the amount of user placeholders with the following command:

# Configure to have 3 user placeholders
kubectl scale sts/user-placeholder --replicas=3

scheduling.userPlaceholder.enabled

scheduling.userPlaceholder.replicas

How many placeholder pods would you like to have?

scheduling.userPlaceholder.resources

Unless specified here, the placeholder pods will request the same resources specified for the real singleuser pods.

scheduling.corePods

These settings influence the core pods like the hub, proxy and user-scheduler pods.

scheduling.corePods.nodeAffinity

Where should pods be scheduled? Perhaps on nodes with a certain label is preferred or even required?

scheduling.corePods.nodeAffinity.matchNodePurpose

Decide if core pods ignore, prefer or require to schedule on nodes with this label:

hub.jupyter.org/node-purpose=core

scheduling.userPods

These settings influence the user pods like the user-placeholder, user-dummy and actual user pods named like jupyter-someusername.

scheduling.userPods.nodeAffinity

Where should pods be scheduled? Perhaps on nodes with a certain label is preferred or even required?

scheduling.userPods.nodeAffinity.matchNodePurpose

Decide if user pods ignore, prefer or require to schedule on nodes with this label:

hub.jupyter.org/node-purpose=user

ingress

ingress.enabled

Enable the creation of a Kubernetes Ingress to proxy-public service.

See Advanced Topics — Zero to JupyterHub with Kubernetes 0.7.0 documentation for more details.

ingress.annotations

Annotations to apply to the Ingress.

See the Kubernetes documentation for more details about annotations.

ingress.hosts

List of hosts to route requests to the proxy.

ingress.pathSuffix

Suffix added to Ingress’s routing path pattern.

Specify * if your ingress matches path by glob pattern.

ingress.tls

TLS configurations for Ingress.

See the Kubernetes documentation for more details about annotations.

prePuller

prePuller.annotations

Annotations to apply to the hook and continous image puller pods. One example use case is to disable istio sidecars which could interfere with the image pulling.

prePuller.resources

These are standard Kubernetes resources with requests and limits for cpu and memory. They will be used on the containers in the pods pulling images. These should be set extremely low as the containers shut down directly or is a pause container that just idles.

They were made configurable as usage of ResourceQuota may require containers in the namespace to have explicit resources set.

prePuller.extraTolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

prePuller.hook

See the optimization section for more details.

prePuller.hook.enabled

prePuller.hook.podSchedulingWaitDuration

The hook-image-awaiter has a criteria to await all the hook-image-puller DaemonSet’s pods to both schedule and finish their image pulling. This flag can be used to relax this criteria to instead only await the pods that has already scheduled to finish image pulling after a certain duration.

The value of this is that sometimes the newly created hook-image-puller pods cannot be scheduled because nodes are full, and then it probably won’t make sense to block a helm upgrade.

An infinite duration to wait for pods to schedule can be represented by -1. This was the default behavior of version 0.9.0 and earlier.

prePuller.hook.nodeSelector

An object with key value pairs representing labels. K8s Nodes are required to have match all these labels for this Pod to scheduled on them.

disktype: ssd
nodetype: awesome

See the Kubernetes documentation for more details.

prePuller.hook.tolerations

Tolerations allow a pod to be scheduled on nodes with taints. These are additional tolerations other than the user pods and core pods default ones hub.jupyter.org/dedicated=user:NoSchedule or hub.jupyter.org/dedicated=core:NoSchedule. Note that a duplicate set of tolerations exist where / is replaced with _ as the Google cloud does not support the character / yet in the toleration.

Pass this field an array of Toleration objects.

See the Kubernetes docs for more info.

prePuller.continuous

See the optimization section for more details.

NOTE: If used with a Cluster Autoscaler (an autoscaling node pool), also add user-placeholders and enable pod priority.

prePuller.continuous.enabled

prePuller.pullProfileListImages

The singleuser.profileList configuration can let the user choose an image through the selection of a profile. This option determines if those images will be pulled, both by the hook and continuous pullers.

The reason to disable this, is that if you have for example 10 images which start pulling in order from 1 to 10, a user that arrives and wants to start a pod with image number 10 will need to wait for all images to be pulled, and then it may be preferable to just let the user arriving wait for a single image to be pulled on arrival.

prePuller.extraImages

See the optimization section for more details.

prePuller:
  extraImages:
    myExtraImageIWantPulled:
      name: jupyter/all-spark-notebook
      tag: 2343e33dec46

custom

Additional values to pass to the Hub. JupyterHub will not itself look at these, but you can read values in your own custom config via hub.extraConfig. For example:

custom:
  myHost: "https://example.horse"
hub:
  extraConfig:
    myConfig.py: |
      c.MyAuthenticator.host = get_config("custom.myHost")