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adding update on resizing droplet
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@@ -117,3 +117,51 @@ Step 3: Install conda / pip packages for all users
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.. include:: add_packages.txt
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.. include:: add_packages.txt
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Step 4: Resizing and editing the droplet
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========================================
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#. As you are using your JupyterHub, you may find that you need more memory,
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disk space, or CPUs. Digital Ocean servers can be resized in the
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"Resize Droplet" panel.
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.. image:: ../images/providers/digitalocean/resize-droplet.png
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:alt: Resize panel of digital ocean
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#. You will need to tell the JupyterHub to make use of these new resources.
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To accomplish this, you will follow the instructions in :ref:`topic/tljh-config`
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to set memory limits and reload the hub. This can be completed using the terminal
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in the JupyterHub, as in Step 3. It can also be completed through the Digital Ocean
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console.
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#. TLJH configuration options can be verified by viewing the tljh-config output.
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.. code-block:: bash
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sudo tljh-config show
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#. If you have changed your memory availability successfully, this will be reflected
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in the `nbresuse <https://github.com/yuvipanda/nbresuse>`_ extension in the upper-right
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when you open a Jupyter notebook on the Hub.
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.. image:: ../images/nbresuse.png
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:alt: nbresuse demonstration
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#. If you have changed the number of cores, this can be verified at the command line.
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``nproc`` displays the number of available cores, and should be equal to the
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number of cores you selected in the "Resize Droplet" panel.
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.. code-block:: bash
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nproc --all
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#. Disk space changes can be verified, as well. The ``df`` command shows how much disk
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space is available. The ``-hT`` argument allows us to have this printed in a human readable
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format, and condenses the output to show one storage volume.
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.. code-block:: bash
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df -hT /home
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