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Merge pull request #658 from jtpio/jupyterlab-3.0

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Yuvi Panda
2021-03-22 01:04:51 +05:30
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parent d732e889a6 1a4748bd06
commit 2c1f448792
9 changed files with 29 additions and 130 deletions
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4
docs/contributing/packages.rst
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@@ -40,9 +40,7 @@ Apt packages
============
Base operating system packages, including Python itself, are installed
via ``apt`` from the base Ubuntu repositories. The one exception to this
is nodejs, which is installed from the `nodesource <https://github.com/nodesource/distributions>`_
apt repository. The Ubuntu provided version of nodejs is usually too old.
via ``apt`` from the base Ubuntu repositories.
We generally do not pin versions of packages provided by apt, instead
just using the latest versions provided by Ubuntu.

4
docs/howto/admin/nbresuse.rst
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@@ -4,7 +4,7 @@
Check your memory usage
=======================
The `nbresuse <https://github.com/yuvipanda/nbresuse>`_ extension is part of
The `jupyter-resource-usage <https://github.com/jupyter-server/jupyter-resource-usage>`_ extension is part of
the default installation, and tells you how much memory your user is using
right now, and what the memory limit for your user is. It is shown in the
top right corner of the notebook interface. Note that this is memory usage
@@ -12,4 +12,4 @@ for everything your user is running through the Jupyter notebook interface,
not just the specific notebook it is shown on.
.. image:: ../../images/nbresuse.png
:alt: Memory limit / usage shown with nbresuse
:alt: Memory limit / usage shown with jupyter-resource-usage

22
docs/howto/admin/resize.rst
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@@ -1,10 +1,10 @@
.. _howto/admin/resize:
=================================================
Resize the resources available to your JupyterHub
Resize the resources available to your JupyterHub
=================================================
As you are using your JupyterHub, you may need to increase or decrease
As you are using your JupyterHub, you may need to increase or decrease
the amount of resources allocated to your TLJH install. The kinds of resources that can be
allocated, as well as the process to do so, will depend on the provider / interface for your
VM. We recommend consulting the installation page for your provider for more information. This
@@ -18,12 +18,12 @@ Currently there are instructions to resize your resources on the following provi
Once resources have been reallocated, you must tell TLJH to make use of these resources,
and verify that the resources have become available.
Verifying a Resize
Verifying a Resize
==================
#. Once you have resized your server, tell the JupyterHub to make use of
these new resources. To accomplish this, follow the instructions in
:ref:`topic/tljh-config` to set new memory or CPU limits and reload the hub. This can be completed
#. Once you have resized your server, tell the JupyterHub to make use of
these new resources. To accomplish this, follow the instructions in
:ref:`topic/tljh-config` to set new memory or CPU limits and reload the hub. This can be completed
using the terminal in the JupyterHub (or via SSH-ing into your VM and using this terminal).
#. TLJH configuration options can be verified by viewing the tljh-config output.
@@ -36,14 +36,14 @@ Verifying a Resize
#. **To verify changes to memory**, confirm that it worked by starting
a new server (if you had one previously running, click "Control Panel -> Stop My Server" to
shut down your active server first), opening a notebook, and checking the value of the
`nbresuse <https://github.com/yuvipanda/nbresuse>`_ extension in the upper-right.
shut down your active server first), opening a notebook, and checking the value of the
`jupyter-resource-usage <https://github.com/jupyter-server/jupyter-resource-usage>`_ extension in the upper-right.
.. image:: ../../images/nbresuse.png
:alt: nbresuse demonstration
:alt: jupyter-resource-usage demonstration
#. **To verify changes to CPU**, use the ``nproc`` from a terminal.
This command displays the number of available cores, and should be equal to the
#. **To verify changes to CPU**, use the ``nproc`` from a terminal.
This command displays the number of available cores, and should be equal to the
number of cores you selected in your provider's interface.
.. code-block:: bash

4
docs/howto/admin/resource-estimation.rst
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@@ -62,10 +62,10 @@ stop, unlike with RAM.
Recommended\, CPU = (Max\, concurrent\, users \times Max\, CPU\, usage\, per\, user) + 20\%
The ``20%`` is overhead for TLJH and related services. This is around 20% of a
The ``20%`` is overhead for TLJH and related services. This is around 20% of a
single modern CPU. This, of course, is just an estimate. We recommend using
the same process used to estimate Memory required for estimating CPU required.
You cannot use nbresuse for this, but you should carry out normal workflow and
You cannot use jupyter-resource-usage for this, but you should carry out normal workflow and
investigate the CPU usage on the machine.
Disk space

10
docs/topic/installer-actions.rst
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@@ -4,21 +4,19 @@
What does the installer do?
===========================
This document details what exactly the installer does to the machine it is
This document details what exactly the installer does to the machine it is
run on.
``apt`` Packages installed
==========================
The packages ``python3`` and ``python3-venv`` are installed from the apt repositories.
Since we need an recent & supported version of ``nodejs``, we install it from
`nodesource <https://github.com/nodesource/distributions>`_.
Hub environment
===============
JupyterHub is run from a python3 virtual environment located in ``/opt/tljh/hub``. It
uses the system's installed python and is owned by root. It also contains a binary install
uses the system's installed python and is owned by root. It also contains a binary install
of `traefik <http://traefik.io/>`_. This virtual environment is completely managed by TLJH.
.. note::
@@ -34,7 +32,7 @@ User environment
By default, a ``miniconda`` environment is installed in ``/opt/tljh/user``. This contains
the notebook interface used to launch all users, and the various packages available to all
users. The environment is owned by the ``root`` user. JupyterHub admins may use
users. The environment is owned by the ``root`` user. JupyterHub admins may use
to ``sudo -E conda install`` or ``sudo -E pip install`` packages into this environment.
This conda environment is added to ``$PATH`` for all users started with JupyterHub. If you
@@ -49,7 +47,7 @@ This should let you run various ``conda`` and ``pip`` commands. If you run into
.. code-block:: bash
sudo env PATH=${PATH} <command>
sudo env PATH=${PATH} <command>
By default, ``sudo`` does not respect any custom environments you have activated. The ``env PATH=${PATH}``
'fixes' that.