Application Configuration#
The JupyterHub Outpost uses a configuration file outpost_config.py similar to jupyterhub_config.py of JupyterHub. The Spawner configuration for the Outpost is therefore similar to the Spawner configuration in JupyterHub.
The easiest way is configure the Outpost’s configuration file is via the outpostConfig key in the helm chart’s values.yaml file.
Persistent database#
To use a persistent database such as postgresql with JupyterHub Outpost, use extraEnvVarsSecrets in your values.yaml file. All possible values related to the database connection can be found in the source code itself.
Ensure that you have a database such postgres installed and that a JupyterHub Outpost user and database exists.
Example SQL commands for postgresql:
CREATE USER jupyterhuboutpost WITH ENCRYPTED PASSWORD '...';
CREATE DATABASE jupyterhuboutpost OWNER jupyterhuboutpost;
Create a secret in your Outpost namespace with the required values before installing JupyterHub Outpost:
kind: Secret
metadata:
name: my-db-secret
...
stringData:
SQL_TYPE: "postgresql"
SQL_USER: "jupyterhuboutpost"
SQL_PASSWORD: "..."
SQL_HOST: "postgres.database.svc"
SQL_PORT: "5432"
SQL_DATABASE: "jupyterhuboutpost"
And add the database secret to your Outpost values.yaml file:
...
extraEnvVarsSecrets:
- my-db-secret
Simple KubeSpawner#
In this example, we use the KubeSpawner to spawn all single-user servers with the same image.
values.yaml file:
outpostConfig: |
from kubespawner import KubeSpawner
c.JupyterHubOutpost.spawner_class = KubeSpawner
c.KubeSpawner.image = "jupyter/minimal-notebook:notebook-7.0.3"
Update or install JupyterHub Outpost with values.yaml file:
helm upgrade --install -f values.yaml --namespace outpost outpost jupyterhub-outpost/jupyterhub-outpost
The JupyterHub OutpostSpawner can override each c.<Spawner>.<key> value using the custom_misc feature. For more information, take a look at the OutpostSpawner configuration. In the example above, custom_misc could be used to dynamically override the c.KubeSpawner.image value.
Customize Logging#
For the logging configuration, the Outpost offers these options (corresponding to the logging options of JupyterHub):
c.JupyterHubOutpost.log_level = ...
c.JupyterHubOutpost.log_datafmt = ...
c.JupyterHubOutpost.log_format = ...
If more customization is required, one can do this directly in the outpost_config.py file itself (possible via the outpostConfig key of the helm chart).
class TornadoGeneralLoggingFilter(logging.Filter):
def filter(self, record):
# I don't want to see this log line generated by tornado
if str(record.msg).startswith("Could not open static file"):
return False
return True
logging.getLogger("tornado.general").addFilter(TornadoGeneralLoggingFilter())
import os
logged_logger_name = os.environ.get("LOGGER_NAME", "MyOutpostInstance")
c.JupyterHubOutpost.log_format = f"%(color)s[%(levelname)1.1s %(asctime)s.%(msecs).03d {logged_logger_name} %(name)s %(module)s:%(lineno)d]%(end_color)s %(message)s"
Sanitize Spawner.start response#
JupyterHub Outpost will use the return value of the start function of the configured SpawnerClass to tell JupyterHub where the single-user server will be running. For example, in the KubeSpawner, the response of KubeSpawner.start() will be something like http://jupyter-<id>-<user_id>:<port> and the Outpost will forward this response to JupyterHub.
The JupyterHub OutpostSpawner will take this information and create a ssh port-forwarding process with the option -L 0.0.0.0:<local_jhub_port>:jupyter-<id>-<user_id>:<port>. Afterwards, JupyterHub will look for the newly created single-user server at http://localhost:<local_jhub_port>. If the response of the start function of the configured SpawnerClass in the JupyterHub Outpost service is not correct, OutpostSpawner and Outpost cannot work together properly. To ensure nearly all Spawners can be used anyway, you can override the response send to the OutpostSpawner.
# In the `outpostConfig` key of your helm values.yaml file or your outpost_config.py file:
# This may be a coroutine
def sanitize_start_response(spawner, original_response):
# ... determine the correct location for the new single-user server
return "<...>"
c.JupyterHubOutpost.sanitize_start_response = sanitize_start_response
Note
If you don’t know where your single-user server will be running at the end of the start function, you have to return an empty string. In that case, JupyterHub OutpostSpawner won’t create a ssh port-forwarding process. Instead, the start process of the single-user server has to send a POST request to the $JUPYTERHUB_SETUPTUNNEL_URL url. Have a look at the API Endpoints of the OutpostSpawner (https://jupyterhub-outpostspawner.readthedocs.io/en/latest/apiendpoints.html) for more information.
Disable JupyterHub configuration overwrite#
By default, JupyterHubs can overwrite the JupyterHub Outpost configuration with the OutpostSpawner’s custom_misc function. As an administrator of the JupyterHub Outpost service, you can prevent this.
# In the `outpostConfig` key of your helm values.yaml file or your outpost_config.py file:
async def allow_override(jupyterhub_name, misc):
if jupyterhub_name == "trustedhub":
return True
if list(misc.keys()) != ["image"]:
return False
return misc.get("image", "None") in ["allowed_image1", "allowed_image2"]
c.JupyterHubOutpost.allow_override = allow_override
The above example leads to the following behaviour:
JupyterHub with credential username “trustedhub” can overwrite anything.
If a JupyterHub (other than trustedhub) tries to overwrite anything except the
imagekey, it will not be allowed.The given image must be
allowed_image1orallowed_image2.
Note
If custom_misc in the POST request is empty, the allow_override function will not be called.
If allow_override returns False, the JupyterLab will not be started. An error message will be returned to the JupyterHub OutpostSpawner and shown to the user.
Recreate ssh tunnels at startup#
If your JupyterHub Outpost is used as a ssh node in the JupyterHub OutpostSpawner, all port-forwarding processes have to be recreated if the JupyterHub Outpost service was restarted. While restarting, existing ssh port-forwarding process will fail after a few seconds and the user’s single-user server would be unreachable.
By default tunnels will be recreated at JupyterHub Outpost restarts. You can disable this behaviour with the ssh_recreate_at_start key.
# In the `outpostConfig` key of your helm values.yaml file or your outpost_config.py file:
async def restart_tunnels(wrapper, jupyterhub_credential):
if jupyterhub_credential == "local_jupyterhub":
return False
return True
c.JupyterHubOutpost.ssh_recreate_at_start = restart_tunnels
# c.JupyterHubOutpost.ssh_recreate_at_start = False
Note
JupyterHub Outpost will use the stored JupyterHub API token to recreate the port-forwarding process. If the API token is no longer valid, this will fail. The single-user server would then be unreachable and must be restarted by the user.
Flavors#
Overview#
Flavors define preconfigured resource templates for User sessions. They specify runtime limits and user constraints, helping you manage system load and provide differentiated access based on user groups or hub configurations.
Flavors are mandatory and part of the default configuration of the Outpost. All users will have access to the default flavors unless specified otherwise.
Basic Flavor Structure#
A flavor configuration typically looks like this:
flavors:
flavors:
default:
max: 20
maxPerUser: 3
weight: 11
display_name: "Default"
description: "Service will run with normal resources for max 5 days"
runtime:
hours: 120
resources:
cpu_guarantee: 0.1
cpu_limit: 1
mem_guarantee: "256M"
mem_limit: "2048M"
Resources must be used by your Spawner Configuration.
Parameters#
Key |
Description |
|---|---|
|
User-facing name of the flavor |
|
Description of resources or limitations |
|
Maximum lifetime of a session using this flavor. Supported keys: days, hours, minutes |
|
Can be used to define allowed resources |
|
Maximum total number of concurrent sessions using this flavor |
|
Maximum number of sessions per user using this flavor |
|
Controls the ordering in the flavor list; higher weights appear first |
Per-User Flavor Control#
You can assign flavors to users based on their authentication attributes (like name, email). This allows differentiated access control. Ask the JupyterHub authenticator for the attributes, or set the log level to trace and check the Outpost logs.
Example 1: Allow minimal flavor for non-company users#
users:
publicUsers:
negate_authentication: true
authentication:
name: ".*@mycompany.org"
flavors: ["minimal"]
weight: 10
All users not ending with
@mycompany.orgare only allowed to use theminimalflavor.
Example 2: Block all Gmail users#
users:
googleUsers:
authentication:
name: ".*g(oogle)*mail.com$"
forbidden: true
weight: 20
Users with Gmail or Google Mail addresses will be denied access.
Each field in
authentication(likename,
A regular expression (e.g.,
"^user[0-9]+@example.com$")A glob-style pattern (e.g.,
"*@example.com")A literal value (e.g.,
"admin@example.com")Or a list of allowed literal values.
The system will try to match in this order: Regex → Glob → Exact match.
This gives you flexibility in how users are grouped and access is granted.
Manipulate incoming user authentication dict#
Before checking if the given user authentication dict matches your configuration, you might want to manipulate it. E.g. you don’t care about lower- / uppercase differences in the users name field:
# In the `outpostConfig` key of your helm values.yaml file or your outpost_config.py file:
async def lowercase_name(authentication):
if "name" in authentication.keys():
authentication["name"] = authentication["name"].lower()
return authentication
c.JupyterHubOutpost.update_user_authentication = lowercase_name
Per-Hub Flavor Control#
In environments with multiple JupyterHub instances, you can configure flavors per hub using the hubs section:
hubs:
minimalhub:
weight: 15
jupyterhub_name:
- hubmini
flavors:
- minimal
normalhubs:
weight: 10
jupyterhub_name:
- huba
- hubb
flavors:
- default
hubminiwill only offer theminimalflavor.hubaandhubbwill offer thedefaultflavor.
The
weightcontrols the priority if multiple groups match — the one with the highest weight takes precedence.
Default Behavior#
If no user or hub restrictions are configured:
All defined flavors will be available to all users.
This behavior can be overridden by defining
usersorhubs.
Recommendations#
Start with a base set of flavors (
minimal,default) and refine access over time.Use
negate_authenticationfor simple allow/deny matching logic based on patterns.Always test your regex for
namecarefully to avoid unintentional matches.Use
weightwisely to control precedence in overlapping rules.
Use Cases#
Blocked Users: Administrators can configure flavors for specific users that deny access, effectively blocking them from launching any jupyter servers.
Prioritized Users: For power users, administrators can assign more resources (e.g., higher CPU, additional memory) to ensure they have the performance needed for demanding tasks.
External Users: For guest or external users, administrators may provide a default, minimal resource allocation to prevent overuse of the system’s resources.
Benefits#
Resource Management: Fine-grained control over resource allocation ensures efficient use of system resources.
User Control: Administrators can easily adjust resource access based on user needs or status (e.g., external user vs internal user).
Scalability: As your user base grows, you can easily apply different flavors to new users without major changes to the overall configuration.