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small updates to the docs

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Chris Holdgraf
2018-07-31 09:38:25 -07:00
parent d0f3b581e0
commit ccac483c50
7 changed files with 100 additions and 24 deletions
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46
docs/howto/auth/ldap.rst Normal file
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.. _howto/auth/ldap:
=============================
Using LDAP for authentication
=============================
`LDAP <https://en.wikipedia.org/wiki/Lightweight_Directory_Access_Protocol>`_
is an open and widely-used protocol for authentication.
The `LDAPAuthenticator's documentation <https://github.com/jupyterhub/ldapauthenticator#required-configuration>`_
lists the various configuration options you can set for LDAPAuthenticator. You can set them
in TLJH with the following pattern:
.. code-block:: bash
sudo -E tljh-config set auth.<authenticator-name>.<config-option-name> <config-option-value>
When the documentation asks you to set ``LDAPAuthenticator.server_address`` to some
value, you can do that with the following command:
.. code-block:: bash
sudo -E tljh-config set auth.LDAPAuthenticator.server_address = 'my-ldap-server'
Enabling the authenticator
==========================
For LDAPAuthenticator, the fully qualified name is ``ldapauthenticator.LDAPAuthenticator``.
This is the same name that the `documentation asks <https://github.com/jupyterhub/ldapauthenticator#usage>`_
you to set ``c.JupyterHub.authenticator_class`` to.
For LDAPAuthenticator, this would be:
.. code-block:: bash
sudo -E tljh-config set auth.type ldapauthenticator.LDAPAuthenticator
Once enabled, you need to reload JupyterHub for the config to take effect.
.. code-block:: bash
sudo -E tljh-config reload
Try logging in a separate incognito window to check if your configuration works. This
lets you preserve your terminal in case there were errors. If there are
errors, :ref:`troubleshooting/logs` should help you debug them.

15
docs/howto/resource-estimation.rst
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@@ -40,9 +40,16 @@ Maximum memory allowed per user
Depending on what kinda work your users are doing, they will use different amounts
of memory. The easiest way to determine this is to run through a typical user
workflow yourself, and measure how much memory is used. Add 20-40% headroom for
users to 'play around', and that should be the maximum memory allowed per user.
The system will prevent users from using more memory than this.
workflow yourself, and measure how much memory is used.
For example, you can begin running a Jupyter Notebook session on your JupyterHub, then open a
terminal on the JupyterHub and use ``top`` to track how much memory you use
as you go through the material. A good rule of thumb is to take the maximum amount of memory you used during
your session, and add 20-40% headroom for users to 'play around'. This is the
maximum amount of memory that should be given to each user.
If users use *more* than this alloted amount of memory, their kernel will restart (and all
their progress in the current session will be lost).
CPU
===
@@ -56,7 +63,7 @@ stop, unlike with RAM.
Server CPU Recommended = (Maximum concurrent users \times Maximum CPU usage per user) + 0.2
The ``0.2`` is overhead for TLJH and related services. **Server CPU Recommended**
is the amount of CPU the server you aquire should have. We recommend using
is the amount of CPU the server you acquire should have. We recommend using
the same process used to estimate Memory required for estimating CPU required.
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