Features | Requirements | Installation | Configuration | Getting help | License | Resources
The systemdspawner enables JupyterHub to spawn single-user notebook servers using systemd.
If you want to use Linux Containers (Docker, rkt, etc) for isolation and security benefits, but don't want the headache and complexity of container image management, then you should use the SystemdSpawner.
With the systemdspawner, you get to use the familiar, traditional system administration tools, whether you love or meh them, without having to learn an extra layer of container related tooling.
The following features are currently available:
-
Limit maximum memory permitted to each user.
If they request more memory than this, it will not be granted (
mallocwill fail, which will manifest in different ways depending on the programming language you are using). -
Limit maximum CPU available to each user.
-
Provide fair scheduling to users independent of the number of processes they are running.
For example, if User A is running 100 CPU hogging processes, it will usually mean User B's 2 CPU hogging processes will never get enough CPU time as scheduling is traditionally per-process. With Systemd Spawner, both these users' processes will as a whole get the same amount of CPU time, regardless of number of processes being run. Good news if you are User B.
-
Accurate accounting of memory and CPU usage (via cgroups, which systemd uses internally).
You can check this out with
systemd-cgtop. -
/tmpisolation.Each user gets their own
/tmp, to prevent accidental information leakage. -
Spawn notebook servers as specific local users on the system.
This can replace the need for using SudoSpawner.
-
Restrict users from being able to sudo to root (or as other users) from within the notebook.
This is an additional security measure to make sure that a compromise of a jupyterhub notebook instance doesn't allow root access.
-
Restrict what paths users can write to.
This allows making
/read only and only granting write privileges to specific paths, for additional security. -
Automatically collect logs from each individual user notebook into
journald, which also handles log rotation.
Systemd Spawner requires you to use a Linux Distro that ships with at least systemd v211. The security related features require systemd v228 or v227. We recommend running with at least systemd v228. You can check which version of systemd is running with:
$ systemd --version | head -1
systemd 231Certain kernel options need to be enabled for the CPU / Memory limiting features
to work. If these are not enabled, CPU / Memory limiting will just fail
silently. You can check if your kernel supports these features by running
the check-kernel.bash script.
Currently, JupyterHub must be run as root to use Systemd Spawner. systemd-run
needs to be run as root to be able to set memory & cpu limits. Simple sudo rules
do not help, since unrestricted access to systemd-run is equivalent to root. We
will explore hardening approaches soon.
Each user's server is spawned to run as a local unix user account. Hence this spawner requires that all users who authenticate have a local account already present on the machine.
We recommend running this with systemd spawner. The default kernel has all the features we need, and a recent enough version of systemd to give us all the features.
The systemd version that ships by default with Jessie doesn't provide all the features we need, and the default kernel doesn't ship with the features we need. However, if you enable jessie-backports you can install a new enough version of systemd and linux kernel to get it to work fine.
The kernel has all the features we need, but the version of systemd (219) is too old for the security related features of systemdspawner. However, basic spawning, memory & cpu limiting will work.
You can install it from PyPI with:
pip install jupyterhub-systemdspawnerYou can enable it for your jupyterhub with the following lines in your
jupyterhub_config.py file
c.JupyterHub.spawner_class = 'systemdspawner.SystemdSpawner'Lots of configuration options for you to choose! You should put all of these
in your jupyterhub_config.py file:
mem_limitcpu_limituser_workingdirdefault_shellextra_pathsunit_name_templateisolate_tmpisolate_devicesdisable_user_sudoreadonly_pathsreadwrite_pathsuse_sudo
Specifies the maximum memory that can be used by each individual user. It can be
specified as an absolute byte value. You can use the suffixes K, M, G or T to
mean Kilobyte, Megabyte, Gigabyte or Terabyte respectively. Setting it to None disables
memory limits.
Even if you want individual users to use as much memory as possible, it is still good practice to set a memory limit of 80-90% of total physical memory. This prevents one user from being able to single handedly take down the machine accidentally by OOMing it.
c.SystemdSpawner.mem_limit = '4G'Defaults to None, which provides no memory limits.
This info is exposed to the single-user server as the environment variable
MEM_LIMIT as integer bytes.
A float representing the total CPU-cores each user can use. 1 represents one
full CPU, 4 represents 4 full CPUs, 0.5 represents half of one CPU, etc.
This value is ultimately converted to a percentage and rounded down to the
nearest integer percentage, i.e. 1.5 is converted to 150%, 0.125 is
converted to 12%, etc.
c.SystemdSpawner.cpu_limit = 4.0Defaults to None, which provides no CPU limits.
This info is exposed to the single-user server as the environment variable
CPU_LIMIT as a float.
Note: there is a bug in systemd v231 which prevents the CPU limit from being set to a value greater than 100%.
Completely unrelated to cpu_limit is the concept of CPU fairness - that each
user should have equal access to all the CPUs in the absense of limits. This
does not entirely work in the normal case for Jupyter Notebooks, since CPU
scheduling happens on a per-process level, rather than per-user. This means
a user running 100 processes has 100x more access to the CPU than a user running
one. This is far from an ideal situation.
Since each user's notebook server runs in its own Systemd Service, this problem is mitigated - all the processes spawned from a user's notebook server are run in one cgroup, and cgroups are treated equally for CPU scheduling. So independent of how many processes each user is running, they all get equal access to the CPU. This works out perfect for most cases, since this allows users to burst up and use all CPU when nobody else is using CPU & forces them to automatically yield when other users want to use the CPU.
The directory to spawn each user's notebook server in. This directory is what users see when they open their notebooks servers. Usually this is the user's home directory.
{USERNAME} and {USERID} in this configuration value will be expanded to the
appropriate values for the user being spawned.
c.SystemdSpawner.user_workingdir = '/home/{USERNAME}'Defaults to /home/{USERNAME}.
The default shell to use for the terminal in the notebook. Sets the SHELL environment
variable to this.
c.SystemdSpawner.default_shell = '/bin/bash'Defaults to whatever the value of the SHELL environment variable is in the JupyterHub
process, or /bin/bash if SHELL isn't set.
List of paths that should be prepended to the PATH environment variable for the spawned
notebook server. This is easier than setting the env property, since you want to
add to PATH, not completely replace it. Very useful when you want to add a virtualenv
or conda install onto the user's PATH by default.
c.SystemdSpawner.extra_paths = ['/home/{USERNAME}/conda/bin']{USERNAME} and {USERID} in this configuration value will be expanded to the
appropriate values for the user being spawned.
Defaults to [] which doesn't add any extra paths to PATH
Template to form the Systemd Service unit name for each user notebook server. This allows differentiating between multiple jupyterhubs with Systemd Spawner on the same machine. Should contain only [a-zA-Z0-9_-].
c.SystemdSpawner.unit_name_template = 'jupyter-{USERNAME}-singleuser'{USERNAME} and {USERID} in this configuration value will be expanded to the
appropriate values for the user being spawned.
Defaults to jupyter-{USERNAME}-singleuser
Setting this to true provides a separate, private /tmp for each user. This is very
useful to protect against accidental leakage of otherwise private information - it is
possible that libraries / tools you are using create /tmp files without you knowing and
this is leaking info.
c.SystemdSpawner.isolate_tmp = TrueDefaults to false.
This requires systemd version > 227. If you enable this in earlier versions, spawning will fail.
Setting this to true provides a separate, private /dev for each user. This prevents the
user from directly accessing hardware devices, which could be a potential source of
security issues. /dev/null, /dev/zero, /dev/random and the ttyp pseudo-devices will
be mounted already, so most users should see no change when this is enabled.
c.SystemdSpawner.isolate_devices = TrueDefaults to false.
This requires systemd version > 227. If you enable this in earlier versions, spawning will fail.
Setting this to true prevents users from being able to use sudo (or any other means) to
become other users (including root). This helps contain damage from a compromise of a user's
credentials if they also have sudo rights on the machine - a web based exploit will now only
be able to damage the user's own stuff, rather than have complete root access.
c.SystemdSpawner.disable_user_sudo = TrueDefaults to false.
This requires systemd version > 228. If you enable this in earlier versions, spawning will fail.
List of filesystem paths that should be mounted readonly for the users' notebook server. This
will override any filesystem permissions that might exist. Subpaths of paths that are mounted
readonly can be marked readwrite with readwrite_paths. This is useful for marking / as
readonly & only whitelisting the paths where notebook users can write.
c.SystemdSpawner.readonly_paths = ['/']{USERNAME} and {USERID} in this configuration value will be expanded to the
appropriate values for the user being spawned.
Defaults to None which disables this feature.
This requires systemd version > 228. If you enable this in earlier versions, spawning will fail. It can also contain only directories (not files) until systemd version 231.
List of filesystem paths that should be mounted readwrite for the users' notebook server. This
only makes sense if readonly_paths is used to make some paths readonly - this can then be
used to make specific paths readwrite. This does not override filesystem permissions - the
user needs to have appropriate rights to write to these paths.
c.SystemdSpawner.readwrite_paths = ['/home/{USERNAME}']{USERNAME} and {USERID} in this configuration value will be expanded to the
appropriate values for the user being spawned.
Defaults to None which disables this feature.
This requires systemd version > 228. If you enable this in earlier versions, spawning will fail. It can also contain only directories (not files) until systemd version 231.
Use sudo to run systemd-run / systemctl commands.
This can be useful if you want to run jupyterhub as a non-root user. However, the utility of this is currently limited - you will need to give it pretty wide rights, and is not entirely useful. Eventually, we will make this more secure by splitting out the actual parts that require root into a separate script.
It is still useful, however - things not running as root is always better than things running as root :)
c.SystemdSpawner.use_sudo = FalseDefaults to False.
We encourage you to ask questions on the mailing list. You can also participate in development discussions or get live help on Gitter.
We use a shared copyright model that enables all contributors to maintain the copyright on their contributions.
All code is licensed under the terms of the revised BSD license.