.. _insatll/digitalocean: =========================== Installing on Digital Ocean =========================== Goal ==== By the end of this tutorial, you should have a JupyterHub with some admin users and a user environment with packages you want installed running on `DigitalOcean `_. Pre-requisites ============== #. A DigitalOcean account with a payment method attached. Step 1: Installing The Littlest JupyterHub ========================================== Let's create the server on which we can run JupyterHub. #. Log in to `DigitalOcean `_. You might need to attach a credit card or other payment method to your account before you can proceed with the tutorial. #. Click the **Create** button on the top right, and select **Droplets** from the dropdown menu. DigitalOcean calls servers **droplets**. .. image:: ../images/providers/digitalocean/create-menu.png :alt: Dropdown menu on clicking 'create' in top right corner This takes you to a page titled **Create Droplets** that lets you configure your server. #. Under **Choose an image**, select **18.04 x64** under **Ubuntu**. .. image:: ../images/providers/digitalocean/select-image.png :alt: Select 18.04 x64 image under Ubuntu #. Under **Choose a size**, select the size of the server you want. The default (4GB RAM, 2CPUs, 20 USD / month) is not a bad start. You can resize your server later if you need. Check out our guide on How To :ref:`howto/admin/resource-estimation` to help pick how much Memory, CPU & disk space your server needs. #. Scroll down to **Select additional options**, and select **User data**. .. image:: ../images/providers/digitalocean/additional-options.png :alt: Turn on User Data in additional options This opens up a textbox where you can enter a script that will be run when the server is created. We will use this to set up The Littlest JupyterHub on this server. #. Copy the text below, and paste it into the user data text box. Replace ```` with the name of the first **admin user** for this JupyterHub. This admin user can log in after the JupyterHub is set up, and can configure it to their needs. **Remember to add your username**! .. code-block:: bash #!/bin/bash curl https://raw.githubusercontent.com/jupyterhub/the-littlest-jupyterhub/master/bootstrap/bootstrap.py \ | sudo python3 - \ --admin .. note:: See :ref:`topic/installer-actions` if you want to understand exactly what the installer is doing. :ref:`topic/customizing-installer` documents other options that can be passed to the installer. #. Under the **Finalize and create** section, enter a ``hostname`` that descriptively identifies this server for you. .. image:: ../images/providers/digitalocean/hostname.png :alt: Select suitable hostname for your server #. Click the **Create** button! You will be taken to a different screen, where you can see progress of your server being created. .. image:: ../images/providers/digitalocean/server-create-wait.png :alt: Server being created #. In a few seconds your server will be created, and you can see the **public IP** used to access it. .. image:: ../images/providers/digitalocean/server-create-done.png :alt: Server finished creating, public IP available #. The Littlest JupyterHub is now installing in the background on your new server. It takes around 5-10 minutes for this installation to complete. #. Check if the installation is complete by copying the **public ip** of your server, and trying to access it with a browser. This will fail until the installation is complete, so be patient. #. When the installation is complete, it should give you a JupyterHub login page. .. image:: ../images/first-login.png :alt: JupyterHub log-in page #. Login using the **admin user name** you used in step 6, and a password. Use a strong password & note it down somewhere, since this will be the password for the admin user account from now on. #. Congratulations, you have a running working JupyterHub! Step 2: Adding more users ========================== .. include:: add_users.txt Step 3: Install conda / pip packages for all users ================================================== .. include:: add_packages.txt Step 4: Resizing and editing the droplet ======================================== #. As you are using your JupyterHub, you may find that you need more memory, disk space, or CPUs. Digital Ocean servers can be resized in the "Resize Droplet" panel. .. image:: ../images/providers/digitalocean/resize-droplet.png :alt: Resize panel of digital ocean #. You will need to tell the JupyterHub to make use of these new resources. To accomplish this, you will follow the instructions in :ref:`topic/tljh-config` to set memory limits and reload the hub. This can be completed using the terminal in the JupyterHub, as in Step 3. It can also be completed through the Digital Ocean console. #. TLJH configuration options can be verified by viewing the tljh-config output. .. code-block:: bash sudo tljh-config show #. If you have changed your memory availability successfully, this will be reflected in the `nbresuse `_ extension in the upper-right when you open a Jupyter notebook on the Hub. .. image:: ../images/nbresuse.png :alt: nbresuse demonstration #. If you have changed the number of cores, this can be verified at the command line. ``nproc`` displays the number of available cores, and should be equal to the number of cores you selected in the "Resize Droplet" panel. .. code-block:: bash nproc --all #. Disk space changes can be verified, as well. The ``df`` command shows how much disk space is available. The ``-hT`` argument allows us to have this printed in a human readable format, and condenses the output to show one storage volume. .. code-block:: bash df -hT /home