Revert "Merge of latest changes into RTD theme to enable multi-language support (#604)"

This reverts commit 186f1e02b8.
2026-09-05 21:31:30 +00:00 · 2019-07-10 15:20:53 -07:00
parent 186f1e02b8
commit f2a5c5a46b
407 changed files with 2660 additions and 2918 deletions
@@ -0,0 +1,276 @@
+.. _aws-web:
+
+Create and launch |CL-ATTR| from Amazon Web Services
+######################################################
+
+This tutorial walks you through creating and launching a |CL|
+:abbr:`AMI (Amazon Machine Image)` instance from the
+:abbr:`AWS (Amazon Web Services)` console and complete the following tasks:
+
+#. Locate and select the |CL| OS Basic AMI in the AWS Marketplace.
+#. Create a new public and private key pair to allow you to connect to your
+   |CL| instance securely.
+#. Launch the new |CL| instance and connect to it.
+#. Update your instance of |CL| using the :command:`swupd` command.
+#. Stop the |CL| instance.
+
+Prerequisites
+*************
+
+This tutorial assumes the following statements are true:
+
+* You are using a linux-based system to access AWS and can run :command:`SSH`
+  to access the remote |CL| AWS image.
+* Your browser puts downloaded files in the :file:`$HOME/Downloads`
+  directory.
+* You have already set up an AWS user account and logged into the AWS
+  console.
+
+.. note::
+   This tutorial uses a |CL| AMI t2.micro instance that is eligible for the
+   AWS free tier. To learn more about AWS and setting up an account, visit the
+   AWS website at http://aws.amazon.com.
+
+Locate, select, and launch the |CL| Basic AMI
+*********************************************
+
+#. Start from your main AWS services console menu in your browser and select the
+   :guilabel:`EC2` text as shown in figure 1:
+
+   .. figure:: figures/aws-web-1.png
+      :scale: 50 %
+      :alt: AWS Console
+
+      Figure 1: :guilabel:`AWS Console`
+
+   This selection brings up your :guilabel:`EC2 Dashboard` menu.
+
+#. To create a new |CL| instance from the :guilabel:`EC2 Dashboard` menu,
+   select the :guilabel:`Launch Instance` button as shown in figure 2:
+
+   .. figure:: figures/aws-web-2.png
+      :scale: 50 %
+      :alt: EC2 Dashboard
+
+      Figure 2: :guilabel:`EC2 Dashboard`
+
+   This selection takes you to the
+   :guilabel:`Step 1: Choose an Amazon Machine Image (AMI)` menu.
+
+#. To find the :guilabel:`Clear Linux OS Basic` AMI in the
+   :guilabel:`Step 1: Choose an Amazon Machine Image (AMI)` menu, do the
+   following:
+
+   #. In the lefthand navigation window, select the
+      :guilabel:`AWS Marketplace` menu item to bring up the search bar to
+      :guilabel:`Search AWS Marketplace Products`.
+
+   #. In the search bar, type "clear linux os" and hit the :kbd:`Enter` key to
+      search for and locate the :guilabel:`Clear Linux OS Basic` AMI.
+
+   #. Select the :guilabel:`Clear Linux OS Basic` AMI by clicking on the
+      :guilabel:`Select` button as shown in figure 3:
+
+      .. figure:: figures/aws-web-3.png
+         :scale: 50 %
+         :alt: Step 1: Choose AMI
+
+         Figure 3: :guilabel:`Step 1: Choose AMI`
+
+   #. A pop-up dialog box appears showing you more information about the
+      :guilabel:`Clear Linux OS Basic` AMI along with the pricing details for running
+      |CL| on different platform configurations as shown in figure 4. Select
+      the :guilabel:`Continue` button.
+
+      .. figure:: figures/aws-web-4.png
+         :scale: 50 %
+         :alt: Clear Linux OS Basic
+
+         Figure 4: :guilabel:`Clear Linux OS Basic`
+
+#. The :guilabel:`Choose Instance Type` menu appears as shown in figure 5.
+
+   .. figure:: figures/aws-web-5.png
+      :scale: 50 %
+      :alt: Choose an Instance Type
+
+      Figure 5: :guilabel:`Choose an Instance Type`
+
+   Select the :guilabel:`t2.micro` type by clicking the box on the left side
+   of the instance and then select the :guilabel:`Review and Launch` button to
+   move to the :guilabel:`Step 7: Review the Instance Launch` menu.
+
+   .. note::
+
+      You can configure the instance details, add additional storage, add
+      tags, and configure the security group before selecting the
+      :guilabel:`Review and Launch` button if you want to further customize
+      this |CL| instance.
+
+#. The :guilabel:`Step 7: Review the Instance Launch` menu, shown in figure 6,
+   allows you to
+   :guilabel:`Cancel` the process, return to the :guilabel:`Previous` screen
+   to change the configuration or :guilabel:`Launch` the instance defined.
+
+   .. figure:: figures/aws-web-6.png
+      :scale: 50 %
+      :alt: Step 7: Review the Instance Launch
+
+      Figure 6: :guilabel:`Step 7: Review the Instance Launch`
+
+   #. Select the :guilabel:`Launch` button. A dialog box appears, as shown in
+      figure 7, asking you to
+      :guilabel:`Select an existing key pair or create a new pair`.
+
+      .. figure:: figures/aws-web-7.png
+         :scale: 50 %
+         :alt: Select an existing key pair or create a new pair
+
+         Figure 7: :guilabel:`Select an existing key pair or create a new pair`
+
+      #. Select the :guilabel:`Create a new key pair` option.
+
+      #. For the :guilabel:`Key pair name` field, enter `AWSClearTestKey`.
+
+      #. Select the :guilabel:`Download Key Pair` button to download the
+         :file:`AWSClearTestKey.pem` to your browser's defined
+         :file:`Downloads` directory.
+
+      #. When the file finishes downloading, select the
+         :guilabel:`Launch Instances` button to proceed to the
+         :guilabel:`Launch Status` menu shown in figure 8.
+
+         .. figure:: figures/aws-web-8.png
+            :scale: 50 %
+            :alt: Launch Status
+
+            Figure 8: :guilabel:`Launch Status`
+
+   #. Once the :guilabel:`Launch Status` page changes to what is shown in
+      figure 9, select the :guilabel:`View Instances` button to view your
+      :guilabel:`Instances` dashboard.
+
+      .. figure:: figures/aws-web-9.png
+         :scale: 50 %
+         :alt: View Instance
+
+         Figure 9: :guilabel:`View Instance`
+
+Connect to your Clear Linux OS Basic instance
+*********************************************
+
+Your :guilabel:`Instances` Dashboard is shown in figure 10 with the new |CL|
+OS basic instance already selected and in the running state. If there are
+other instances available, they are also listed but not selected.
+
+.. figure:: figures/aws-web-10.png
+   :scale: 50 %
+   :alt: Instance Dashboard
+
+   Figure 10: :guilabel:`Instance Dashboard`
+
+#. To connect to your running instance, click the :guilabel:`Connect` button
+   located at the top of your dashboard. AWS brings up the pop-up dialog
+   box shown in figure 11 describing how to connect to your running instance.
+
+.. _fig-aws-web-11:
+
+.. figure:: figures/aws-web-11.png
+   :scale: 50 %
+   :alt: Connect to Your Instance
+
+   Figure 11: :guilabel:`Connect to Your Instance`
+
+#. Open a terminal on your system. You should be in your :file:`$HOME`
+   directory.
+
+#. Copy the previously downloaded keyfile from the :file:`Downloads`
+   directory to the current directory.
+
+   .. code-block:: console
+
+      cp Downloads/AWSClearTestKey.pem .
+
+#. Change the attributes of the :file:`AWSClearTestKey.pem` using the
+   :command:`chmod` command as instructed in the dialog box shown in figure
+   11.
+
+   .. code-block:: console
+
+      chmod 400 AWSClearTestKey.pem
+
+#. Copy the text highlighted in the :guilabel:`Example:` section that is
+   shown in :ref:`figure 11<fig-aws-web-11>`. Paste the copied text into your
+   terminal, change the text before the `@` sign to the username `clear`, and
+   press the :kbd:`Enter` key to execute the command.
+
+   .. code-block:: console
+
+      ssh -i "AWSClearTestKey.pem" clear@ec2-34-209-39-184.us-west-2.compute.amazonaws.com
+
+#. A message appears on the terminal stating the authenticity of the host can't
+   be established and prompts you with the message:
+
+   .. code-block:: console
+
+      The authenticity of host 'ec2-34-209-39-184.us-west-2.compute.amazonaws.com (34.209.39.184)' can't be established.
+      ECDSA key fingerprint is SHA256:LrziT5Ar66iBTfia8qmiIsrfBUm/UGam76U8bDR6yJc.
+      Are you sure you want to continue connecting (yes/no)?
+
+#. Type `yes` and hit the :kbd:`Enter` key. Another warning is printed to the
+   terminal and you are now at the command prompt of your new |CL| instance.
+
+   .. code-block:: console
+
+      Warning: Permanently added 'ec2-34-209-39-184.us-west-2.compute.amazonaws.com,34.209.39.184' (ECDSA) to the list of known hosts.
+      clear@clr-96a8565d0ca54b0c80364a1e5e7b0f88 ~ $
+
+Update the |CL| instance
+************************
+
+Run the :command:`sudo swupd update` command to update the operating
+system as shown in figure 12:
+
+.. figure:: figures/aws-web-12.png
+   :scale: 50 %
+   :alt: sudo swupd update
+
+   Figure 12: :guilabel:`sudo swupd update`
+
+In this example we updated from version 18940 to 19100.
+
+Stop the |CL| instance
+**********************
+
+When you are finished using your AWS |CL| instance you need to stop it using
+the :guilabel:`Instances` dashboard to stop accruing charges. Complete the
+following steps from the :guilabel:`Instances` dashboard to stop your AWS |CL|
+instance from running.
+
+#. Select the :guilabel:`Actions` button to bring up a pull-down menu.
+
+#. Select the :guilabel:`Instance State` menu item to expand the options.
+
+#. Select :guilabel:`Stop` menu item to shut down the running instance.
+
+   Figure 13 illustrates these steps.
+
+   .. figure:: figures/aws-web-13.png
+      :scale: 50 %
+      :alt: Stop Instance
+
+      Figure 13: :guilabel:`Stop Instance`
+
+#. A pop-up dialog box appears warning you that any ephemeral storage of
+   your instance will be lost. Select the :guilabel:`Yes, Stop` button to stop
+   your |CL| instance.
+
+.. figure:: figures/aws-web-14.png
+   :scale: 50 %
+   :alt: Stop Instances
+
+   Figure 14: :guilabel:`Stop Instances`
+
+Congratulations! You are up and running with |CL| on AWS. To see what you
+can do with your |CL| instance, visit our :ref:`tutorials <tutorials>`
+section for examples on using your |CL| system.
@@ -0,0 +1,544 @@
+.. _azure:
+
+Run |CL-ATTR| using Microsoft Azure CLI 2.0
+###########################################
+
+|CL-ATTR| is available for you to use in the Microsoft* Azure* marketplace and
+is offered with three different images, also known as a
+:abbr:`SKU (Stock Keeping Unit)`.
+
+* |CL| Basic - This SKU consists of a bare-bones system which can be used as a
+  starting point for those wanting to explore and build out a system with
+  additional software bundles of their choosing.
+
+* |CL| Containers - This SKU comes with the containers-basic software bundle
+  already installed.
+
+* |CL| Machine-learning - This SKU comes pre-loaded with popular open source
+  tools for developing machine learning applications.
+
+You can access these images directly from your MS Azure dashboard through the
+`Azure portal`_ or by using the MS Azure :abbr:`CLI (Command Line Interface)`
+2.0. If you do not already have an account set up with MS Azure, you can sign
+up for a `MS Azure free account`_ to access the |CL|
+:abbr:`VM(Virtual Machine)` images.
+
+The Azure CLI offers the ability to create and manage resources in MS Azure
+from the command line. In this tutorial you learn to:
+
+#. Install the latest MS Azure CLI on your |CL| machine.
+
+#. Log into MS Azure using the CLI 2.0 interface.
+
+#. Create a MS Azure resource group.
+
+#. Locate the |CL| images.
+
+#. Create and log into the |CL| virtual machine.
+
+#. Stop and deallocate the |CL| VM and resources.
+
+To use the MS Azure CLI 2.0 on your |CL| system, your system must have the
+following packages installed:
+
+* Python 2.7 or later
+
+* libffi
+
+* OpenSSL 1.0.2
+
+You can check to see what versions you have installed on your system by
+running the individual commands as follows:
+
+.. code-block:: bash
+
+   python --version
+
+.. code-block:: console
+
+   python 2.7.12
+
+.. code-block:: bash
+
+   openssl version
+
+.. code-block:: console
+
+   OpenSSL 1.0.2n 7 Dec 2017
+
+.. code-block:: bash
+
+   ls -l /usr/lib64/libffi*
+
+.. code-block:: console
+
+   lrwxrwxrwx 1 root root    15 Jan 12  2017 /usr/lib64/libffi.so.6 -> libffi.so.6.0.4
+   -rwxr-xr-x 1 root root 38792 Jan 12  2017 /usr/lib64/libffi.so.6.0.4
+
+If you do not have these packages installed on your |CL| system, install the
+sysadmin-basic software bundle using the :command:`swupd` command:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add sysadmin-basic
+
+.. note::
+
+   These instructions are for installing the MS Azure CLI 2.0 tools on a |CL|
+   system. If you are installing the CLI on another platform, follow the
+   instructions in the `MS Azure Install Azure CLI tutorial`_ for your
+   specific operating system.
+
+Install MS Azure CLI 2.0 on |CL|
+********************************
+
+#. To install the MS Azure CLI 2.0 on |CL|, use the :command:`curl` command as
+   follows:
+
+   .. code-block:: bash
+
+      curl -L https://aka.ms/InstallAzureCli | bash
+
+   If you get an error message from :command:`curl` related to the -L
+   parameter or an error message is generated that includes the text "Object
+   Moved", use the full URL instead of the aka.ms redirect address:
+
+   .. code-block:: bash
+
+      curl https://azurecliprod.blob.core.windows.net/install | bash
+
+#. The installation script begins and prompts you several times during
+   execution for information.
+
+   .. note::
+
+      The console output from the script displays your username instead of the
+      **[user]** variable shown on this tutorial.
+
+   .. code-block:: console
+
+      ===> In what directory would you like to place the install? (leave blank to use '/home/[user]/lib/azure-cli'):
+
+   Press the :kbd:`Enter` key to accept the default or you can chose another
+   directory to install the MS Azure CLI 2.0 tools into.
+
+   .. code-block:: console
+
+      ===> In what directory would you like to place the 'az' executable? (leave blank to use '/home/[user]/bin'):
+
+   Press the :kbd:`Enter` key to accept the default or you can chose another
+   directory to install the :command:`az` executable in.
+
+#. The installation downloads and builds all required tools and when complete
+   prompts you with:
+
+   .. code-block:: console
+
+      ===> Modify profile to update your $PATH and enable shell/tab completion now? (Y/n): Y
+
+   Type :kbd:`Y` and press the :kbd:`Enter` key to allow this modification.
+
+   .. code-block:: console
+
+      ===> Enter a path to an rc file to update (leave blank to use '/home/[user]/.bashrc'):
+
+   Press the :kbd:`Enter` key to accept the default or enter the pathname to
+   your :file:`.bashrc` file. The installation completes with the final output
+   shown below:
+
+   .. code-block:: console
+
+      -- Backed up '/home/[user].bashrc' to '/home/[user]/.bashrc.backup'
+      -- Tab completion set up complete.
+      -- If tab completion is not activated, verify that '/home/[user]/.bashrc' is sourced by your shell.
+      --
+      -- ** Run `exec -l $SHELL` to restart your shell. **
+      --
+      -- Installation successful.
+      -- Run the CLI with /home/[user]/bin/az --help
+
+#. The installation program finishes and you must restart your shell for
+   the changes to take effect. When the installation is successful, run the
+   following command to restart your shell.
+
+   .. code-block:: bash
+
+      exec -l $SHELL
+
+With the MS Azure CLI 2.0 executable successfully built and installed, run
+the :command:`az` command.
+
+.. code-block:: bash
+
+   az
+
+The output from the :command:`az` command is shown below:
+
+.. code-block:: console
+
+
+        /\
+       /  \    _____   _ _ __ ___
+      / /\ \  |_  / | | | \'__/ _ \
+     / ____ \  / /| |_| | | |  __/
+    /_/    \_\/___|\__,_|_|  \___|
+
+
+   Welcome to the cool new Azure CLI!
+
+   Here are the base commands:
+
+       account          : Manage Azure subscription information.
+       acr              : Manage Azure Container Registries.
+       acs              : Manage Azure Container Services.
+       ad               : Synchronize on-premises directories and manage Azure Active Directory
+                          resources.
+       advisor          : (PREVIEW) Manage Azure Advisor.
+       aks              : Manage Kubernetes clusters.
+       appservice       : Manage App Service plans.
+       backup           : Commands to manage Azure Backups.
+       batch            : Manage Azure Batch.
+       batchai          : Batch AI.
+       billing          : Manage Azure Billing.
+       cdn              : Manage Azure Content Delivery Networks (CDNs).
+       cloud            : Manage registered Azure clouds.
+       cognitiveservices: Manage Azure Cognitive Services accounts.
+       configure        : Display and manage the Azure CLI 2.0 configuration. This command is
+                          interactive.
+       consumption      : Manage consumption of Azure resources.
+       container        : (PREVIEW) Manage Azure Container Instances.
+       cosmosdb         : Manage Azure Cosmos DB database accounts.
+       disk             : Manage Azure Managed Disks.
+       dla              : (PREVIEW) Manage Data Lake Analytics accounts, jobs, and catalogs.
+       dls              : (PREVIEW) Manage Data Lake Store accounts and filesystems.
+       eventgrid        : Manage Azure Event Grid topics and subscriptions.
+       extension        : Manage and update CLI extensions.
+       feature          : Manage resource provider features.
+       feedback         : Loving or hating the CLI?  Let us know!
+       find             : Find Azure CLI commands.
+       functionapp      : Manage function apps.
+       group            : Manage resource groups and template deployments.
+       image            : Manage custom virtual machine images.
+       interactive      : Start interactive mode.
+       iot              : (PREVIEW) Manage Internet of Things (IoT) assets.
+       keyvault         : Safeguard and maintain control of keys, secrets, and certificates.
+       lab              : Manage Azure DevTest Labs.
+       lock             : Manage Azure locks.
+       login            : Log in to Azure.
+       logout           : Log out to remove access to Azure subscriptions.
+       managedapp       : Manage template solutions provided and maintained by Independent Software
+                          Vendors (ISVs).
+       monitor          : Manage the Azure Monitor Service.
+       mysql            : Manage Azure Database for MySQL servers.
+       network          : Manage Azure Network resources.
+       policy           : Manage resource policies.
+       postgres         : Manage Azure Database for PostgreSQL servers.
+       provider         : Manage resource providers.
+       redis            : Access to a secure, dedicated Redis cache for your Azure applications.
+       reservations     : Manage Azure Reservations.
+       resource         : Manage Azure resources.
+       role             : Manage user roles for access control with Azure Active Directory and service
+                          principals.
+       sf               : Manage and administer Azure Service Fabric clusters.
+       snapshot         : Manage point-in-time copies of managed disks, native blobs, or other
+                          snapshots.
+       sql              : Manage Azure SQL Databases and Data Warehouses.
+       storage          : Manage Azure Cloud Storage resources.
+       tag              : Manage resource tags.
+       vm               : Provision Linux or Windows virtual machines.
+       vmss             : Manage groupings of virtual machines in an Azure Virtual Machine Scale Set
+                          (VMSS).
+       webapp           : Manage web apps.
+
+Log into your Microsoft Azure account
+*************************************
+
+#. With the :command:`az` command properly installed and functional, login to
+   your MS Azure account using the :command:`az login` command shown below:
+
+   .. code-block:: bash
+
+      az login
+
+   The output from this command is:
+
+   .. code-block:: console
+
+      To sign in, use a web browser to open the page https://aka.ms/devicelogin and enter the code BQ9MG442B to authenticate.
+
+#. Open your browser and enter the page `https://aka.ms/devicelogin` as shown
+   in figure 1:
+
+   .. figure:: azure/figures/azure-1.png
+      :scale: 50 %
+      :alt: Microsoft Device Login
+
+      Figure 1: :guilabel:`Microsoft Device Login`
+
+#. Enter the code `BQ9MG442B` to authenticate your device as shown in figure
+   2. The code `BQ9MG442B` is a random authentication code generated for each
+   session login and will be different each time you log into MS Azure using
+   the :command:`az login` command.
+
+   .. figure:: azure/figures/azure-2.png
+      :scale: 50 %
+      :alt: Microsoft Device Login - Azure CLI
+
+      Figure 2: :guilabel:`Microsoft Device Login - Azure CLI`
+
+#. Once you enter the authentication code, the website changes to a screen to
+   enter your existing Microsoft Azure credentials.
+
+#. Log in with your existing MS Azure account credentials. Once complete, the
+   browser screen changes again as shown in figure 3. The screen shows you
+   have signed into the Microsoft Cross-platform Command Line Interface
+   application on your device and you can close the window.
+
+   .. figure:: azure/figures/azure-3.png
+      :scale: 50 %
+      :alt: Microsoft Azure Cross-platform CLI
+
+      Figure 3: :guilabel:`Microsoft Azure Cross-platform CLI`
+
+The MS Azure CLI 2.0 interface is now active using your existing MS Azure
+account credentials.
+
+Create a MS Azure resource group
+********************************
+
+To learn more about MS Azure resource groups, visit the
+`Azure Resource Manager overview`_ for an overview and detailed description
+of resources within MS Azure.
+
+#. To create our new resource group, run the :command:`az group create ...`
+   command shown below to create a resource group named `ClearResourceGroup`
+   using the `-n` parameter and locate it in the `westus` region using the
+   `-l` parameter.
+
+   .. code-block:: bash
+
+      az group create -n ClearResourceGroup -l westus
+
+#. When the command has completed, the output from this command is similar to
+   the following:
+
+   .. code-block:: console
+
+      {
+        "id": "/subscriptions/{unique-id}/resourceGroups/ClearResourceGroup",
+        "location": "westus",
+        "managedBy": null,
+        "name": "ClearResourceGroup",
+        "properties": {
+          "provisioningState": "Succeeded"
+        },
+        "tags": null
+      }
+
+Create and log into the |CL| virtual machine
+********************************************
+
+For this tutorial, we are using the |CL| Basic SKU for our VM.
+
+#. To locate the available |CL| Basic VM SKU images in the MS Azure
+   marketplace, run the :command:`az vm image ...` command:
+
+   .. code-block:: bash
+
+      az vm image list --offer clear-linux --sku basic --all --output table
+
+   This command may take some time to finish. The output lists all available
+   |CL| Basic images available in the Microsoft Azure marketplace as shown
+   below:
+
+   .. code-block:: console
+
+      Offer           Publisher            Sku               Urn                                                            Version
+      --------------  -------------------  ----------------  -------------------------------------------------------------  ---------
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:15780.0.0             15780.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:15960.0.0             15960.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:16050.0.0             16050.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:16150.0.0             16150.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:16500.0.0             16500.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:16810.0.0             16810.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:18080.0.0             18080.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:18620.0.0             18620.0.0
+      clear-linux-os  clear-linux-project  basic             clear-linux-project:clear-linux-os:basic:18860.0.0             18860.0.0
+
+   .. note::
+
+      The output list shows current offerings. New versions are added to the
+      MS Azure marketplace all the time. To reference the latest version of an
+      image, you can use the version label `latest` when specifying an image.
+
+#. The information shown in the `Urn` column lists the
+   `Publisher:Offer:Sku:Version` for each image available and this is the
+   information we want to create the |CL| Basic VM. Since we are creating a
+   |CL| Basic VM, highlight the `clear-linux-project:clear-linux-os:basic:`
+   string and copy it to your clipboard. Use the label
+   `latest` instead of referencing a specific version.
+
+#. Create the new |CL| Basic VM. Run the :command:`az vm create ...`
+   command using the URN `:clear-linux-project:clear-linux-os:basic:latest`
+   that we copied to the clipboard on the previous step.
+
+   .. code-block:: bash
+
+      az vm create --resource-group ClearResourceGroup --name ClearVM --image clear-linux-project:clear-linux-os:basic:latest --generate-ssh-keys
+
+   .. note::
+
+      If you have already defined your public/private SSH key pair and they
+      are stored in your :file:`$HOME/.ssh` directory, you do not need to
+      include the *--generate-ssh-keys* option.
+
+   Your output from this command will look similar to this output, where
+   [user] is your user name:
+
+   .. code-block:: console
+
+      SSH key files '/home/[user]/.ssh/id_rsa' and '/home/[user]/.ssh/id_rsa.pub' have been generated under ~/.ssh to allow SSH access to the VM. If using machines without permanent storage, back up your keys to a safe location.
+
+      running...
+
+      {
+        "fqdns": "",
+        "id": "/subscriptions/{unique-id}/resourceGroups/ClearResourceGroup/providers/Microsoft.Compute/virtualMachines/ClearVM",
+        "location": "westus",
+        "macAddress": "00-0D-3A-37-C7-59",
+        "powerState": "VM running",
+        "privateIpAddress": "10.0.0.4",
+        "publicIpAddress": "13.91.4.245",
+        "resourceGroup": "ClearResourceGroup",
+        "zones": ""
+      }
+
+   Take note of the public IP address from the output.
+
+#. Login into the new |CL| Basic VM, run the :command:`ssh` command with the
+   public IP address obtained from the previous step as shown:
+
+   .. code-block:: bash
+
+      ssh [user]@13.91.4.245
+
+   You may see the following message about the authenticity of the host. If
+   this appears, type `yes` to proceed connecting to your new |CL| VM.
+
+   .. code-block:: console
+
+      The authenticity of host '13.91.4.245 (13.91.4.245)' can't be established.
+      RSA key fingerprint is SHA256:{unique-number}.
+      Are you sure you want to continue connecting (yes/no)? yes
+      Warning: Permanently added '13.91.4.245' (RSA) to the list of known hosts.
+
+      [user]@ClearVM ~ $
+
+   You are now logged into your new |CL| VM as [user], where [user] is your
+   user name. To check which software bundles are included with
+   this VM image, run the :command:`sudo swupd bundle-list` command inside the VM:
+
+   .. code-block:: bash
+
+      sudo swupd bundle-list
+
+   The output shown should be similar to:
+
+   .. code-block:: console
+
+      swupd-client bundle list 3.14.1
+         Copyright (C) 2012-2017 Intel Corporation
+
+      bootloader
+      editors
+      kernel-hyperv
+      network-basic
+      openssh-server
+      os-cloudguest-azure
+      os-core
+      os-core-update
+      perl-basic
+      python-basic
+      python3-basic
+      storage-utils
+      sysadmin-basic
+      Current OS version: 19600
+
+   When you are finished using your new |CL| VM, type :command:`exit` to close
+   the :command:`SSH` terminal and logout.
+
+Stop and deallocate the |CL| VM and resources
+*********************************************
+
+When you finish using your new |CL| instance, you must stop the VM and
+deallocate the resources in your resource group. If you only stop a VM, the OS
+image shuts down but the resources associated with it in your resource group
+remain allocated and incurring charges. For instance, if you stop and then
+later start the VM using the :command:`az vm start...` without deallocating
+the resources, the IP address is retained and you can access the VM using that
+same IP address. To release the resources associated with the VM and stop
+incurring charges for them, you must deallocate the resources as well.
+
+#. At the command prompt, enter the :command:`az vm stop...` command as
+   follows:
+
+   .. code-block:: bash
+
+      az vm stop --resource-group ClearResourceGroup --name ClearVM
+
+   This will stop the VM and then output text similar to:
+
+   .. code-block:: console
+
+      {
+        "endTime": "2017-12-13T23:04:02.346676+00:00",
+        "error": null,
+        "name": "{unique-name}",
+        "startTime": "2017-12-13T23:03:59.018536+00:00",
+        "status": "Succeeded"
+      }
+
+#. Once the VM stops, deallocate the VM resources to stop incurring
+   charges for the |CL| instance. Enter the following command:
+
+   .. code-block:: console
+
+      az vm deallocate --resource-group ClearResourceGroup --name ClearVM
+
+**Congratulations!**
+
+You are up and running with |CL| on MS Azure using the Azure
+CLI 2.0 command line tools.
+
+Next steps
+**********
+
+To see use cases you can fulfill with your |CL| instance, visit our
+:ref:`tutorials <tutorials>` section.
+
+For additional information visit the |CL|
+`Azure Partner Mini Case Study`_ and the `Azure Partner Datasheet`_.
+
+To learn more about the MS Azure CLI 2.0 tool and options that are available,
+visit the `MS Azure documentation and tutorials`_ website.
+
+.. _`Azure Portal`:
+   https://portal.azure.com
+
+.. _`MS Azure free account`:
+   https://azure.microsoft.com/en-us/free/
+
+.. _`MS Azure documentation and tutorials`:
+   https://docs.microsoft.com/en-us/cli/azure/overview?view=azure-cli-latest
+
+.. _`MS Azure Install Azure CLI tutorial`:
+   https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest
+
+.. _`Azure Resource Manager overview`:
+   https://docs.microsoft.com/en-us/azure/azure-resource-manager/resource-group-overview
+
+.. _Azure Partner Datasheet:
+   http://download.microsoft.com/download/D/9/E/D9E22342-96D9-4455-BB15-99A1AF514DDD/Microsoft%20Azure%20Partner%20Datasheet%20-%20Intel%20Clear%20Linux.pdf
+
+.. _Azure Partner Mini Case Study:
+   http://download.microsoft.com/download/D/9/E/D9E22342-96D9-4455-BB15-99A1AF514DDD/Microsoft%20Azure%20Partner%20Mini%20Case%20Study%20-%20Intel%20Clear%20Linux.pdf
@@ -0,0 +1,106 @@
+.. _dars:
+
+Data Analytics Reference Stack
+##############################
+
+This tutorial shows you how to use the Data Analytics Reference Stack
+(DARS), and to optionally build your own images with the baseline Dockerfiles
+provided in the `DARS repository`_. Our assumption is that |CL-ATTR| is the
+host. However, any system that supports Docker\* containers can be used to
+follow these steps.
+
+.. contents::
+   :local:
+   :depth: 1
+
+The Data Analytics Reference Stack release
+******************************************
+
+The Data Analytics Reference Stack (DARS) provides developers and enterprises a straightforward, highly optimized software stack for storing and processing large amounts of data.  More detail is available on the `DARS architecture and performance benchmarks`_.
+
+The Data Analytics Reference Stack provides two pre-built Docker images, available on `Docker Hub`_:
+
+* A |CL|-derived `DARS with OpenBlas`_ stack optimized for `OpenBLAS`_
+* A |CL|-derived  `DARS with MKL`_ stack optimized for `MKL`_
+
+We recommend you view the latest component versions for each image in the
+:file:`README` found in the `DARS repository`_.  Because |CL| is a rolling
+distribution, the package version numbers in the |CL|-based containers may
+not be the latest released by |CL|.
+
+
+
+Using the Docker Images
+***********************
+
+To immediately start using the latest stable DARS images, pull directly
+from `Docker Hub`_. For this tutorial we'll use the `Dars with MKL`_ version of the stack.
+
+Once you have downloaded the image, you can run it with
+
+.. code-block:: bash
+
+   docker run -it --ulimit nofile=1000000:1000000 --name mkl <name of image>
+
+This will launch the image and drop you into a bash shell inside the
+container.  You will see output similar to the following:
+
+.. code-block:: console
+
+   root@fd5155b89857 /root # spark-shell
+   spark-shell
+   Config directory: /usr/share/defaults/spark/
+   Welcome to
+     ____              __
+    / __/__  ___ _____/ /__
+    _\ \/ _ \/ _ `/ __/  '_/
+   /___/ .__/\_,_/_/ /_/\_\   version 2.4.0
+      /_/
+
+   Using Scala version 2.12.7 (OpenJDK 64-Bit Server VM, Java 1.8.0-internal)
+   Type in expressions to have them evaluated.
+   Type :help for more information.
+
+   scala>
+
+The :command:`--ulimit nofile` parameter is currently required in order to
+increase the number of open files opened at certain point by the spark
+engine.
+
+Building DARS Images
+********************
+
+If you choose to build your own DARS container images, you can customize
+them as needed. Use the provided Dockerfile as a baseline. To construct
+images with |CL|, start with a |CL| development platform that
+has the :command:`containers-basic-dev` bundle installed. Learn more about
+bundles and installing them by using :ref:`swupd-guide`.
+
+First, clone the `DARS repository`_ from GitHub.
+
+.. code-block:: bash
+
+   git clone https://github.com/clearlinux/dockerfiles/tree/master/stacks/dars -b master
+
+Then, inside the DARS directory, run :command:`make` to build OpenBLAS and
+MKL images, and run :command:`make baseline` to build the baseline CentOS
+image. Depending on the system, it may take a while to finish building.
+Once completed, check the resulting images with :command:`Docker`
+
+.. code-block:: bash
+
+   docker images | grep dars
+
+You can use any of the resulting images to launch fully functional
+containers.  If you need to customize the containers, you can edit the
+provided :file:`Dockerfile`.
+
+
+.. _DARS repository:  https://github.com/clearlinux/dockerfiles/tree/master/stacks/dars
+.. _Docker Hub: https://hub.docker.com/
+.. _OpenBLAS: http://www.openblas.net/
+.. _MKL: https://software.intel.com/en-us/mkl
+.. _CentOS: https://www.centos.org/
+.. _DARS with OpenBLAS: https://hub.docker.com/r/clearlinux/stacks-dars-openblas/
+.. _DARS with MKL: https://hub.docker.com/r/clearlinux/stacks-dars-mkl/
+.. _DARS architecture and performance benchmarks: https://clearlinux.org/stacks/data-analytics-stack-v1
@@ -0,0 +1,446 @@
+.. _dlrs:
+
+Deep Learning Reference Stack
+#############################
+
+This tutorial describes how to run benchmarking workloads for TensorFlow\*,
+PyTorch\*, and Kubeflow in |CL-ATTR| using the Deep Learning Reference Stack.
+
+
+.. contents::
+   :local:
+   :depth: 1
+
+Overview
+********
+
+We created the Deep Learning Reference Stack to help AI developers deliver the
+best experience on Intel® Architecture. This stack reduces complexity common
+with deep learning software components, provides flexibility for customized
+solutions, and enables you to quickly prototype and deploy Deep Learning
+workloads. Use this tutorial to run benchmarking workloads on your solution.
+
+The Deep Learning Reference Stack is available in the following versions:
+
+* `Intel MKL-DNN-VNNI`_, which is optimized using Intel® Math Kernel Library
+  for Deep Neural Networks (Intel® MKL-DNN) primitives and introduces support
+  for Intel® AVX-512 Vector Neural Network Instructions (VNNI).
+* `Intel MKL-DNN`_, which includes the TensorFlow framework optimized using
+  Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) primitives.
+* `Eigen`_, which includes `TensorFlow`_ optimized for Intel® architecture.
+* `PyTorch with OpenBLAS`_, which includes PyTorch with OpenBlas.
+* `PyTorch with Intel MKL-DNN`_, which includes PyTorch optimized using Intel®
+  Math Kernel Library (Intel® MKL) and Intel MKL-DNN.
+
+
+.. note::
+
+   To take advantage of the Intel® AVX-512 and VNNI functionality with the Deep
+   Learning Reference Stack, you must use the following hardware:
+
+   * Intel® AVX-512 images require an Intel® Xeon® Scalable Platform
+   * VNNI requires a 2nd generation Intel® Xeon® Scalable Platform
+
+
+Stack features
+==============
+
+* Deep Learning Reference Stack `V3.0 release announcement`_.
+* Deep Learning Reference Stack v2.0 including current `PyTorch benchmark results`_.
+* Deep Learning Reference Stack v1.0 including current `TensorFlow benchmark results`_.
+* `Release notes on Github\*`_ for the latest release of Deep Learning Reference Stack.
+
+.. note::
+
+   Performance test results for the Deep Learning Reference Stack were
+   obtained using `runc` as the runtime.
+
+Prerequisites
+=============
+
+* :ref:`Install <bare-metal-install-desktop>` |CL| on your host system.
+* :command:`containers-basic` bundle
+* :command:`cloud-native-basic` bundle
+
+In |CL|, :command:`containers-basic` includes Docker\*, which is required for
+TensorFlow and PyTorch benchmarking. Use the :command:`swupd` utility to
+check if :command:`containers-basic` and :command:`cloud-native-basic` are present:
+
+.. code-block:: bash
+
+   sudo swupd bundle-list
+
+To install the :command:`containers-basic` or :command:`cloud-native-basic` bundles, enter:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add containers-basic cloud-native-basic
+
+Docker is not started upon installation of the :command:`containers-basic`
+bundle. To start Docker, enter:
+
+.. code-block:: bash
+
+   sudo systemctl start docker
+
+To ensure that Kubernetes is correctly installed and configured, follow the
+instructions in :ref:`kubernetes`.
+
+Version compatibility
+=====================
+
+We validated these steps against the following software package versions:
+
+* |CL| 26240 (Lower version not supported.)
+* Docker 18.06.1
+* Kubernetes 1.11.3
+* Go 1.11.12
+
+TensorFlow single and multi-node benchmarks
+*******************************************
+
+This section describes running the `TensorFlow benchmarks`_ in single node.
+For multi-node testing, replicate these steps for each node. These steps
+provide a template to run other benchmarks, provided that they can invoke
+TensorFlow.
+
+#. Download either the `Eigen`_ or the `Intel MKL-DNN`_ Docker image
+   from `Docker Hub`_.
+
+#. Run the image with Docker:
+
+   .. code-block:: bash
+
+      docker run --name <image name>  --rm -i -t <clearlinux/
+      stacks-dlrs-TYPE> bash
+
+   .. note::
+
+      Launching the Docker image with the :command:`-i` argument starts
+      interactive mode within the container. Enter the following commands in
+      the running container.
+
+#. Clone the benchmark repository in the container:
+
+   .. code-block:: bash
+
+      git clone http://github.com/tensorflow/benchmarks -b cnn_tf_v1.12_compatible
+
+#. Execute the benchmark script:
+
+   .. code-block:: bash
+
+      python benchmarks/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --device=cpu --model=resnet50 --data_format=NHWC
+
+.. note::
+
+   You can replace the model with one of your choice supported by the
+   TensorFlow benchmarks.
+
+PyTorch single and multi-node benchmarks
+****************************************
+
+This section describes running the `PyTorch benchmarks`_ for Caffe2 in
+single node.
+
+#. Download either the `PyTorch with OpenBLAS`_ or the `PyTorch with Intel
+   MKL-DNN`_ Docker image from `Docker Hub`_.
+
+#. Run the image with Docker:
+
+   .. code-block:: bash
+
+      docker run --name <image name>  --rm -i -t <clearlinux/stacks-dlrs-TYPE> bash
+
+   .. note::
+
+      Launching the Docker image with the :command:`-i` argument starts
+      interactive mode within the container. Enter the following commands in
+      the running container.
+
+#. Clone the benchmark repository:
+
+   .. code-block:: bash
+
+      git clone https://github.com/pytorch/pytorch.git
+
+#. Execute the benchmark script:
+
+   .. code-block:: bash
+
+       cd pytorch/caffe2/python
+       python convnet_benchmarks.py --batch_size 32 \
+                             --cpu \
+                             --model AlexNet
+
+Kubeflow multi-node benchmarks
+******************************
+
+The benchmark workload runs in a Kubernetes cluster. The tutorial uses
+`Kubeflow`_ for the Machine Learning workload deployment on three nodes.
+
+Kubernetes setup
+================
+
+Follow the instructions in the :ref:`kubernetes` tutorial to get set up on
+|CL|. The Kubernetes community also has
+`instructions for creating a cluster`_.
+
+Kubernetes networking
+=====================
+
+We used `flannel`_ as the network provider for these tests. If you
+prefer a different network layer, refer to the Kubernetes
+`networking documentation`_ for setup.
+
+Images
+======
+
+You must add `launcher.py` to the Docker image to include the Deep
+Learning Reference Stack and put the benchmarks repo in the correct
+location. From the Docker image, run the following:
+
+.. code-block:: bash
+
+   mkdir -p /opt
+   git clone https://github.com/tensorflow/benchmarks.git /opt/tf-benchmarks
+   cp launcher.py /opt
+   chmod u+x /opt/*
+
+Your entry point becomes: :file:`/opt/launcher.py`
+
+This builds an image that can be consumed directly by TFJob from Kubeflow.
+
+ksonnet\*
+=========
+
+Kubeflow uses ksonnet\* to manage deployments, so you must install it
+before setting up Kubeflow.
+
+ksonnet was added to the :command:`cloud-native-basic` bundle in |CL| version 27550. If
+you are using an older |CL| version (not recommended), you must manually
+install ksonnet as described below.
+
+On |CL|, follow these steps:
+
+.. code-block:: bash
+
+   swupd bundle-add go-basic-dev
+   export GOPATH=$HOME/go
+   export PATH=$PATH:$GOPATH/bin
+   go get github.com/ksonnet/ksonnet
+   cd $GOPATH/src/github.com/ksonnet/ksonnet
+   make install
+
+After the ksonnet installation is complete, ensure that binary `ks` is
+accessible across the environment.
+
+Kubeflow
+========
+
+Once you have Kubernetes running on your nodes, set up `Kubeflow`_ by
+following these instructions from the `quick start guide`_.
+
+.. code-block:: bash
+
+   export KUBEFLOW_SRC=$HOME/kflow
+   export KUBEFLOW_TAG="v0.4.1"
+   export KFAPP="kflow_app"
+   export K8S_NAMESPACE="kubeflow"
+
+   mkdir ${KUBEFLOW_SRC}
+   cd ${KUBEFLOW_SRC}
+   ks init ${KFAPP}
+   cd ${KFAPP}
+   ks registry add kubeflow github.com/kubeflow/kubeflow/tree/${KUBEFLOW_TAG}/kubeflow
+   ks pkg install kubeflow/common
+   ks pkg install kubeflow/tf-training
+
+Next, deploy the primary package for our purposes: tf-job-operator.
+
+.. code-block:: bash
+
+   ks env rm default
+   kubectl create namespace ${K8S_NAMESPACE}
+   ks env add default --namespace "${K8S_NAMESPACE}"
+   ks generate tf-job-operator tf-job-operator
+   ks apply default -c tf-job-operator
+
+This creates the CustomResourceDefinition (CRD) endpoint to launch a TFJob.
+
+Run a TFJob
+===========
+
+#. Select this link for the `ksonnet registries for deploying TFJobs`_.
+
+#. Install the TFJob components as follows:
+
+   .. code-block:: bash
+
+      ks registry add dlrs-tfjob github.com/clearlinux/dockerfiles/tree/master/stacks/dlrs/kubeflow/dlrs-tfjob
+
+      ks pkg install dlrs-tfjob/dlrs-bench
+
+#. Export the image name to use for the deployment:
+
+   .. code-block:: bash
+
+      export DLRS_IMAGE=<docker_name>
+
+   .. note::
+
+      Replace <docker_name> with the image name you specified in previous steps.
+
+#. Generate Kubernetes manifests for the workloads and apply them using these commands:
+
+   .. code-block:: bash
+
+      ks generate dlrs-resnet50 dlrsresnet50 --name=dlrsresnet50 --image=${DLRS_IMAGE}
+      ks generate dlrs-alexnet dlrsalexnet --name=dlrsalexnet --image=${DLRS_IMAGE}
+      ks apply default -c dlrsresnet50
+      ks apply default -c dlrsalexnet
+
+This replicates and deploys three test setups in your Kubernetes cluster.
+
+Results of running this tutorial
+================================
+
+You must parse the logs of the Kubernetes pod to retrieve performance
+data. The pods will still exist post-completion and will be in
+‘Completed’ state. You can get the logs from any of the pods to inspect the
+benchmark results. More information about `Kubernetes logging`_ is available
+from the Kubernetes community.
+
+Use Jupyter Notebook
+********************
+
+This example uses the `PyTorch with OpenBLAS`_ container image. After it is
+downloaded, run the Docker image with :command:`-p` to specify the shared port
+between the container and the host. This example uses port 8888.
+
+.. code-block:: bash
+
+   docker run --name pytorchtest --rm -i -t -p 8888:8888 clearlinux/stacks-pytorch-oss bash
+
+After you start the container, launch the Jupyter Notebook. This
+command is executed inside the container image.
+
+.. code-block:: bash
+
+   jupyter notebook --ip 0.0.0.0 --no-browser --allow-root
+
+After the notebook has loaded, you will see output similar to the following:
+
+.. code-block:: console
+
+   To access the notebook, open this file in a browser: file:///.local/share/jupyter/runtime/nbserver-16-open.html
+   Or copy and paste one of these URLs:
+   http://(846e526765e3 or 127.0.0.1):8888/?token=6357dbd072bea7287c5f0b85d31d70df344f5d8843fbfa09
+
+From your host system, or any system that can access the host's IP address,
+start a web browser with the following. If you are not running the browser on
+the host system, replace :command:`127.0.0.1` with the IP address of the host.
+
+.. code-block:: bash
+
+  http://127.0.0.1:8888/?token=6357dbd072bea7287c5f0b85d31d70df344f5d8843fbfa09
+
+Your browser displays the following:
+
+.. figure:: figures/dlrs-fig-1.png
+   :scale: 50 %
+   :alt: Jupyter Notebook
+
+Figure 1: :guilabel:`Jupyter Notebook`
+
+
+To create a new notebook, click :guilabel:`New` and select :guilabel:`Python 3`.
+
+.. figure:: figures/dlrs-fig-2.png
+   :scale: 50%
+   :alt: Create a new notebook
+
+Figure 2: Create a new notebook
+
+A new, blank notebook is displayed, with a cell ready for input.
+
+.. figure:: figures/dlrs-fig-3.png
+   :scale: 50%
+   :alt: New blank notebook
+
+
+To verify that PyTorch is working, copy the following snippet into the blank cell, and run the cell.
+
+.. code-block:: console
+
+   from __future__ import print_function
+   import torch
+   x = torch.rand(5, 3)
+   print(x)
+
+.. figure:: figures/dlrs-fig-4.png
+   :scale: 50%
+   :alt: Sample code snippet
+
+When you run the cell, your output will look something like this:
+
+.. figure:: figures/dlrs-fig-5.png
+   :scale: 50%
+   :alt: code output
+
+You can continue working in this notebook, or you can download existing
+notebooks to take advantage of the Deep Learning Reference Stack's optimized
+deep learning frameworks. Refer to `Jupyter Notebook`_ for details.
+
+Related topics
+**************
+
+* Deep Learning Reference Stack `V3.0 release announcement`_
+* `TensorFlow benchmarks`_
+* `PyTorch benchmarks`_
+* `Kubeflow`_
+* :ref:`kubernetes` tutorial
+* `Jupyter Notebook`_
+
+
+.. _TensorFlow: https://www.tensorflow.org/
+
+.. _Kubeflow: https://www.kubeflow.org/
+
+.. _Docker Hub: https://hub.docker.com/
+
+.. _TensorFlow benchmarks: https://www.tensorflow.org/guide/performance/benchmarks
+
+.. _PyTorch benchmarks: https://github.com/pytorch/pytorch/blob/master/caffe2/python/convnet_benchmarks.py
+
+.. _instructions for creating a cluster: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/
+
+.. _flannel: https://github.com/coreos/flannel
+
+.. _networking documentation: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/#pod-network
+
+.. _quick start guide: https://www.kubeflow.org/docs/started/getting-started/
+
+.. _Eigen: https://hub.docker.com/r/clearlinux/stacks-dlrs-oss/
+
+.. _Intel MKL-DNN: https://hub.docker.com/r/clearlinux/stacks-dlrs-mkl/
+
+.. _PyTorch with OpenBLAS: https://hub.docker.com/r/clearlinux/stacks-pytorch-oss
+
+.. _PyTorch with Intel MKL-DNN: https://hub.docker.com/r/clearlinux/stacks-pytorch-mkl
+
+.. _Intel MKL-DNN-VNNI: https://hub.docker.com/r/clearlinux/stacks-dlrs-mkl-vnni
+
+.. _V3.0 release announcement:  https://clearlinux.org/stacks/deep-learning-reference-stack-v3
+
+.. _ksonnet registries for deploying TFJobs: https://github.com/clearlinux/dockerfiles/tree/master/stacks/dlrs/kubeflow/dlrs-tfjob
+
+.. _Kubernetes logging: https://kubernetes.io/docs/concepts/cluster-administration/logging/
+
+.. _TensorFlow benchmark results: https://clearlinux.org/stacks/deep-learning-reference-stack
+
+.. _PyTorch benchmark results: https://clearlinux.org/stacks/deep-learning-reference-stack-pytorch
+
+.. _Jupyter Notebook: https://jupyter.org/
+
+.. _Release notes on Github\*: https://github.com/clearlinux/dockerfiles/blob/master/stacks/dlrs/releasenote.md
@@ -0,0 +1,247 @@
+.. _docker:
+
+Run Docker\* on |CL-ATTR|
+#########################
+
+|CL-ATTR| supports multiple containerization platforms, including a Docker\*
+solution. |CL| has many `unique features`_ including a minimal default
+installation, which makes it compelling to use as a host for container
+workloads, management, and orchestration.
+
+This tutorial covers:
+
+.. contents:: :local:
+   :depth: 1
+
+.. note::
+
+   This tutorial focuses on the installaton of the Docker ecosystem.
+   If you want to use |CL| as a Docker container image, refer to the
+   official |CL| container image
+   `published on Docker* Hub <https://hub.docker.com/_/clearlinux/>`_
+   and our guide to :ref:`custom-clear-container`.
+
+Prerequisites
+*************
+
+This tutorial assumes you have installed |CL| on your host system.
+For detailed instructions on installing |CL| on a bare metal system, follow
+the :ref:`bare metal installation instructions<bare-metal-install-server>`.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+Additionally, you should have:
+
+* A basic understanding of Linux and Docker.
+
+* |CL| environment that has transparent network access to the Internet.
+  If you are behind a HTTP proxy server, in a corporate setting for example,
+  please refer to the `Docker proxy instructions`_ .
+
+Install the containers-basic bundle
+***********************************
+
+Software in |CL| is offered in the form of `bundles`_ to provide a
+complete function. The *containers-basic* provides all the required software
+packages to run Docker images as containers.
+
+#. First, install the *containers-basic* bundle by running this
+   :command:`swupd` command:
+
+   .. code-block:: bash
+
+      sudo swupd bundle-add containers-basic
+
+#. Start the Docker daemon through systemd manager by running this command:
+
+   .. code-block:: bash
+
+      sudo systemctl start docker
+
+   If you want Docker to start automatically on boot, enable the
+   systemd service by running this command:
+
+   .. code-block:: bash
+
+      sudo systemctl enable docker
+
+#. Finally, verify :command:`docker` has been installed by running this
+   command and checking the version output for both *client* and *server*:
+
+   .. code-block:: bash
+
+      sudo docker version
+
+Congratulations! At this point, you have a working installation of Docker
+on |CL|. You are ready to start using container images on your system.
+
+Integration with Kata Containers (optional)
+********************************************
+
+`Kata Containers`_, is an open source project aiming to increase security
+of containers by using a hardware-backed virtual machine container runtime
+rather than software namespace containers that are provided by the standard
+Docker *runc* runtime.
+
+|CL| provides easy integration of the *kata-runtime* with Docker.
+More information on installing and using  the *kata-runtime* may be found at :ref:`kata`.
+
+
+.. note::
+
+   The proceeding sections of this tutorial are standard to Docker setup
+   and configuration. If you are familiar with Docker basics, you do not
+   need to continue reading. The following sections are provided here for
+   sake of completeness.
+
+.. _additional-docker-configuration:
+
+Additional Docker configuration
+*******************************
+
+Perform additional Docker daemon configuration via a configuration file
+typically located at :file:`/etc/docker/daemon.json`. |CL| features a
+`stateless system`_  so the configuration file :file:`daemon.json` does *NOT*
+exist by default.
+
+#. Create the :file:`daemon.json` by running this command:
+
+   .. code-block:: bash
+
+      sudo touch /etc/docker/daemon.json
+
+   .. note::
+
+      Refer to the `Docker documentation on daemon configuration`_ for the
+      full list of available configuration options and examples.
+
+#. For production systems, we follow Docker's recommendation to use the
+   `OverlayFS storage driver`_ `overlay2`, shown below:
+
+   .. code-block:: json
+
+      {
+         "storage-driver": "overlay2"
+      }
+
+   .. note::
+
+      A testing version is found in `Docker Device Mapper storage driver`_.
+      If using this storage driver, a warning message may appear: "usage of
+      loopback devices is strongly discouraged for production use".
+
+#. Save and close :file:`daemon.json`.
+
+#. Once you've made any required changes, be sure to restart the
+   Docker daemon through systemd manager by running this command:
+
+   .. code-block:: bash
+
+      sudo systemctl restart docker
+
+Pulling and running an image from Docker Hub
+********************************************
+
+`Docker Hub`_ is a publically available container image repository which
+comes preconfigured with Docker. In the example below we will pull and run
+an the official Docker image for nginx, an open source reverse proxy server.
+
+#. First, pull a container image from Docker Hub using the
+   :command:`docker pull` command. Download the latest nginx Docker
+   container image by running this command:
+
+   .. code-block:: bash
+
+      sudo docker pull nginx
+
+#. Create and launch a new container using the :command:`docker run`
+   command. Launch a nginx container by running this command:
+
+   .. code-block:: bash
+
+      sudo docker run --name test-nginx -d -p 8080:80 nginx
+
+   .. note::
+
+      Below is an explanation of switches used in the command above. For
+      detailed :command:`docker run` switches and syntax, refer to the
+      `Docker Documentation`_ .
+
+      * The *--name* switch lets you provide a friendly name to
+        target the container for future operations
+
+      * The *-d* switch launches the container in the background
+
+      * The *-p* switch allows the container's HTTP port (80) to be
+        accessible from the |CL| host on port 8080
+
+#. You can access the Welcome to Nginx! splash page running in the container
+   by browsing to \http://127.0.0.1:8080 or by running this :command:`curl`
+   command from your |CL| machine:
+
+   .. code-block:: bash
+
+      curl 127.0.0.1:8080
+
+#. Finally, stop and delete the nginx container by running the
+   :command:`docker stop` and :command:`docker rm` commands.
+
+   .. code-block:: bash
+
+      sudo docker stop test-nginx
+      sudo docker rm test-nginx
+
+Congratulations! At this point, you have successfully pulled a nginx
+container image from `Docker Hub`_ and have run an example container.
+
+Creating a Docker swarm cluster
+*******************************
+
+Clusters of Docker hosts are referred to as *swarms*.
+
+The process in this tutorial can be repeated to install Docker on multiple
+|CL| hosts with the intent to form a Docker swarm cluster.
+
+The `Docker documentation on swarm key concepts`_ and
+`Docker documentation on creating a swarm`_ can be referenced
+for further instructions on setting up a swarm.
+
+Related topics
+**************
+
+* `Docker Home`_
+* `Docker Documentation`_
+* `Docker Hub`_
+* `Kata Containers`_
+
+.. _unique features: https://clearlinux.org/features
+
+.. _Docker proxy instructions: https://docs.docker.com/config/daemon/systemd/#httphttps-proxy
+
+.. _bundles: https://clearlinux.org/documentation/clear-linux/concepts/bundles-about#related-concepts
+
+.. _stateless system: https://clearlinux.org/features/stateless
+
+.. _Docker documentation on daemon configuration: https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file
+
+.. _Kata Containers: https://katacontainers.io/
+
+.. _Docker Home: https://www.docker.com/
+
+.. _Docker Documentation: https://docs.docker.com/
+
+.. _Docker Hub: https://hub.docker.com/
+
+.. _Docker documentation on swarm key concepts: https://docs.docker.com/engine/swarm/key-concepts/
+
+.. _Docker documentation on creating a swarm: https://docs.docker.com/engine/swarm/swarm-tutorial/create-swarm/
+
+.. _Configure direct lvm mode for production: https://docs.docker.com/storage/storagedriver/device-mapper-driver/
+
+.. _OverlayFS storage driver: https://docs.docker.com/storage/storagedriver/overlayfs-driver/
+
+.. _Docker Device Mapper storage driver: https://docs.docker.com/storage/storagedriver/device-mapper-driver/
@@ -0,0 +1,103 @@
+.. _flatpak:
+
+Use Flatpak\* to install applications on |CL-ATTR|
+##################################################
+
+This tutorial provides all the required steps to install Flatpak as well as
+downloading, installing, and running LibreOffice\* on |CL-ATTR|.
+
+Please visit the `Flatpak website`_ for more information about Flatpak and
+how to use it. You can also `download it here`_.
+
+Before you begin
+****************
+
+This tutorial assumes you have installed |CL| on your host system.
+For detailed instructions on installing |CL| on a bare metal system, visit
+our :ref:`bare metal installation guide <bare-metal-install-desktop>`.
+
+Install Flatpak on your host system
+===================================
+
+Flatpak is included as part of the bundle `desktop`. To install the
+application, log in to your user account and enter the following command:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add desktop
+
+Install and run the LibreOffice Flatpak image
+=============================================
+
+Application developers have the option to bundle their applications using
+Flatpak to allow the installation of a single distribution of their
+application on different distributions of Linux, including |CL|.
+Flatpak provides a `list of applications`_ available through Flathub.
+
+|CL| enables the Flathub repository by default.
+
+
+Installing using gnome software
+-------------------------------
+
+All you need to do is to launch `gnome software`, search for the LibreOffice
+app, and click the install button.
+
+.. figure:: figures/01-install-libreoffice.gif
+   :alt: install libreoffice step by step
+
+   Figure 1: Installing LibreOffice using gnome-software
+
+
+
+Installing using the command line
+---------------------------------
+
+Open the `gnome-terminal` and type the following command to install the
+LibreOffice app.
+
+.. code-block:: bash
+
+   flatpak install --user flathub org.libreoffice.LibreOffice
+   Installing in user:
+   org.libreoffice.LibreOffice/x86_64/stable        flathub 2aff77bd5cf1
+     permissions: ipc, network, pulseaudio, wayland, x11, dri
+     file access: host, xdg-run/dconf
+     dbus access: ca.desrt.dconf, org.gtk.vfs.*
+     dbus ownership: org.libreoffice.LibreOfficeIpc0
+   org.libreoffice.LibreOffice.Locale/x86_64/stable flathub 924157b3b009
+   Is this ok [y/n]: y
+   Installing for user: org.libreoffice.LibreOffice/x86_64/stable from flathub
+   [####################] 403 metadata, 4661 content objects fetched; 222574 KiB transferred in 99 seconds
+   Now at 2aff77bd5cf1.
+   Installing for user: org.libreoffice.LibreOffice.Locale/x86_64/stable from flathub
+   [####################] 10 metadata, 71 content objects fetched; 1013 KiB transferred in 3 seconds
+   Now at 924157b3b009.
+
+
+Launch LibreOffice
+==================
+A new set of icons will appear in your Gnome applications list titled :guilabel:`LibreOffice.` To
+execute the application, highlight the application and click on the :guilabel:`LibreOffice` icon.
+LibreOffice will start normally.
+
+.. figure:: figures/02-openlibreoffice.gif
+   :alt: Opening LibreOffice app
+
+   Figure 2: Select :guilabel:`LibreOffice` app
+
+Using the command line
+----------------------
+
+.. code-block:: bash
+
+   flatpak run org.libreoffice.LibreOffice
+
+
+.. _Flatpak website: http://flatpak.org
+
+.. _list of applications: http://flatpak.org/apps.html
+
+.. _download it here:
+   http://download.documentfoundation.org/libreoffice/flatpak/latest/LibreOffice.flatpak
+
@@ -0,0 +1,273 @@
+.. _fmv:
+
+Use the function multi-version patch generator
+##############################################
+
+CPU architectures often gain interesting new instructions as they evolve but
+application developers find it difficult to take advantage of those
+instructions. The reluctance to lose backward-compatibility is one of the
+main roadblocks slowing developers from using advancements in newer computing
+architectures. :abbr:`FMV (Function Multi-Versioning)`, which first appeared
+in `GCC`_ 4.8, is a way to have multiple implementations of a function, each
+using a different architecture specialized instruction-set extensions. GCC
+6 introduces changes to FMV to make it even easier to bring architecture-
+based optimizations to the application code.
+
+In this tutorial we will use FMV on general code and on
+:abbr:`FFT (Fast Fourier Transform)` library code. Upon completing the
+tutorial, you will be able to use this technology on your code and use the
+libraries to deploy architecture-based optimizations to your application code.
+
+Install and configure a |CL| host on bare metal
+***********************************************
+First, follow our guide to :ref:`bare-metal-install-desktop`. Once the bare
+metal installation and initial configuration are complete, add the
+`desktop-dev` bundle to the system. `desktop-dev`: contains the necessary
+development tools like GCC and Perl\*.
+
+To install the bundles, run the following command in the :file:`$HOME`
+directory:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add desktop-dev
+
+Detect loop vectorization candidates
+************************************
+
+Now, we need to detect the loop vectorization candidates to be cloned for
+multiple platforms with FMV. As an example, we will use the following
+simple C code:
+
+.. code-block:: c
+   :linenos:
+
+    #include <stdio.h>
+    #include <stdlib.h>
+    #include <sys/time.h>
+    #define MAX 1000000
+
+    int a[256], b[256], c[256];
+
+    void foo(){
+        int i,x;
+        for (x=0; x<MAX; x++){
+            for (i=0; i<256; i++){
+                a[i] = b[i] + c[i];
+            }
+        }
+    }
+
+
+    int main(){
+        foo();
+        return 0;
+    }
+
+Save the example code as :file:`example.c` in the current directory and build
+with the following flags:
+
+.. code-block:: bash
+
+        gcc -O3  -fopt-info-vec  example.c -o example
+
+The build generates the following output:
+
+.. code-block:: console
+
+    example.c:11:9: note: loop vectorized
+    example.c:11:9: note: loop vectorized
+
+The output shows that line 11 is a good candidate for vectorization:
+
+.. code-block:: c
+
+    for (i=0; i<256; i++){
+        a[i] = b[i] + c[i];
+
+Generate the FMV patch
+**********************
+
+To generate the FMV patch with the `make-fmv-patch`_ project, we
+must clone the project and generate a log file with the loop vectorized
+information:
+
+.. code-block:: bash
+
+        git clone https://github.com/clearlinux/make-fmv-patch.git
+        gcc -O3  -fopt-info-vec  example.c -o example &> log
+
+To generate the patch files, execute:
+
+.. code-block:: bash
+
+        perl ./make-fmv-patch/make-fmv-patch.pl log .
+
+The :file:`make-fmv-patch.pl` script takes two arguments: `<buildlog>` and
+`<sourcecode>`. Replace `<buildlog>` and `<sourcecode>` with the proper
+values and execute:
+
+.. code-block:: bash
+
+        perl make-fmv-patch.pl <buildlog> <sourcecode>
+
+The command generates the following :file:`example.c.patch` patch:
+
+.. code-block:: console
+
+    --- ./example.c 2017-09-27 16:05:42.279505430 +0000
+    +++ ./example.c~    2017-09-27 16:19:11.691544026 +0000
+    @@ -5,6 +5,7 @@
+
+     int a[256], b[256], c[256];
+
+    +__attribute__((target_clones("avx2","arch=atom","default")))
+     void foo(){
+         int i,x;
+         for (x=0; x<MAX; x++){
+
+We recommend you use the :file:`make-fmv-patch` script to add the attribute
+generating the target clones on the function `foo`. Thus, we can have the
+following code:
+
+.. code-block:: c
+
+    #include <stdio.h>
+    #include <stdlib.h>
+    #include <sys/time.h>
+    #define MAX 1000000
+
+    int a[256], b[256], c[256];
+
+    __attribute__((target_clones("avx2","arch=atom","default")))
+    void foo(){
+        int i,x;
+        for (x=0; x<MAX; x++){
+            for (i=0; i<256; i++){
+                a[i] = b[i] + c[i];
+            }
+        }
+    }
+
+
+    int main(){
+        foo();
+        return 0;
+    }
+
+Changing the value of the `$avx2` variable, we can change the target
+clones when adding the patches or in the :file:`make-fmv-patch.pl` script:
+
+.. code-block:: perl
+
+    my $avx2 = '__attribute__((target_clones("avx2","arch=atom","default")))'."\n";
+
+Compile the code again with FMV and add the option to analyze the `objdump`
+log:
+
+.. code-block:: bash
+
+    gcc -O3 example.c -o example -g
+    objdump -S example | less
+
+You can see the multiple clones of the `foo` function:
+
+.. code-block:: console
+
+    foo
+    foo.avx2.0
+    foo.arch_atom.1
+
+The cloned functions use AVX2 registers and vectorized instructions. To
+verify, enter the following commands:
+
+::
+
+    vpaddd (%r8,%rax,1),%ymm0,%ymm0
+    vmovdqu %ymm0,(%rcx,%rax,1)
+
+FTT project example
+*******************
+
+To follow the same approach with a package like FFT, we must use the
+`-fopt-info-vec` flag to get a build log file similar to:
+
+.. code-block:: bash
+
+    ~/make-fmv-patch/make-fmv-patch.pl results/build.log fftw-3.3.6-pl2/
+
+    patching fftw-3.3.6-pl2/libbench2/verify-lib.c @ lines (36 114 151 162 173 195 215 284)
+    patching fftw-3.3.6-pl2/tools/fftw-wisdom.c @ lines (150)
+    patching fftw-3.3.6-pl2/libbench2/speed.c @ lines (26)
+    patching fftw-3.3.6-pl2/tests/bench.c @ lines (27)
+    patching fftw-3.3.6-pl2/libbench2/util.c @ lines (181)
+    patching fftw-3.3.6-pl2/libbench2/problem.c @ lines (229)
+    patching fftw-3.3.6-pl2/tests/fftw-bench.c @ lines (101 147 162 249)
+    patching fftw-3.3.6-pl2/libbench2/mp.c @ lines (79 190 215)
+    patching fftw-3.3.6-pl2/libbench2/caset.c @ lines (5)
+    patching fftw-3.3.6-pl2/libbench2/verify-r2r.c @ lines (44 187 197 207 316 333 723)
+
+For example, the :file:`fftw-3.3.6-pl2/tools/fftw-wisdom.c.patch` file
+generates the following patches:
+
+.. code-block:: diff
+   :linenos:
+
+       --- fftw-3.3.6-pl2/libbench2/verify-lib.c   2017-01-27 21:08:13.000000000 +0000
+       +++ fftw-3.3.6-pl2/libbench2/verify-lib.c~  2017-09-27 17:49:21.913802006 +0000
+       @@ -33,6 +33,7 @@
+
+        double dmax(double x, double y) { return (x > y) ? x : y; }
+
+       +__attribute__((target_clones("avx2","arch=atom","default")))
+        static double aerror(C *a, C *b, int n)
+        {
+            if (n > 0) {
+       @@ -111,6 +112,7 @@
+       }
+
+       /* make array hermitian */
+       +__attribute__((target_clones("avx2","arch=atom","default")))
+       void mkhermitian(C *A, int rank, const bench_iodim *dim, int stride)
+       {
+            if (rank == 0)
+       @@ -148,6 +150,7 @@
+       }
+
+       /* C = A + B */
+       +__attribute__((target_clones("avx2","arch=atom","default")))
+       void aadd(C *c, C *a, C *b, int n)
+       {
+            int i;
+       @@ -159,6 +162,7 @@
+       }
+
+       /* C = A - B */
+       +__attribute__((target_clones("avx2","arch=atom","default")))
+       void asub(C *c, C *a, C *b, int n)
+       {
+            int i;
+       @@ -170,6 +174,7 @@
+       }
+
+       /* B = rotate left A (complex) */
+       +__attribute__((target_clones("avx2","arch=atom","default")))
+       void arol(C *b, C *a, int n, int nb, int na)
+       {
+            int i, ib, ia;
+       @@ -192,6 +197,7 @@
+            }
+       }
+
+With these patches, we can select where to apply the FMV technology making
+bringing architecture-based optimizations to application code even easier.
+
+**Congratulations!**
+
+You have successfully installed an FMV development environment on |CL|.
+Furthermore, you used cutting edge compiler technology to improve the
+performance of your application based on Intel Architecture technology and
+profiling of the specific execution of your application.
+
+.. _GCC:  https://gcc.gnu.org
+.. _make-fmv-patch: https://github.com/clearlinux/make-fmv-patch
@@ -0,0 +1,420 @@
+.. _greengrass:
+
+Enable AWS Greengrass\* and OpenVINO™ toolkit
+#############################################
+
+Hardware accelerated Function-as-a-Service (FaaS) enables cloud developers to
+deploy inference functionalities [1] on Intel® IoT edge devices with
+accelerators (CPU, Integrated GPU, Intel® FPGA, and Intel® Movidius™
+technology). These functions provide a great developer experience and seamless
+migration of visual analytics from cloud to edge in a secure manner using a
+containerized environment. Hardware-accelerated FaaS provides the best-in-class
+performance by accessing optimized deep learning libraries on Intel® IoT
+edge devices with accelerators.
+
+This tutorial demonstrates how to:
+
+* Set up the Intel® edge device with |CL-ATTR|
+* Install the OpenVINO™ toolkit and Amazon Web Services\* (AWS\*)
+  Greengrass\* software stacks
+* Use AWS Greengrass\* and AWS Lambda\* to deploy the FaaS samples from the cloud
+
+Refer to the following topics:
+
+.. contents:: :local:
+   :depth: 1
+
+
+Supported platforms
+*******************
+
+*	Operating System: |CL| latest release
+*	Hardware:	Intel® core platforms (This tutorial supports inference on CPU only.)
+
+Sample description
+==================
+
+The AWS Greengrass samples are located at `Edge-Analytics-FaaS`_. This
+tutorial uses the 1.0 version of the source code.
+
+|CL| provides the following AWS Greengrass samples:
+
+* `greengrass_classification_sample.py`_
+
+  This AWS Greengrass sample classifies a video stream using classification
+  networks such as AlexNet and GoogLeNet and publishes top-10 results on AWS\*
+  IoT Cloud every second.
+
+* `greengrass_object_detection_sample_ssd.py`_
+
+  This AWS Greengrass sample detects objects in a video stream and
+  classifies them using single-shot multi-box detection (SSD) networks such
+  as SSD Squeezenet, SSD Mobilenet, and SSD300. This sample publishes
+  detection outputs such as class label, class confidence, and bounding box
+  coordinates on AWS IoT Cloud every second.
+
+
+Install the OS on the edge device
+*********************************
+
+Start with a clean installation of |CL| on a new system, using the
+:ref:`bare-metal-install-desktop`, found in :ref:`get-started`.
+
+Create user accounts
+====================
+
+After |CL| is installed, create two user accounts. Create an administrative
+user in |CL| and create a user account for the Greengrass services to use (
+see Greengrass user below).
+
+#. Create a new user and set a password for that user. Enter the following
+   commands as ``root``:
+
+   .. code-block:: bash
+
+      useradd <userid>
+      passwd <userid>
+
+#. Next, enable the :command:`sudo` command for your new ``<userid>``. Add
+   ``<userid>`` to the *wheel* group:
+
+   .. code-block:: bash
+
+      usermod -G wheel -a <userid>
+
+#. Create a :file:`/etc/fstab` file.
+
+   .. code-block:: bash
+
+      touch /etc/fstab
+
+   .. note::
+
+      By default, |CL| does not create an :file:`/etc/fstab` file.
+      You must create this file before the Greengrass service runs.
+
+Add required bundles
+====================
+
+Use the :command:`swupd` software updater utility to add the prerequisite bundles
+for the OpenVINO software stack:
+
+.. code-block:: bash
+
+   swupd bundle-add os-clr-on-clr desktop-autostart computer-vision-basic
+
+.. note::
+
+   Learn more about how to :ref:`swupd-guide`.
+
+The :command:`computer-vision-basic` bundle installs the OpenVINO™ toolkit,
+and the sample models optimized for Intel® edge platforms.
+
+Convert deep learning models
+============================
+
+Locate sample models
+--------------------
+
+There are two types of provided models that can be used in conjunction with
+AWS Greengrass for this tutorial: classification or object detection.
+
+To complete this tutorial using an image classification model,
+download the BVLC AlexNet model files `bvlc_alexnet.caffemodel`_ and `deploy.prototxt`_
+to the default model_location at :file:`/usr/share/openvino/models`.
+Any custom pre-trained classification models can be used with the
+classification sample.
+
+For object detection, the sample models optimized for Intel® edge platforms
+are included with the computer-vision-basic bundle installation at :file:`/usr/share/openvino/models`.
+These models are provided as an example; however, you may also use a custom SSD model
+with the Greengrass object detection sample.
+
+Run model optimizer
+-------------------
+
+Follow these instructions for `converting deep learning models to Intermediate Representation using Model Optimizer`_. To optimize either of the sample models described above, run one of the following commands.
+
+For classification using BVLC AlexNet model:
+
+.. code-block:: bash
+
+   python3 mo.py --framework caffe --input_model
+   <model_location>/bvlc_alexnet.caffemodel --input_proto
+   <model_location>/deploy.prototxt --data_type <data_type> --output_dir
+   <output_dir> --input_shape [1,3,227,227]
+
+For object detection using SqueezeNetSSD-5Class model:
+
+.. code-block:: bash
+
+   python3 mo.py --framework caffe --input_model
+   <model_location>/'SqueezeNet 5-Class detection'/SqueezeNetSSD-5Class.caffemodel
+   --input_proto <model_location>/'SqueezeNet 5-Class detection'/SqueezeNetSSD-5Class.prototxt
+   --data_type <data_type> --output_dir <output_dir>
+
+In these examples:
+
+* ``<model_location>`` is :file:`/usr/share/openvino/models`.
+
+* ``<data_type>`` is FP32 or FP16, depending on target device.
+
+* ``<output_dir>`` is the directory where the Intermediate Representation
+  (IR) is stored. IR contains .xml format corresponding to the network
+  structure and .bin format corresponding to weights. This .xml file should be
+  passed to :command:`<PARAM_MODEL_XML>`.
+
+* In the BVLC AlexNet model, the prototxt defines the input shape with
+  batch size 10 by default. In order to use any other batch size, the
+  entire input shape must be provided as an argument to the model
+  optimizer. For example, to use batch size 1, you must provide:
+  ``--input_shape [1,3,227,227]``
+
+
+Configure AWS Greengrass group
+******************************
+
+For each Intel® edge platform, you must create a new AWS Greengrass group
+and install AWS Greengrass core software to establish the connection between
+cloud and edge.
+
+#. To create an AWS Greengrass group, follow the instructions in 
+   `Configure AWS IoT Greengrass on AWS IoT`_.
+
+#. To install and configure AWS Greengrass core on edge platform, follow
+   the instructions in `Start AWS Greengrass on the Core Device`_. In
+   step 8(b), download the x86_64 Ubuntu\* configuration of the AWS Greengrass
+   core software.
+
+   .. note::
+
+      You do not need to run the :file:`cgroupfs-mount.sh` script in step #6
+      of Module 1 of the `AWS Greengrass developer guide`_ because this is
+      enabled already in |CL|.
+
+#. Be sure to download both the security resources and the AWS Greengrass
+   core software.
+
+   .. note::
+
+      Security certificates are linked to your AWS account.
+
+
+Create and package Lambda function
+**********************************
+
+#. Complete steps 1-4 of the AWS Greengrass tutorial at `Create and Package a Lambda Function`_.
+
+   .. note::
+
+      This creates the tarball needed to create the AWS Greengrass
+      environment on the edge device.
+
+
+#. In step 5, replace :file:`greengrassHelloWorld.py` with the classification or object detection
+   Greengrass sample from `Edge-Analytics-Faas`_:
+
+   * Classification: `greengrass_classification_sample.py`_
+
+   * Object Detection: `greengrass_object_detection_sample_ssd.py`_
+
+#. Zip the selected Greengrass sample with the extracted Greengrass SDK folders from the previous
+   step into :file:`greengrass_sample_python_lambda.zip`.
+
+   The zip should contain:
+
+   * greengrasssdk
+
+   * greengrass classification or object detection sample
+
+   For example:
+
+   .. code-block:: bash
+
+      zip -r greengrass_lambda.zip greengrasssdk
+      greengrass_object_detection_sample_ssd.py
+
+#. Return to the AWS documentation section called `Create and Package a Lambda Function`_
+   and complete the procedure.
+
+   .. note::
+
+      In step 9(a) of the AWS documentation, while uploading the zip file,
+      make sure to name the handler to one of the following, depending on the
+      AWS Greengrass sample you are using:
+
+      * greengrass_object_detection_sample_ssd.function_handler
+      * greengrass_classification_sample.function_handler
+
+
+Configure Lambda function
+*************************
+
+After creating the Greengrass group and the Lambda function, start
+configuring the Lambda function for AWS Greengrass.
+
+#. Follow steps 1-8 in `Configure the Lambda Function for AWS IoT Greengrass`_ in the AWS
+   documentation.
+
+#. In addition to the details mentioned in step 8, change the Memory limit
+   to 2048 MB to accommodate large input video streams.
+
+#. Add the following environment variables as key-value pairs when editing
+   the Lambda configuration and click on update:
+
+   .. list-table:: **Table 1.  Environment variables: Lambda configuration**
+      :widths: 20 80
+      :header-rows: 1
+
+      * - Key
+        - Value
+      * - PARAM_MODEL_XML
+        - <MODEL_DIR>/<IR.xml>, where <MODEL_DIR> is user specified and
+          contains IR.xml, the Intermediate Representation file from Intel® Model Optimizer.
+          For this tutorial, <MODEL_DIR> should be set to '/usr/share/openvino/models'
+          or one of its subdirectories.
+      * - PARAM_INPUT_SOURCE
+        - <DATA_DIR>/input.webm to be specified by user. Holds both input and
+           output data. For webcam, set PARAM_INPUT_SOURCE to ‘/dev/video0’
+      * - PARAM_DEVICE
+        - "CPU"
+      * - PARAM_CPU_EXTENSION_PATH
+        - /usr/lib64/libcpu_extension.so
+      * - PARAM_OUTPUT_DIRECTORY
+        - <DATA_DIR> to be specified by user. Holds both input and output
+          data
+      * - PARAM_NUM_TOP_RESULTS
+        - User specified for classification sample.
+          (e.g. 1 for top-1 result, 5 for top-5 results)
+
+#. Add subscription to subscribe, or publish messages from AWS Greengrass
+   Lambda function by completing the procedure in `Configure the Lambda Function for AWS IoT Greengrass`_.
+
+   .. note::
+
+      The optional topic filter field is the topic mentioned inside the Lambda
+      function. In this tutorial, sample topics include the following:
+      :command:`openvino/ssd` or :command:`openvino/classification`
+
+Add local resources
+===================
+
+Refer to the AWS documentation for details about `local resources and access privileges`_.
+
+The following table describes the local resources needed for the CPU:
+
+.. list-table:: **Local resources**
+    :widths: 20, 20, 20, 20
+    :header-rows: 1
+
+    * - Name
+      - Resource type
+      - Local path
+      - Access
+
+    * - ModelDir
+      - Volume
+      - <MODEL_DIR> to be specified by user
+      - Read-Only
+
+    * - Webcam
+      - Device
+      - /dev/video0
+      - Read-Only
+
+    * - DataDir
+      - Volume
+      - <DATA_DIR> to be specified by user. Holds both input and output
+        data.
+      - Read and Write
+
+Deploy Lambda function
+**********************
+
+Refer to the AWS documentation for instructions on how to 
+`deploy the lambda function to AWS Greengrass core device`_. Select
+*Deployments* on the group page and follow the instructions.
+
+Output consumption
+==================
+
+There are four options available for output consumption. These options are
+used to report, stream, upload, or store inference output at an interval
+defined by the variable :command:`reporting_interval` in the AWS Greengrass samples.
+
+a. IoT cloud output:
+
+   This option is enabled by default in the AWS Greengrass samples using the 
+   :command:`enable_iot_cloud_output` variable. You can use it to verify the lambda
+   running on the edge device. It enables publishing messages to IoT cloud
+   using the subscription topic specified in the lambda. (For example, topics
+   may include :command:`openvino/classification` for classification and :command:`openvino/ssd`
+   for object detection samples.) For classification, top-1 result with class
+   label are published to IoT cloud. For SSD object detection, detection
+   results such as bounding box coordinates of objects, class label, and
+   class confidence are published.
+
+   Follow the instructions here to `view the output on IoT cloud`_.
+
+b. Kinesis streaming:
+
+   This option enables inference output to be streamed from the edge device
+   to cloud using Kinesis [3] streams when :command:`enable_kinesis_output` is set
+   to True. The edge devices act as data producers and continually push
+   processed data to the cloud. You must set up and specify
+   Kinesis stream name, Kinesis shard, and AWS region in the AWS Greengrass
+   samples.
+
+c. Cloud storage using AWS S3 bucket:
+
+   When the :command:`enable_s3_jpeg_output` variable is set to True, it enables
+   uploading and storing processed frames (in jpeg format) in an AWS S3
+   bucket. You must set up and specify the S3 bucket name in the AWS
+   Greengrass samples to store the JPEG images. The images are named using the
+   timestamp and uploaded to S3.
+
+d. Local storage:
+
+   When the :command:`enable_s3_jpeg_output` variable is set to True, it enables
+   storing processed frames (in jpeg format) on the edge device. The images
+   are named using the timestamp and stored in a directory specified by
+   :command:`PARAM_OUTPUT_DIRECTORY`.
+
+References
+**********
+
+1. AWS Greengrass: https://aws.amazon.com/greengrass/
+2. AWS Lambda: https://aws.amazon.com/lambda/
+3. AWS Kinesis: https://aws.amazon.com/kinesis/
+
+.. _Edge-Analytics-FaaS: https://github.com/intel/Edge-Analytics-FaaS/tree/v1.0/AWS%20Greengrass
+
+.. _bvlc_alexnet.caffemodel: http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel
+
+.. _deploy.prototxt: https://github.com/BVLC/caffe/blob/master/models/bvlc_alexnet/deploy.prototxt
+
+.. _greengrass_classification_sample.py: https://github.com/intel/Edge-Analytics-FaaS/blob/v1.0/AWS%20Greengrass/greengrass_classification_sample.py
+
+.. _greengrass_object_detection_sample_ssd.py: https://github.com/intel/Edge-Analytics-FaaS/blob/v1.0/AWS%20Greengrass/greengrass_object_detection_sample_ssd.py
+
+.. _converting deep learning models to Intermediate Representation using Model Optimizer: https://software.intel.com/en-us/articles/OpenVINO-ModelOptimizer
+
+.. _AWS Greengrass Developer Guide: https://docs.aws.amazon.com/greengrass/latest/developerguide/what-is-gg.html
+
+.. _Configure AWS IoT Greengrass on AWS IoT: https://docs.aws.amazon.com/greengrass/latest/developerguide/gg-config.html
+
+.. _Start AWS Greengrass on the Core Device: https://docs.aws.amazon.com/greengrass/latest/developerguide/gg-device-start.html
+
+.. _Configure the Lambda Function for AWS IoT Greengrass: https://docs.aws.amazon.com/greengrass/latest/developerguide/config-lambda.html
+
+.. _local resources and access privileges: https://docs.aws.amazon.com/greengrass/latest/developerguide/access-local-resources.html
+
+.. _deploy the lambda function to AWS Greengrass core device: https://docs.aws.amazon.com/greengrass/latest/developerguide/configs-core.html
+
+.. _Edge-optmized models repository: https://github.com/intel/Edge-optimized-models
+
+.. _view the output on IoT cloud: https://docs.aws.amazon.com/greengrass/latest/developerguide/lambda-check.html
+
+.. _this link to add local resources and access privileges: https://docs.aws.amazon.com/greengrass/latest/developerguide/access-local-resources.html
+
+.. _Create and Package a Lambda Function: https://docs.aws.amazon.com/greengrass/latest/developerguide/create-lambda.html
@@ -0,0 +1,256 @@
+.. _hadoop:
+
+Set up a single node cluster with Hadoop\*
+##########################################
+
+This tutorial walks you through the process of installing, configuring, and
+running Apache\* Hadoop on |CL-ATTR|. The Apache Hadoop software library is a
+framework for distributed processing of large data sets across clusters of
+computers using simple programming models. It is designed to scale up from
+single servers to thousands of machines, with each machine offering local
+computation and storage.
+
+Prerequisites
+*************
+
+Before following this tutorial, you should follow the
+:ref:`bare-metal-install-desktop` to ensure you have installed |CL|.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+For the purposes of this tutorial, we will install Hadoop in a single machine
+running both the master and slave daemons.
+
+Install Apache Hadoop
+*********************
+
+Apache Hadoop is included in the `big-data-basic` bundle. To install the
+framework, enter the following command:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add big-data-basic
+
+Configure Apache Hadoop
+***********************
+
+#. To create the configuration directory, enter the following command:
+
+   .. code-block:: bash
+
+      sudo mkdir /etc/hadoop
+
+#. Copy the defaults from :file:`/usr/share/defaults/hadoop` to
+   :file:`/etc/hadoop` with the following command:
+
+   .. code-block:: bash
+
+      $ sudo cp /usr/share/defaults/hadoop/* /etc/hadoop
+
+   .. note:: Since |CL| is a stateless system, you should never modify the
+      files under the :file:`/usr/share/defaults` directory. The software
+      updater will overwrite those files.
+
+Once all the configuration files are in :file:`/etc/hadoop`, we must edit
+them to fit our needs. The `NameNode` server is the master server. It manages
+the namespace of the files system and regulates the clients' access to files.
+The first file we edit, :file:`/etc/hadoop/core-site.xml`, informs the Hadoop
+daemon where `NameNode` is running.
+
+In this tutorial, our `NameNode` runs in our `localhost`. Follow these steps
+to set it up correctly:
+
+#. Open the :file:`/etc/hadoop/core-site.xml` file using the editor of your
+   choice and modify the file as follows:
+
+   .. code-block:: xml
+
+      <?xml version="1.0" encoding="UTF-8"?>
+      <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+      <configuration>
+      <property>
+      <name>fs.default.name</name>
+      <value>hdfs://localhost:9000</value>
+      </property>
+      </configuration>
+
+#. Edit the :file:`/etc/hadoop/hdfs-site.xml` file. This file configures the
+   :abbr:`HDFS (Hadoop Distributed File System)` daemons. This configuration
+   includes the list of permitted and excluded data nodes and the size of
+   said blocks. In this example, we are setting the number of block
+   replication to 1 from the default of 3 as follows:
+
+   .. code-block:: xml
+      :emphasize-lines: 6
+
+      <?xml version="1.0" encoding="UTF-8"?>
+      <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+      <configuration>
+      <property>
+      <name>dfs.replication</name>
+      <value>1</value>
+      </property>
+      <property>
+      <name>dfs.permission</name>
+      <value>false</value>
+      </property>
+      </configuration>
+
+#. Edit the :file:`/etc/hadoop/mapred-site.xml` file. This file configures
+   all daemons related to `MapReduce`: `JobTracker` and `TaskTrackers`. With
+   `MapReduce`, Hadoop can process big amounts of data in multiple systems. In
+   our example, we set :abbr:`YARN (Yet Another Resource Manager)` as our
+   runtime framework for executing `MapReduce` jobs as follows:
+
+   .. code-block:: xml
+      :emphasize-lines: 5,6
+
+      <?xml version="1.0" encoding="UTF-8"?>
+      <?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+      <configuration>
+      <property>
+      <name>mapreduce.framework.name</name>
+      <value>yarn</value>
+      </property>
+      </configuration>
+
+#. Edit the :file:`/etc/hadoop/yarn-site.xml` file. This file configures all
+   daemons related to `YARN`: `ResourceManager` and `NodeManager`. In our
+   example, we implement the `mapreduce_shuffle` service, which is the
+   default as follows:
+
+   .. code-block:: xml
+      :emphasize-lines: 4,5,8,9
+
+      <?xml version="1.0"?>
+      <configuration>
+      <property>
+      <name>yarn.nodemanager.aux-services</name>
+      <value>mapreduce_shuffle</value>
+      </property>
+      <property>
+      <name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
+      <value>org.apache.hadoop.mapred.ShuffleHandler</value>
+      </property>
+      </configuration>
+
+Configure your SSH key
+**********************
+
+#. Create a SSH key. If you already have one, skip this step.
+
+   .. code-block:: bash
+
+      sudo ssh-keygen -t rsa
+
+
+#. Copy the key to your authorized keys.
+
+   .. code-block:: bash
+
+      sudo cat /root/.ssh/id_rsa.pub | sudo tee -a /root/.ssh/authorized_keys
+
+#. Log into the localhost. If no password prompt appears, you are ready to
+   run the Hadoop daemons.
+
+   .. code-block:: bash
+
+      sudo ssh localhost
+
+Run the Hadoop daemons
+**********************
+
+With all the configuration files properly edited, we are ready to start the
+daemons.
+
+When we format the `NameNode` server, it formats the meta-data related to
+data nodes. Thus, all the information on the data nodes is lost and the nodes
+can be reused for new data.
+
+#. Format the `NameNode` server with the following command:
+
+   .. code-block:: bash
+
+      sudo hdfs namenode -format
+
+#. Start the DFS in `NameNode` and `DataNodes` with the following command:
+
+   .. code-block:: bash
+
+      sudo start-dfs.sh
+
+#. The console output should be similar to:
+
+   .. code-block:: console
+
+      Starting namenodes on [localhost]
+      The authenticity of host 'localhost (::1)' can't be established.
+      ECDSA key fingerprint is
+      SHA256:97e+7TnomsS9W7GjFPjzY75HGBp+f1y6sA+ZFcOPIPU.
+      Are you sure you want to continue connecting (yes/no)?
+
+   Enter `yes` to continue.
+
+#. Start the `YARN` daemons `ResourceManager` and `NodeManager` with the
+   following command:
+
+   .. code-block:: bash
+
+      sudo start-yarn.sh
+
+#. Ensure everything is running as expected with the following command:
+
+   .. code-block:: bash
+
+      sudo jps
+
+#. The console output should be similar to:
+
+   .. code-block:: console
+
+      22674 DataNode
+      26228 Jps
+      22533 NameNode
+      23046 ResourceManager
+      22854 SecondaryNameNode
+      23150 NodeManager
+
+Run the MapReduce wordcount example
+***********************************
+
+#. Create the input directory.
+
+   .. code-block:: bash
+
+      sudo hdfs dfs -mkdir -p /user/root/input
+
+#. Copy a file from the local file system to the HDFS.
+
+   .. code-block:: bash
+
+      sudo hdfs dfs -copyFromLocal local-file /user/root/input
+
+#. Run the `wordcount` example.
+
+   .. code-block:: bash
+
+      sudo hadoop jar /usr/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.0.jar wordcount input output
+
+#. Read output file "part-r-00000". This file contains the number of times
+   each word appears in the file.
+
+   .. code-block:: bash
+
+      sudo hdfs dfs -cat /user/root/output/part-r-00000
+
+**Congratulations!**
+
+You successfully installed and setup a single node Hadoop cluster.
+Additionally, you ran a simple wordcount example.
+
+Your single node Hadoop cluster is up and running!
+
@@ -0,0 +1,116 @@
+  .. _kata:
+
+Install Kata Containers\*
+#########################
+
+This tutorial describes how to install, configure, and run `Kata Containers`_
+on |CL-ATTR|. Kata Containers is an open source project developing a
+lightweight implementation of :abbr:`VMs (Virtual Machines)` that offer the
+speed of containers and the security of VMs.
+
+Prerequisites
+*************
+
+This tutorial assumes you have installed |CL| on your host system.
+For detailed instructions on installing |CL| on a bare metal system, follow
+the :ref:`bare metal installation tutorial<bare-metal-install-desktop>`.
+
+If you have Clear Containers installed on your |CL| system, then follow the
+:ref:`migrate Clear Containers to Kata Containers tutorial<kata_migration>`.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+Install Kata Containers
+***********************
+
+Kata Containers is included in the :file:`containers-virt` bundle.
+To install the framework, enter the following command:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add containers-virt
+
+Restart the Docker\* and Kata Containers systemd services.
+
+.. code-block:: bash
+
+   sudo systemctl daemon-reload
+   sudo systemctl restart docker
+
+Run Kata Containers
+*******************
+
+.. code-block:: bash
+
+   sudo docker run -ti busybox sh
+
+.. note::
+
+   If you use a proxy server and your proxy environment variables are already
+   set, run the following commands as a shell script to configure Docker:
+
+   .. code-block:: bash
+
+      docker_service_dir="/etc/systemd/system/docker.service.d/"
+      sudo mkdir -p "$docker_service_dir"
+      cat <<EOF | sudo tee "$docker_service_dir/proxy.conf"
+      [Service]
+      Environment="HTTP_PROXY=$http_proxy"
+      Environment="HTTPS_PROXY=$https_proxy"
+      EOF
+      echo "Reloading unit files and starting docker service"
+      sudo systemctl daemon-reload
+      sudo systemctl restart docker
+      sudo docker info
+
+**Congratulations!**
+
+You've successfully installed and set up Kata Containers on |CL|.
+
+More information about Docker
+*****************************
+
+Docker on |CL| provides a :file:`docker.service` file to start the Docker
+daemon. The daemon will use runc or kata-runtime depending on the
+environment:
+
+*  If you are running |CL| on bare metal or on a VM with Nested
+   Virtualization activated, Docker uses kata-runtime as the
+   default runtime.
+*  If you are running |CL| on a VM without Nested Virtualization,
+   Docker uses runc as the default runtime.
+
+You do not need to manually configure the runtime for Docker, because
+it automatically uses the runtime supported by the system.
+
+Troubleshooting
+===============
+
+- To change the Docker storage driver, see
+  :ref:`additional-docker-configuration`.
+
+- For some |CL| versions before 27000, you may need to manually
+  configure Docker\* to use Kata Containers by default.
+
+  To do so, enter:
+
+  .. code-block:: bash
+
+     sudo mkdir -p /etc/systemd/system/docker.service.d/
+     cat <<EOF | sudo tee /etc/systemd/system/docker.service.d/50-runtime.conf
+     [Service]
+     Environment="DOCKER_DEFAULT_RUNTIME=--default-runtime kata-runtime"
+     EOF
+
+- To check the version of |CL| on your system, enter:
+
+  .. code-block:: bash
+
+     sudo swupd verify
+
+
+.. _Kata Containers: https://katacontainers.io/
@@ -0,0 +1,91 @@
+.. _kata_migration:
+
+Migrate Clear Containers to Kata Containers\*
+#############################################
+
+`Clear Containers`_ and `Kata Containers`_ can co-exist in the same system.
+Both can be installed through the :file:`containers-virt bundle`. However, we
+recommend that you migrate to Kata Containers because Clear Containers is no
+longer maintained_ and will soon be deprecated on |CL-ATTR|.
+
+This guide describes how to migrate to Kata Containers and assumes that:
+
+*  Clear Containers is on a Docker\* system.
+*  Kata Containers is installed. See :ref:`kata`.
+
+
+Stop Clear Containers instances
+*******************************
+
+As an unprivileged user, stop all running instances of Clear Containers:
+
+.. code-block:: bash
+
+    for container in $(sudo docker ps -q); do sudo docker stop $container; done
+
+
+Manually migrate customized configuration files
+***********************************************
+
+If you have made changes to your `Clear Containers configuration`_, review
+those changes and decide whether to manually apply those changes to your
+`Kata Containers configuration`_.
+
+Make any required changes before continuing this process.
+
+.. note::
+
+  You do not need to manually remove any Clear Containers packages.
+
+
+Enable Kata Containers as default
+*********************************
+
+#. Configure Docker to use the Kata Containers runtime by default.
+
+   .. code-block:: bash
+
+      sudo mkdir -p /etc/systemd/system/docker.service.d/
+      cat <<EOF | sudo tee /etc/systemd/system/docker.service.d/51-runtime.conf
+      [Service]
+      Environment="DOCKER_DEFAULT_RUNTIME=--default-runtime kata-runtime"
+      EOF
+
+#. Restart the Docker systemd services.
+
+   .. code-block:: bash
+
+      sudo systemctl daemon-reload
+      sudo systemctl restart docker
+
+#. Verify Docker is using Kata Containers.
+
+   .. code-block:: bash
+
+      sudo docker info | grep -i 'default runtime'
+      Default Runtime: kata-runtime
+
+Run Kata Containers
+*******************
+
+Use the following command:
+
+.. code-block:: bash
+
+   sudo docker run -ti busybox sh
+
+**Congratulations!**
+
+You've successfully migrated from Clear Containers to Kata Containers.
+
+
+.. _Clear Containers: https://github.com/clearcontainers
+
+.. _Kata Containers: https://github.com/kata-containers
+
+.. _maintained: https://github.com/kata-containers/documentation/blob/master/Upgrading.md#maintenance-warning
+
+.. _Clear Containers configuration: https://github.com/clearcontainers/runtime#configuration
+
+.. _Kata Containers configuration: https://github.com/kata-containers/runtime#configuration
+
@@ -0,0 +1,92 @@
+.. _kubernetes-bp:
+
+Kubernetes Best Practices on |CL|
+#################################
+
+Use swupd to update clusters
+****************************
+
+This tutorial shows you how to manage your Kubernetes cluster while using
+:command:`swupd` to update |CL-ATTR|.
+
+In our tutorial :ref:`kubernetes`, we explain how to set up a Kubernetes
+cluster on |CL| using `kubeadm`. `Kubeadm documentation`_ often builds on the
+assumption that the distribution uses a traditional package manager (e.g.,
+RPM/DEB).
+
+In contrast, |CL| uses `swupd` to update the OS, which in this case updates
+all of the kubernetes node and client binaries simultaneously, as part of
+the `cloud-native-basic` bundle (e.g., kubectl, kubeadm, kubelet). Running
+:command:`sudo swupd update` requires special care to ensure the OS
+incorporates the latest Kubernetes upgrades.
+
+This document describes best practices to manage cluster upgrades with
+`kubeadm` on a |CL|-based cluster.
+
+Prerequisites
+*************
+
+Assure that you:
+
+* Completed :ref:`kubernetes`
+* Installed the bundle `cloud-native-basic`
+
+.. note::
+
+   Other Linux\* distros shown in Kubernetes upgrade documentation reflect
+   `apt-get update`, `apt-mark hold kubeadm`, and similar commands; however, such commands **are not valid** on |CL|.
+
+Update the control plane
+************************
+
+#. Read kubernetes documentation `before you begin`_.
+
+#. On your master node, run the command:
+
+   .. code-block:: bash
+
+      sudo swupd update
+
+   .. note::
+
+      If the minor version of Kubernetes changes, |CL| shows a message-of-the-day, or `motd`. When the `motd` appears, you **must postpone** a kubelet restart on master and nodes until the control plane is properly updated. :command:`swupd update` does not restart services automatically unless explicitly configured to do so.
+
+#. Now follow these instructions in kubernetes documentation.
+
+   * `Upgrade control plane`_
+   * `Drain control plane node`_
+   * `Restart Kubelet and undrain node`_
+
+Update worker nodes
+*******************
+
+#. On each worker node, run the command:
+
+   .. code-block:: bash
+
+      sudo swupd update
+
+#. Now follow these instructions in kubernetes documentation:
+
+   * `Drain node`_
+   * `Update kubelet configuration`_
+   * `Restart Kubelet and undrain node`_
+
+.. _Kubeadm documentation: https://kubernetes.io/docs/reference/setup-tools/kubeadm/kubeadm-upgrade/
+
+.. _Restart Kubelet and undrain node: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#restart-the-kubelet-for-all-nodes
+
+.. _Update kubelet configuration: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#upgrade-the-kubelet-config-on-worker-nodes
+
+.. _Drain node: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#drain-control-plane-and-worker-nodes
+
+ .. _Restart kubelet and undrain node: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#restart-the-kubelet-for-all-nodes
+
+.. _Upgrade control plane: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#upgrade-the-control-plane-node
+
+.. _Drain control plane node: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#drain-control-plane-and-worker-nodes
+
+.. _Kubeadmn documentation: https://kubernetes.io/docs/reference/setup-tools/kubeadm/kubeadm/
+
+.. _before you begin: https://kubernetes.io/docs/tasks/administer-cluster/kubeadm/kubeadm-upgrade-1-13/#before-you-begin
+
@@ -0,0 +1,414 @@
+.. _kubernetes:
+
+Run Kubernetes\*
+################
+
+This tutorial describes how to install, configure, and run the
+`Kubernetes container orchestration system`_ on |CL-ATTR| using CRI+O and
+kata-runtime.
+
+Kubernetes\* is an open source system for automating deployment, scaling, and
+management of containerized applications. It groups containers that make up
+an application into logical units for easy management and discovery.
+
+Kata Containers\* kata-runtime adheres to
+:abbr:`OCI (Open Container Initiative*)` guidelines and work seamlessly with
+Kubernetes. `Kata Containers`_ provide strong isolation for untrusted
+workloads or  multi-tenant scenarios. Kata Containers can be
+allocated on a per-pod basis so you can mix and match both on the same host
+to suit your needs.
+
+.. contents:: :local:
+   :depth: 1
+
+Prerequisites
+*************
+
+This tutorial assumes you have already installed |CL|. For detailed
+instructions on installing |CL| on a bare metal system, follow the
+:ref:`bare metal installation tutorial<bare-metal-install-desktop>`.
+Learn about the benefits of having an up-to-date system for cloud
+orchestration on the :ref:`swupd-about` page.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+Install Kubernetes and CRI runtimes
+***********************************
+
+Kubernetes, a set of supported :abbr:`CRI (Container Runtime Interface)`
+runtimes, and networking plugins, are included in the `cloud-native-basic`_
+bundle.
+
+To install this framework, enter the following command:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add cloud-native-basic
+
+.. note::
+
+   For more on networking plugins, see `Install pod network add-on`_.
+
+Configure Kubernetes
+********************
+
+This tutorial uses the basic default Kubernetes configuration for simplicity.
+You must define your Kubernetes configuration according to your specific
+deployment and your security needs.
+
+#. Enable IP forwarding to avoid kubeadm `preflight check`_ errors:
+
+   Create (or edit if it exists) the file :file:`/etc/sysctl.d/60-k8s.conf`
+   and include the following line:
+
+   .. code-block:: bash
+
+      net.ipv4.ip_forward = 1
+
+   Apply the change:
+
+   .. code-block:: bash
+
+      sudo systemctl restart systemd-sysctl
+
+#. Enable the kubelet service:
+
+   .. code-block:: bash
+
+      sudo systemctl enable kubelet.service
+
+#. Disable swap using one of the following methods, either:
+
+   a) Temporarily:
+
+      .. code-block:: bash
+
+         sudo swapoff -a
+
+      .. note::
+
+         Swap will be enabled at next reboot, causing failures in
+         your cluster.
+
+   or:
+
+   b) Permanently:
+
+      Mask the swap partition:
+
+      .. code-block:: bash
+
+         sudo systemctl mask $(sed -n -e 's#^/dev/\([0-9a-z]*\).*#dev-\1.swap#p' /proc/swaps) 2>/dev/null
+         sudo swapoff -a
+
+      .. note::
+
+         On systems with limited resources, some performance degradation may
+         be observed while swap is disabled.
+
+#. Switch to root to modify the `hosts` file:
+
+   .. code-block:: bash
+
+      sudo -s
+
+#.  Create (or edit if it exists) the hosts file that Kubernetes will read to
+    locate the master's host:
+
+    .. code-block:: bash
+
+       echo "127.0.0.1 localhost `hostname`" >> /etc/hosts
+
+#.  Exit root:
+
+    .. code-block:: bash
+
+       exit
+
+Configure and run Kubernetes
+****************************
+
+This section describes how to configure and run Kubernetes with CRI-O and kata-runtime.
+
+Configure and run CRI-O + kata-runtime
+======================================
+
+#.  Enable the CRI-O service:
+
+    .. code-block:: bash
+
+       sudo systemctl enable crio.service
+
+#.  Enter the commands:
+
+    .. code-block:: bash
+
+       sudo systemctl daemon-reload
+       sudo systemctl restart crio
+
+#.  Initialize the master control plane with the command:
+
+    .. code-block:: bash
+
+       sudo kubeadm init --cri-socket=/run/crio/crio.sock
+
+Install pod network add-on
+**************************
+
+You must choose and install a `pod network add-on`_ to allow your pods to
+communicate. Check whether or not your add-on requires special flags when you
+initialize the master control plane.
+
+The CRI-O default plugin_dir is :file:`/opt/cni/bin`. This must be a
+writable directory because third-party networking add-ons will install
+themselves there.
+
+.. note::
+
+   CNI plugins provided by |CL| are installed as part of *cloud-native-basic*
+   in :file:`/usr/libexec/cni/` and are currently *not* found by CRI-O by
+   default. These separate directories are required because `swupd` controls
+   the content of :file:`/usr` and leaves :file:`/opt` unchanged.
+
+When using third-party network add-ons that rely on those plugins, such as
+Weave or Flannel do, make them available by creating symlinks:
+
+.. code-block:: bash
+
+   sudo mkdir -p /opt/cni/bin
+
+.. code-block:: bash
+
+   for i in /usr/libexec/cni/*; do sudo ln -sf $i /opt/cni/bin; done
+
+**Notes about Weave Net add-on**
+
+The Weave Net add-on works by default when the above configuration is done.
+
+**Notes about flannel add-on**
+
+If you choose the `flannel` add-on, then you must add the following to the
+`kubeadm init` command:
+
+.. code-block:: bash
+
+   --pod-network-cidr 10.244.0.0/16
+
+If you are using CRI-O and `flannel` and you want to use Kata Containers,
+edit the :file:`/etc/crio/crio.conf` file to add:
+
+..  code-block:: bash
+
+    [crio.runtime]
+    manage_network_ns_lifecycle = true
+
+Use your cluster
+****************
+
+Once your master control plane is successfully initialized, instructions on
+how to use your cluster and its *IP*, *token*, and *hash* values are
+displayed. It is important that you record the cluster values because they
+are needed when joining worker nodes to the cluster. Some values have a valid
+period. The values are presented in a format similar to:
+
+.. code-block:: bash
+
+   kubeadm join <master-ip>:<master-port> --token <token> --discovery-token-ca-cert-hash <hash>
+
+**Congratulations!**
+
+You've successfully installed and set up Kubernetes in |CL| using CRI-O and
+kata-runtime. You are now ready to follow on-screen instructions to deploy a
+pod network to the cluster and join worker nodes with the displayed token
+and IP information.
+
+Related topics
+**************
+
+Read the Kubernetes documentation to learn more about:
+
+* `Understanding basic Kubernetes architecture`_
+
+* `Deploying an application to your cluster`_
+
+* Installing a `pod network add-on`_
+
+* `Joining your nodes`_
+
+Cloud native setup automation (optional)
+****************************************
+
+Clone the `cloud-native-setup`_ repository on your system and follow the instructions. This repository includes helper scripts to automate configuration.
+
+Package configuration customization (optional)
+**********************************************
+
+|CL| is a stateless system that looks for user-defined package configuration
+files in the :file:`/etc/<package-name>` directory to be used as default. If
+user-defined files are not found, |CL| uses the distribution-provided
+configuration files for each package.
+
+If you customize any of the default package configuration files, you **must**
+store the customized files in the :file:`/etc/` directory. If you edit any of
+the distribution-provided default files, your changes will be lost in the
+next system update.
+
+For example, to customize CRI-O configuration in your system, run the
+following commands:
+
+.. code-block:: bash
+
+   sudo mkdir /etc/crio
+   sudo cp /usr/share/defaults/crio/crio.conf /etc/crio/
+   sudo $EDITOR /etc/crio/crio.conf
+
+Learn more about `Stateless`_ in |CL| and view the |CL| `documentation`_.
+
+Proxy configuration (optional)
+******************************
+
+If you use a proxy server, you must set your proxy environment variables and
+create an appropriate proxy configuration file for both CRI-O services. Consult your IT department if you are behind a corporate proxy for
+the appropriate values. Ensure that your local IP is **explicitly included**
+in the environment variable *NO_PROXY*. (Setting *localhost* is not enough.)
+
+If you have already set your proxy environment variables, run the following
+commands as a shell script to configure all of these services in one step:
+
+.. code-block:: bash
+
+   services=('crio')
+   for s in "${services[@]}"; do
+   sudo mkdir -p "/etc/systemd/system/${s}.service.d/"
+   cat << EOF | sudo tee "/etc/systemd/system/${s}.service.d/proxy.conf"
+   [Service]
+   Environment="HTTP_PROXY=${http_proxy}"
+   Environment="HTTPS_PROXY=${https_proxy}"
+   Environment="SOCKS_PROXY=${socks_proxy}"
+   Environment="NO_PROXY=${no_proxy}"
+   EOF
+   done
+
+Next steps
+**********
+
+:ref:`kubernetes-bp`
+
+
+Troubleshooting
+***************
+
+* <HOSTNAME> not found in <IP> message.
+
+  Your DNS server may not be appropriately configured. Try adding an
+  entry to the :file:`/etc/hosts` file with your host's IP and Name.
+
+  For example: 100.200.50.20 myhost
+
+  Use the commands :command:`hostname` and :command:`hostname -I` to retrieve them.
+
+* Images cannot be pulled.
+
+  You may be behind a proxy server. Try configuring your proxy settings,
+  using the environment variables *HTTP_PROXY*, *HTTPS_PROXY*, and *NO_PROXY*
+  as required in your environment.
+
+* Connection refused error.
+
+  If you are behind a proxy server, you may need to add the master's IP to
+  the environment variable *NO_PROXY*.
+
+* Connection timed-out or Access Refused errors.
+
+  You must ensure that the appropriate proxy settings are available from the
+  same terminal where you will initialize the control plane. To verify the
+  proxy settings that Kubernetes will actually use, run the commands:
+
+  .. code-block:: bash
+
+    echo $HTTP_PROXY
+    echo $HTTPS_PROXY
+    echo $NO_PROXY
+
+  If the displayed proxy values are different from your assigned values, the
+  cluster initialization will fail. Contact your IT support team to learn how
+  to set the proxy variables permanently, and how to make them available for
+  all the types of access that you will use, such as remote SSH access.
+
+  If the result of the above commands is blank, you may need to add a
+  ``profile`` to the :file:`/etc` directory. To do so, follow these steps.
+
+  #. Create a `profile` in :file:`/etc`
+
+     .. code-block:: bash
+
+        sudo touch profile
+
+  #. With a preferred editor, open `profile`, and enter your proxy settings.
+     Example shown below.
+
+     .. code-block:: bash
+
+        export "HTTP_PROXY=http://proxy.example.com:443"
+        export "HTTPS_PROXY=http://proxy.example.com:445"
+        export "SOCKS_PROXY=http://proxy.example.com:1080"
+        export "NO_PROXY= site.com,.site.com,localhost,127.0.0.1,<master IP>
+
+     .. note::
+
+        <master IP> can be obtained by running :command:`ifconfig`.
+
+  #. Save and exit the `profile`.
+
+  #. Run:
+
+     .. code-block:: bash
+
+        sudo source profile
+
+  #. To ensure your system isn't running previous session variables, run:
+
+     .. code-block:: bash
+
+        sudo kubeadm reset --cri-socket=/run/crio/crio.sock
+
+  #. Continue below while passing `-E` in the command as shown.
+
+* Missing environment variables.
+
+  If you are behind a proxy server, pass environment variables by adding *-E*
+  to the command that initializes the master control plane.
+
+  .. code-block:: bash
+
+     /* Kubernetes with CRI-O + kata-runtime */
+     sudo -E kubeadm init --cri-socket=/run/crio/crio.sock
+
+.. _Kubernetes container orchestration system: https://kubernetes.io/
+
+.. _Kata Containers: https://katacontainers.io/
+
+.. _Software Update documentation: https://clearlinux.org/documentation/clear-linux/concepts/swupd-about#updating
+
+.. _cloud-native-basic: https://github.com/clearlinux/clr-bundles/blob/master/bundles/cloud-native-basic
+
+.. _preflight check: https://kubernetes.io/docs/reference/setup-tools/kubeadm/implementation-details/#preflight-checks
+
+.. _Understanding basic Kubernetes architecture: https://kubernetes.io/docs/user-journeys/users/application-developer/foundational/#section-3
+
+.. _Deploying an application to your cluster: https://kubernetes.io/docs/user-journeys/users/application-developer/foundational/#section-2
+
+.. _pod network add-on: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/#pod-network
+
+.. _Joining your nodes: https://kubernetes.io/docs/setup/independent/create-cluster-kubeadm/#join-nodes
+
+.. _Stateless: https://clearlinux.org/features/stateless
+
+.. _documentation: https://clearlinux.org/documentation/clear-linux
+
+.. _cloud-native-setup: https://github.com/clearlinux/cloud-native-setup
+
@@ -0,0 +1,242 @@
+.. _machine-learning:
+
+TensorFlow\* machine learning on |CL-ATTR|
+##########################################
+
+This tutorial will demonstrate the installation and execusion of a TensorFlow\*
+machine learning example on |CL-ATTR|. It uses a Jupyter\* Notebook and MNIST
+data for handwriting recognition. 
+
+The initial steps will have you set up a Jupyter kernel and run a Notebook
+on a bare-metal |CL| system.
+
+Prerequisites
+*************
+
+This tutorial assumes you have installed |CL| on your host system. For
+detailed instructions on installing |CL| on a bare metal system, follow the
+:ref:`bare metal installation tutorial<bare-metal-install-desktop>`.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+Once your system is updated, add the following bundles to your system:
+
+* `machine-learning-web-ui`: This bundle contains the Jupyter application.
+
+* `machine-learning-basic`: This bundle contains TensorFlow and other useful
+  tools.
+
+To install the bundles, run the following commands in your :file:`$HOME`
+directory:
+
+.. code-block:: bash
+
+   sudo swupd bundle-add machine-learning-web-ui
+
+   sudo swupd bundle-add machine-learning-basic
+
+Set up a Jupyter notebook
+*************************
+
+With all required packages and libraries installed, set up the file structure
+for the Jupyter Notebook.
+
+#. In the :file:`$HOME` directory, create a directory for the Jupyter
+   Notebooks named :file:`Notebooks`.
+
+   .. code-block:: bash
+
+      mkdir Notebooks
+
+#. Within :file:`Notebooks`, create a directory named :file:`Handwriting`.
+
+   .. code-block:: bash
+
+      mkdir Notebooks/Handwriting
+
+#. Change to the new directory.
+
+   .. code-block:: bash
+
+      cd Notebooks/Handwriting
+
+#. Copy the :file:`MNIST_example.ipynb` file into the :file:`Handwriting`
+   directory.
+
+   .. note::
+      After installing the `machine-learning basic` bundle, you can find the
+      example code under
+      :file:`/usr/share/doc/tensorflow/MNIST_example.ipynb`.
+
+
+The example code downloads and decompresses the MNIST data directly into the
+:file:`./mnist` directory. Alternatively, download the four files directly
+from the Yann LeCun’s `MNIST Database website`_ and save them into a
+:file:`mnist` directory within the :file:`Handwriting` directory.
+
+The files needed are:
+
+* `train-images-idx3-ubyte.gz`_: Training set images (9912422 bytes)
+
+* `train-labels-idx1-ubyte.gz`_: Training set labels (28881 bytes)
+
+* `t10k-images-idx3-ubyte.gz`_: Test set images (1648877 bytes)
+
+* `t10k-labels-idx1-ubyte.gz`_: Test set labels (4542 bytes)
+
+Run the Jupyter machine learning example code
+*********************************************
+
+With |CL|, Jupyter, and TensorFlow installed and configured, we can
+run the example code.
+
+#. Go to the :file:`($HOME)/Notebooks` directory and start Jupyter with the
+   following commands:
+
+   .. code-block:: bash
+
+      cd ~/Notebooks
+
+      jupyter notebook
+
+   The Jupyter server starts and opens a web browser showing the Jupyter file
+   manager with a list of files in the current directory, see figure 1.
+
+   .. figure:: figures/machine-learning-1.png
+      :alt: Jupyter file manager
+
+      Figure 1: The Jupyter file manager shows the list of available files.
+
+#. Click on the :file:`Handwriting` directory. The :file:`MNIST_example.ipynb`
+   file created earlier should be listed there, see figure 2.
+
+   .. figure:: figures/machine-learning-2.png
+      :alt: Example file within the Jupyter file manager
+
+      Figure 2: The example file within the Jupyter file manager.
+
+#. To run the hand writing example, click on the :file:`MNIST_example.ipynb`
+   file to load the notebook, see figure 3.
+
+   .. figure:: figures/machine-learning-3.png
+      :alt: The loaded MNIST_example notebook
+
+      Figure 3: The loaded MNIST_example notebook within the Jupyter file
+      manager.
+
+#. Click the |run-cell| button to execute the code in the current cell and
+   move to the next.
+
+#. Select the :guilabel:`In [2]` cell and click the |run-cell| button to load
+   the MNIST data. The successful output is shown on figure 4.
+
+   .. figure:: figures/machine-learning-4.png
+      :alt: Successful import of MNIST data
+
+      Figure 4: Output after successfully importing the MNIST data.
+
+
+   After the MNIST data was successfully downloaded and extracted into the
+   :file:`mnist` directory within the :file:`($HOME)/Notebooks/Handwriting`
+   directory, four .gz files are present and the four data sets were created:
+   `trainX`, `trainY`, `testX` and `testY`.
+
+#. To inspect the imported data, the function in :guilabel:`In [3]` first
+   instructs Jupyter to reshape the data into an array of 28 x 28 images and to
+   plot the area in a 28 x 28 grid. Click the |run-cell| button twice to show
+   the first two digits in the `trainX` dataset, see figure 5.
+
+   .. figure:: figures/machine-learning-5.png
+      :alt: Function to reshape data.
+
+      Figure 5: A function reshapes the data and displays the first two
+      digits in the `trainX` dataset.
+
+#. The :guilabel:`In [4]` cell defines the neural network. It provides the
+   inputs, defines the hidden layers, runs the training model, and sets up
+   the output layer, see figure 6. Click the |run-cell| button four times to
+   perform these operations.
+
+   .. figure:: figures/machine-learning-6.png
+      :alt: Defining, building and training the neural network model
+
+      Figure 6: Defining, building and training the neural network model.
+
+#. To test the accuracy of the prediction the system makes, select the
+   :guilabel:`In [8]` cell and click the |run-cell| button. In this example,
+   the number 6 was predicted with a 99% accuracy, see figure 7.
+
+   .. figure:: figures/machine-learning-7.png
+      :alt: Prediction example
+
+      Figure 7: The system predicts a number providing the accuracy of the
+      prediction.
+
+   .. note::
+
+      To retest the accuracy of a random data point's prediction, run the
+      cell :guilabel:`In [8]` again. It will take another random data point
+      and predict its value.
+
+#. To check the accuracy for the whole dataset, select the :guilabel:`In [10]`
+   cell and click the |run-cell| button. Our example's accuracy is
+   calculated as 97.17%, see figure 8.
+
+   .. figure:: figures/machine-learning-8.png
+      :alt: System's accuracy
+
+      Figure 8: The system's accuracy for the entire data set.
+
+For more in-depth information on the model used and the mathematics it entails,
+visit the TensorFlow tutorials
+`TensorFlow MNIST beginners demo`_ and `TensorFlow MNIST pros demo`_.
+
+**Congratulations!**
+
+You have successfully installed a Jupyter kernel on |CL|. In addition, you
+trained a neural network to successfully predict the values contained in a
+data set of hand-written number images.
+
+Related topics
+**************
+
+* `MNIST Database website`_
+* `TensorFlow MNIST beginners demo`_
+* `TensorFlow MNIST pros demo`_
+* `Jupyter main website`_
+* `Jupyter documentation`_
+* `MNIST at Wikipedia`_
+
+.. _MNIST Database website:
+   http://yann.lecun.com/exdb/mnist/
+
+.. _train-images-idx3-ubyte.gz:
+   http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
+
+.. _train-labels-idx1-ubyte.gz:
+   http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
+
+.. _t10k-images-idx3-ubyte.gz:
+   http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
+
+.. _t10k-labels-idx1-ubyte.gz:
+   http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
+
+.. _Jupyter main website: http://jupyter.org/
+
+.. _Jupyter documentation:  https://jupyter.readthedocs.io/en/latest/index.html
+
+.. _TensorFlow MNIST beginners demo:
+   https://www.tensorflow.org/get_started/mnist/beginners
+
+.. _TensorFlow MNIST pros demo:
+   https://www.tensorflow.org/get_started/mnist/pros
+
+.. _MNIST at Wikipedia:
+   https://en.wikipedia.org/wiki/MNIST_database
+
+.. |run-cell| image::  ./figures/run-cell-button.png
@@ -0,0 +1,140 @@
+.. _multi-boot-mint:
+
+Install Linux Mint\* 18.1 *Serena* MATE
+#######################################
+
+This guide describes Linux Mint-specific details of the :ref:`multi-boot`
+tutorial.
+
+#. Start the Mint installer and follow the prompts.
+
+#. At the :guilabel:`Installation type` screen, choose
+   :guilabel:`Something else`. See Figure 1.
+
+   .. figure:: figures/multi-boot-mint-1.png
+
+      Figure 1: Mint: Installation type.
+
+#. Create a new root partition.
+
+   #. Under the :guilabel:`Device` column, select :guilabel:`free space`. See
+      Figure 2.
+
+      .. figure:: figures/multi-boot-mint-2.png
+
+         Figure 2: Mint: Add partition.
+
+   #. Click the :guilabel:`+` button.
+
+   #. In the :guilabel:`Size` field, enter a value for the new partition
+      size. For this example, we used *40000 MB*, as shown in Figure 3.
+
+      .. figure:: figures/multi-boot-mint-3.png
+
+         Figure 3: Mint: Configure new partition settings.
+
+   #. Set :guilabel:`Use as` to :guilabel:`Ext4 journaling file system`.
+
+   #. Set the :guilabel:`Mount point` to :guilabel:`/`.
+
+   #. Click :guilabel:`OK`.
+
+#. Share the swap partition created by |CL|.
+
+   #. Under the :guilabel:`Device` column, select :file:`/dev/sda2`.
+
+   #. Click :guilabel:`Change`.
+
+   #. Confirm :guilabel:`Use as` is set to :guilabel:`Swap area`. See Figure 4.
+
+      .. figure:: figures/multi-boot-mint-4.png
+
+         Figure 4: Mint: Set swap partition.
+
+#. Follow the remaining prompts to complete the Mint installation.
+
+#. At this point, you cannot boot |CL| because `Grub`
+   is the default boot loader. Follow these steps to make the |CL|
+   Systemd-Boot the default boot loader and add Mint as a boot option.
+
+   #. Boot into Mint.
+
+   #. Log in.
+
+   #. Locate the Mint :file:`grub.cfg` file in the :file:`/boot/grub/`
+      directory and look for the :guilabel:`menuentry` section. In Figure 5, the
+      highlighted lines identify the kernel, the :file:`initrd` files, the root
+      partition UUID, and the additional parameters used. Use this information
+      to create a new Systemd-Boot entry for Mint.
+
+      .. figure:: figures/multi-boot-mint-5.png
+
+         Figure 5: Mint: grub.cfg file.
+
+   #. Copy the kernel and :file:`initrd` file to the EFI partition.
+
+      .. code-block:: bash
+
+         sudo cp /boot/vmlinuz-4.4.0-53-generic /boot/efi
+
+         sudo cp /boot/initrd.img-4.4.0-53-generic /boot/efi
+
+   #. Create a boot entry for Mint. At a minimum, the file must contain
+      these settings:
+
+      +---------+------------------------------------+
+      | Setting | Description                        |
+      +=========+====================================+
+      | title   | Text to show in the boot menu      |
+      +---------+------------------------------------+
+      | linux   | Linux kernel image                 |
+      +---------+------------------------------------+
+      | initrd  | initramfs image                    |
+      +---------+------------------------------------+
+      | options | Options to pass to the EFI program |
+      |         | or kernel boot parameters          |
+      +---------+------------------------------------+
+
+      See the `systemd boot loader documentation`_ for additional
+      details.
+
+      The *options* parameters must specify the root partition UUID and
+      any additional parameters that Mint requires.
+
+      .. note:: The root partition UUID used below is unique to this example.
+
+      .. code-block:: bash
+
+         sudoedit /boot/efi/loader/entries/mint.conf
+
+      Add the following lines to the :file:`mint.conf` file:
+
+      .. code-block:: console
+
+         title Mint 18.1 Serena MATE
+
+         linux /vmlinuz-4.4.0-53-generic
+
+         initrd /initrd.img-4.4.0-53-generic
+
+         options root=UUID=af4901e1-6238-470a-8c14-bc0f0f7715ec ro
+
+#. Re-install Systemd-Boot to make it the default boot loader.
+
+   .. code-block:: bash
+
+      sudo bootctl install --path /boot/efi
+
+   .. note::
+      If an older version of Mint does not have the `bootctl` command,
+      skip this step and see :ref:`multi-boot-restore-bl` to restore
+      Systemd-Boot.
+
+#. Reboot.
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
+
+
+.. _systemd boot loader documentation:
+   https://wiki.archlinux.org/index.php/Systemd-boot
@@ -0,0 +1,58 @@
+.. _multi-boot-restore-bl:
+
+Restore the |CL-ATTR| boot loader
+###################################
+
+This guide is part of the :ref:`multi-boot` tutorial. If you install a new
+:abbr:`OS (operating system)` or upgrade an existing OS, the default boot
+loader may change from |CL| Systemd-Boot. This guide describes how to restore
+Systemd-Boot.
+
+#. Boot the |CL| installer from a USB thumb drive. See :ref:`bootable-usb`.
+
+#. At the introduction screen, press :kbd:`Control+Alt+F2` to bring up the
+   |CL| console. See Figure 1.
+
+   .. figure:: figures/multi-boot-restore-bl-1.png
+
+      Figure 1: |CL|: Console.
+
+#. Log in as *root*.
+
+   .. note::
+      When you log in for the first time as *root* through the console, you must
+      set a new password.
+
+#. Find the location of the |CL| EFI partition. In this example, it is
+   :file:`/dev/sda3`. See Figure 2.
+
+   .. code-block:: bash
+
+      fdisk -l
+
+   .. figure:: figures/multi-boot-restore-bl-2.png
+
+      Figure 2: |CL|: fdisk -l command.
+
+#. Mount the EFI partition.
+
+   .. code-block:: bash
+
+      mount /dev/sda3 /mnt
+
+#. Re-install Systemd-Boot to make it the default boot loader.
+
+   .. code-block:: bash
+
+      bootctl install --path /mnt
+
+#. Unmount the EFI partition.
+
+   .. code-block:: bash
+
+      umount /mnt
+
+#. Reboot.
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
@@ -0,0 +1,165 @@
+.. _multi-boot-rhel:
+
+Install Red Hat\* Enterprise Linux 7.4 Beta
+###########################################
+
+This guide describes Red Hat-specific details of the :ref:`multi-boot`
+tutorial.
+
+#. Start the Red Hat installer and follow the prompts.
+
+#. At the :guilabel:`INSTALLATION SUMMARY` screen, choose
+   :guilabel:`INSTALLATION DESTINATION`. See Figure 1.
+
+   .. figure:: figures/multi-boot-rhel-1.png
+
+      Figure 1: Red Hat: Installation summary.
+
+#. In the :guilabel:`Device Selection` section, select a drive on which to
+   install the OS. See Figure 2.
+
+   .. figure:: figures/multi-boot-rhel-2.png
+
+      Figure 2: Red Hat: Installation destination.
+
+#. Under the :guilabel:`Other Storage Options` section, choose
+   :guilabel:`I will configure partitioning`. See Figure 2.
+
+#. Click :guilabel:`Done`.
+
+#. Under the :menuselection:`New Red Hat Enterprise Linux 7.4 Installation
+   --> New mount points will use the following partitioning scheme` section,
+   select :menuselection:`Standard Partition` from the drop down list. See
+   Figure 3.
+
+   .. figure:: figures/multi-boot-rhel-3.png
+
+      Figure 3: Red Hat: New partition scheme.
+
+#. Create a new root partition.
+
+   #. Click the :menuselection:`+` button on the lower left corner.
+
+   #. Enter `/` and the new partition size. For this example, we specified 45
+      GB. See Figure 4.
+
+      .. figure:: figures/multi-boot-rhel-4.png
+
+         Figure 4: Red Hat: Create new root partition.
+
+   #. Click :guilabel:`Add mount point`.
+
+#. Share the swap partition that was created by |CL|. See Figure 5.
+
+   #. Expand :guilabel:`Unknown`.
+
+   #. Select :guilabel:`swap / sda2`.
+
+   #. Select :guilabel:`Reformat`.
+
+   #. Click :guilabel:`Update Settings`.
+
+      .. figure:: figures/multi-boot-rhel-5.png
+
+         Figure 5: Red Hat: Configure swap partition.
+
+#. Share the EFI partition that was created by |CL|. See Figure 6.
+
+   #. Expand :guilabel:`Unknown.`
+
+   #. Select :guilabel:`EFI System Partition / sda3`.
+
+   #. Under :guilabel:`Mount Point`, enter `/boot/efi`.
+
+   #. Click :guilabel:`Update Settings`.
+
+      .. figure:: figures/multi-boot-rhel-6.png
+
+         Figure 6: Red Hat: Configure EFI partition.
+
+#. Click :guilabel:`Done`.
+
+#. Follow the remaining prompts to complete the Red Hat installation.
+
+#. At this point, you cannot boot |CL| because `Grub` is the default boot
+   loader. Follow these steps to make the |CL| Systemd-Boot the default boot
+   loader and add Red Hat as a boot option:
+
+   #. Boot into Red Hat.
+
+   #. Log in.
+
+   #. Locate the Red Hat :file:`grub.cfg` file in the
+      :file:`/boot/efi/EFI/redhat/` directory and look for the primary Red
+      Hat :guilabel:`menuentry` section. In Figure 7, the highlighted lines
+      identify the kernel and `initrd` filenames, root partition UUID, and
+      additional parameters used. Use this information to create a
+      new Systemd-Boot entry for Red Hat.
+
+      .. figure:: figures/multi-boot-rhel-7.png
+
+         Figure 7: Red Hat: grub.cfg file.
+
+   #. Copy the kernel and :file:`initrd` file to the EFI partition.
+
+      .. code-block:: bash
+
+         sudo cp /boot/vmlinuz-3.10.0-663.el7.x86_64 /boot/efi
+
+         sudo cp /boot/initramfs-3.10.0-663.el7.x86_64.img /boot/efi
+
+   #. Create a boot entry for Red Hat. At a minimum, the file must contain
+      these settings:
+
+      +---------+---------------------------------------------------+
+      | Setting | Description                                       |
+      +=========+===================================================+
+      | title   | Text to show in the boot menu                     |
+      +---------+---------------------------------------------------+
+      | linux   | Linux kernel image                                |
+      +---------+---------------------------------------------------+
+      | initrd  | initramfs image                                   |
+      +---------+---------------------------------------------------+
+      | options | Options to pass to the EFI program or kernel boot |
+      |         | parameters                                        |
+      +---------+---------------------------------------------------+
+
+      See the `systemd boot loader documentation`_ for additional
+      details.
+
+      The *options* parameters must specify the root partition UUID and any
+      additional parameters that Red Hat requires.
+
+      .. note:: The root partition UUID used below is unique to this example.
+
+         .. code-block:: bash
+
+            sudoedit /boot/efi/loader/entries/redhat.conf
+
+      Add the following lines to the :file:`redhat.conf` file:
+
+      .. code-block:: console
+
+         title Red Hat Enterprise Linux 7.4 Beta
+
+         linux /vmlinuz-3.10.0-663.el7.x86_64
+
+         initrd /initramfs-3.10.0-663.el7.x86_64.img
+
+         options root=UUID=30655c74-6cc1-4c55-8fcc-ac8bddcea4db ro
+         crashkernel=auto rhgb LANG=en_US.UTF-8
+
+   #. Re-install Systemd-Boot to make it the default boot loader.
+
+      .. note::
+         This version of Red Hat does not support `bootctl install`. Perform
+         the steps in :ref:`multi-boot-restore-bl` instead.
+
+   #. Reboot.
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
+
+
+.. _systemd boot loader documentation:
+   https://wiki.archlinux.org/index.php/Systemd-boot
@@ -0,0 +1,124 @@
+.. _multi-boot-sles:
+
+Install SUSE\* Linux Enterprise Server 12 SP2
+#############################################
+
+This guide describes SUSE-specific details of the :ref:`multi-boot`
+tutorial.
+
+#. Start the SUSE installer and follow the prompts.
+
+#. At the :guilabel:`Suggested Partitioning` screen, choose
+   :guilabel:`Expert Partitioner`. See Figure 1.
+
+   .. figure:: figures/multi-boot-sles-1.png
+
+      Figure 1: SUSE: Suggested partitioning.
+
+   **Optional:** Under :guilabel:`Available Storage on Linux` section,
+   right-click the SUSE :file:`/home` partition and delete it. In this example, it is :file:`/dev/sda8`. See Figure 2.
+
+   .. figure:: figures/multi-boot-sles-2.png
+
+      Figure 2: SUSE: Delete /home partition.
+
+#. Under :guilabel:`Available Storage on Linux` section, right-click the SUSE
+   root partition and resize it. In this example, :file:`/dev/sda7` is
+   resized to 45 GB. See Figure 3.
+
+   .. figure:: figures/multi-boot-sles-3.png
+
+      Figure 3: SUSE: Resize root partition.
+
+#. Click :guilabel:`Accept`.
+
+#. Follow the remaining prompts to complete the SUSE installation.
+
+#. At this point, you cannot boot |CL| because `Grub`
+   is the default boot loader. Follow these steps to make the |CL|
+   Systemd-Boot the default boot loader and add SUSE as a boot option:
+
+   #. Boot into SUSE.
+
+   #. Log in.
+
+   #. Locate the SUSE :file:`grub.cfg` file in the :file:`/boot/grub2/` directory
+      and look for the primary SUSE :guilabel:`menuentry` section. In Figure 4, the
+      highlighted lines identify the kernel, the :file:`initrd` filenames, the
+      root partition UUID, and the additional parameters used. Use this information
+      to create a new Systemd-Boot entry for SUSE.
+
+      .. figure:: figures/multi-boot-sles-4.png
+
+         Figure 4: SUSE: grub.cfg file.
+
+   #. Copy the kernel and the :file:`initrd` file to the EFI partition.
+
+      .. code-block:: bash
+
+         sudo cp /boot/vmlinuz-4.4.21-69-default /boot/efi
+
+         sudo cp /boot/initrd-4.4.21-69-default /boot/efi
+
+   #. Create a boot entry for SUSE. At a minimum, the file must contain
+      these settings:
+
+      +---------+---------------------------------------+
+      | Setting | Description                           |
+      +=========+=======================================+
+      | title   | Text to show in the boot menu         |
+      +---------+---------------------------------------+
+      | linux   | Linux kernel image                    |
+      +---------+---------------------------------------+
+      | initrd  | initramfs image                       |
+      +---------+---------------------------------------+
+      | options | Options to pass to the EFI program or |
+      |         | kernel boot parameters                |
+      +---------+---------------------------------------+
+
+      See the `systemd boot loader documentation`_ for additional
+      details.
+
+      The *options* parameter must specify the root partition UUID and
+      any additional parameters SUSE requires.
+
+      .. note:: The root partition UUID used below is unique to this example.
+
+         .. code-block:: bash
+
+            sudoedit /boot/efi/loader/entries/suse.conf
+
+         Add the following lines to the :file:`suse.conf` file:
+
+            .. code-block:: console
+
+               title SUSE Linux Enterprise 12 SP2
+
+               linux /vmlinuz-4.4.21-69-default
+
+               initrd /initrd-4.4.21-69-default
+
+               options root=UUID=b9e25e98-a644-4ac3-b955-ae32800ee350 ro
+               resume=/dev/disk/by-uuid/6a50c032-1c1e-4b4a-b799-ca365bb10dc7
+               splash=silent showopts crashkernel=109M,high
+               crashkernel=72M,low
+
+#. Re-install Systemd-Boot to make it the default boot loader.
+
+   .. code-block:: bash
+
+      sudo bootctl install --path /boot/efi
+
+   .. note::
+      If an older version of SUSE does not have the `bootctl` command,
+      skip this step and see :ref:`multi-boot-restore-bl` to restore
+      Systemd-Boot.
+
+#. Reboot.
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
+
+
+.. _systemd boot loader documentation:
+   https://wiki.archlinux.org/index.php/Systemd-boot
@@ -0,0 +1,142 @@
+.. _multi-boot-ubuntu:
+
+Install Ubuntu\* 16.04 LTS Desktop
+##################################
+
+This guide describes Ubuntu-specific details of the :ref:`multi-boot`
+tutorial.
+
+#. Start the Ubuntu installer and follow the prompts.
+
+#. At the :guilabel:`Installation type` screen, choose
+   :guilabel:`Something else`. See Figure 1.
+
+   .. figure:: figures/multi-boot-ubuntu-1.png
+
+      Figure 1: Ubuntu: Installation type.
+
+#. Create a new root partition.
+
+   #. Under the :guilabel:`Device` column, select :guilabel:`free space`. See
+      Figure 2.
+
+      .. figure:: figures/multi-boot-ubuntu-2.png
+
+         Figure 2: Ubuntu: Add partition.
+
+   #. Click the :guilabel:`+` button on the lower left corner.
+
+   #. Enter the new partition size. For this example, we used *40000 MB*, as
+      shown in Figure 3.
+
+      .. figure:: figures/multi-boot-ubuntu-3.png
+
+         Figure 3: Ubuntu: Configure new root partition.
+
+   #. Set :guilabel:`Use as` to :guilabel:`Ext4 journaling file system`.
+
+   #. Set the :guilabel:`Mount point` to `/`.
+
+   #. Click :guilabel:`OK`.
+
+   #. Under the :guilabel:`Format?` column, select the new partition to be
+      formatted, in this example :file:`/dev/sda8`.
+
+#. Share the swap partition that was created by |CL|.
+
+   #. Under the :guilabel:`Device` column, select :file:`/dev/sda2`.
+
+   #. Click :guilabel:`Change`.
+
+   #. Confirm :guilabel:`Use as` is set to :guilabel:`swap area`. See Figure 4.
+
+      .. figure:: figures/multi-boot-ubuntu-4.png
+
+         Figure 4: Ubuntu: Set swap partition.
+
+#. Follow the remaining prompts to complete the Ubuntu installation.
+
+#. At this point, you cannot boot |CL| because `Grub`
+   is the default boot loader. Follow these steps to make the |CL|
+   Systemd-Boot the default boot loader and add Ubuntu as a boot option:
+
+   #. Boot into Ubuntu.
+
+   #. Log in.
+
+   #. Locate the Ubuntu :file:`grub.cfg` file in the :file:`/boot/grub/`
+      directory and look for the :guilabel:`menuentry` section. In Figure 5, the
+      highlighted lines identify the kernel, the :file:`initrd` files, the
+      root partition UUID, and the additional parameters used. Use this
+      information to create a new Systemd-Boot entry for Ubuntu.
+
+      .. figure:: figures/multi-boot-ubuntu-5.png
+
+         Figure 5: Ubuntu: grub.cfg file.
+
+   #. Copy the kernel and the :file:`initrd` file to the EFI partition.
+
+      .. code-block:: bash
+
+         sudo cp /boot/vmlinuz-4.8.0-36-generic.efi.signed /boot/efi
+
+         sudo cp /boot/initrd.img-4.8.0-36-generic /boot/efi
+
+   #. Create a boot entry for Ubuntu. At a minimum, the file must contain
+      these settings:
+
+      +---------+------------------------------------+
+      | Setting | Description                        |
+      +=========+====================================+
+      | title   | Text to show in the boot menu      |
+      +---------+------------------------------------+
+      | linux   | Linux kernel image                 |
+      +---------+------------------------------------+
+      | initrd  | initramfs image                    |
+      +---------+------------------------------------+
+      | options | Options to pass to the EFI program |
+      |         | or kernel boot parameters          |
+      +---------+------------------------------------+
+
+      See the `systemd boot loader documentation`_ for additional
+      details.
+
+      The *options* parameters must specify the root partition UUID and
+      any additional parameters that Ubuntu requires.
+
+      .. note:: The root partition UUID used below is unique to this example.
+
+      .. code-block:: bash
+
+         sudoedit /boot/efi/loader/entries/ubuntu.conf
+
+      Add the following lines to the :file:`ubuntu.conf` file:
+
+      .. code-block:: console
+
+         title Ubuntu 16.04 LTS Desktop
+
+         linux /vmlinuz-4.8.0-36-generic.efi.signed
+
+         initrd /initrd.img-4.8.0-36-generic
+
+         options root=UUID=17f0aa66-3467-4f99-b92c-8b2cea1045aa ro
+
+#. Re-install Systemd-Boot to make it the default boot loader.
+
+   .. code-block:: bash
+
+      sudo bootctl install --path /boot/efi
+
+   .. note::
+      If an older version of Ubuntu does not have the `bootctl` command,
+      skip this step and see :ref:`multi-boot-restore-bl` to restore
+      Systemd-Boot.
+
+#. Reboot.
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
+
+.. _systemd boot loader documentation:
+   https://wiki.archlinux.org/index.php/Systemd-boot
@@ -0,0 +1,46 @@
+.. _multi-boot-win:
+
+Install Windows\* Server 2016
+#############################
+
+This guide describes Windows-specific details of the :ref:`multi-boot`
+tutorial.
+
+#. Start the Windows installer and follow the prompts.
+
+#. At the :guilabel:`Type of installation` screen, choose
+   :guilabel:`Custom: Install Windows only (advanced)`. See Figure 1.
+
+   .. figure:: figures/multi-boot-win-1.png
+
+      Figure 1: Windows: Choose installation type.
+
+#. Select :guilabel:`Unallocated Space` and create a new partition of the
+   desired size. In this example, we specified 50000 MB. See Figure 2.
+
+   .. figure:: figures/multi-boot-win-2.png
+
+      Figure 2: Windows: Create new partition.
+
+   .. note::
+      Windows creates its own 100 MB EFI partition if none exists.
+      In this example, Windows sees the EFI partition created during the
+      |CL| installation and does not create one.
+
+#. Select the newly created partition and follow the remaining prompts
+   to complete the Windows installation. See Figure 3.
+
+   .. figure:: figures/multi-boot-win-3.png
+
+      Figure 3: Windows: Install on newly created partition.
+
+#. Finish the Windows out-of-box-experience process.
+
+#. At this point, you cannot boot |CL| because Windows is the
+   default boot loader. See :ref:`multi-boot-restore-bl` to restore
+   Systemd-Boot and add Windows to its boot menu.
+
+
+If you want to install other :abbr:`OSes (operating systems)`, refer to
+:ref:`multi-boot` for details.
+
@@ -0,0 +1,266 @@
+.. _multi-boot:
+
+Multi-boot |CL-ATTR| with other operating systems
+#################################################
+
+|CL-ATTR| uses the Systemd-Boot boot loader, which does not support multi-
+booting without manual manipulation. This tutorial shows how to configure the
+|CL| boot loader to work with other :abbr:`OSes (operating systems)`.
+
+Process overview
+****************
+
+The process to install other operating systems for a multi-booting computer is
+described below. Install |CL| first, then install other operating systems in
+any order.
+
+#. Install |CL| first with a EFI partition large enough to store the kernels
+   of other operating systems and their initrds, in the case of Linux
+   distributions.
+
+#. Install the next operating system without creating its own EFI
+   partition.
+
+#. Boot into the newly installed operating system.
+
+#. For Linux distributions, copy its kernel and `initrd` to the |CL| EFI
+   partition. This step is not needed for Windows\*.
+
+#. Add an entry for the newly installed operating system in the
+   Systemd-Boot menu.
+
+#. Make Systemd-Boot the default boot loader.
+
+#. Repeat the previous steps to install each additional operating system.
+
+If you update any installed operating systems, be aware that:
+
+*  The default boot loader may change from |CL| Systemd-Boot. Perform the
+   steps in :ref:`multi-boot-restore-bl`.
+
+*  Linux kernels or `initrd` images may change. Keep their corresponding Systemd-Boot
+   :file:`/boot/efi/loader/entries/*.conf` files up-to-date.
+
+This process is not guaranteed to work with all Linux distributions and all
+their versions. The next section lists the OSes that we tested.
+
+
+Tested operating systems
+************************
+
+The following operating systems were tested on an Intel® NUC6i7KYK with 32GB
+RAM and a 360GB SSD. Table 1 lists the information specific to the
+installation of the tested operating systems.
+
+.. csv-table:: Table 1: OS specific installation information
+   :header: # , OS, Version, Partition Size [#]_, Swap Size [#]_, EFI Partition Size [#]_, Download Link
+
+   1,Clear Linux,16140,50 GB,8 GB,1 GB,https://cdn.download.clearlinux.org/releases/16140/clear/
+   2,Windows,Server 2016,50 GB,N/A,Shared with #1,https://www.microsoft.com/en-us/cloud-platform/windows-server
+   3,Red Hat\*,Server 7.4 Beta,45 GB,Shared with #1,Shared with #1,https://access.redhat.com/downloads/
+   4,SUSE\*,Server 12 SP2,45 GB,Shared with #1,Shared with #1,https://www.suse.com/download-linux/
+   5,Ubuntu\*,16.04.02 LTS Desktop,40 GB,Shared with #1,Shared with #1,https://www.ubuntu.com/download/desktop
+   6,Linux Mint\*,18.1 *Serena* MATE,40 GB,Shared with #1,Shared with #1,https://linuxmint.com/edition.php?id=228
+
+Table notes:
+
+.. [#] Configure the partition size as desired.
+
+
+.. [#] To save disk space, share a single swap partition between
+   multiple Linux installations. Swap size was determined using these
+   `recommended swap partition sizes`_.
+
+
+.. [#] The EFI partition holds the kernel and boot information for |CL| and
+   other operating systems. The partition size is dependent on the number
+   of operating systems to be installed. In general, allocate about 100 MB
+   per operating system. For this tutorial, we used 1 GB.
+
+
+
+.. _multi-boot-detail-proc:
+
+Detailed procedures
+*******************
+
+*  :ref:`multi-boot-cl` (below)
+
+.. toctree::
+   :maxdepth: 2
+
+   multi-boot-win
+   multi-boot-rhel
+   multi-boot-sles
+   multi-boot-ubuntu
+   multi-boot-mint
+   multi-boot-restore-bl
+
+
+.. _multi-boot-cl:
+
+Install |CL|
+************
+
+Navigation tips for text-based installation interfaces:
+
+*  Use the :kbd:`Up Arrow` and :kbd:`Down Arrow` keys to move between
+   the options on the screen.
+
+*  Use the :kbd:`Space` to select or highlight an option.
+
+*  Press :kbd:`Enter` to activate the selected option and to move ahead.
+
+Installation details
+====================
+
+#. Create a bootable USB drive of the |CL| installer using one of the methods
+   below.
+
+   * :ref:`bootable-usb-linux`
+   * :ref:`bootable-usb-mac`
+   * :ref:`bootable-usb-windows`
+
+#. Start the |CL| installer and follow the prompts.
+
+#. On the :guilabel:`Choose Installation Type` screen, choose
+   :guilabel:`Manual (Advanced)`, as shown in Figure 1.
+
+   .. figure:: figures/multi-boot-01.png
+
+      Figure 1: |CL| installer: Choose installation type screen.
+
+#. On the :guilabel:`Choose partitioning method` screen, choose
+   :guilabel:`Manually configure mounts and partitions`, as shown in
+   Figure 2.
+
+   .. figure:: figures/multi-boot-02.png
+
+      Figure 2: |CL|: Choose partitioning method.
+
+#. Select the drive, in this case :file:`/dev/sda`, and press :kbd:`Enter` to
+   go into the `cgdisk` partitioning tool. See Figure 3.
+
+   .. figure:: figures/multi-boot-03.png
+
+   Figure 3: |CL|: Choose drive to partition.
+
+#. Create a new root partition.
+
+   #. Select :guilabel:`New`, as shown in Figure 4.
+
+      .. _multi-boot-04:
+
+      .. figure:: figures/multi-boot-04.png
+
+         Figure 4: |CL|: Create new partition.
+
+   #. Accept the default first sector.
+
+   #. Specify the desired size of the partition. For this example, we
+      specified *50 GB*. See Figure 5.
+
+      .. figure:: figures/multi-boot-05.png
+
+         Figure 5: |CL|: New partition size.
+
+   #. Set the partition type to :guilabel:`8300 (Linux filesystem)`, as shown
+      in Figure 6.
+
+      .. figure:: figures/multi-boot-06.png
+
+         Figure 6: |CL|: Set partition type.
+
+   #. Name the partition :file:`CL-root`. This name makes it easier to
+      identify later. See Figure 7.
+
+      .. figure:: figures/multi-boot-07.png
+
+         Figure 7: |CL|: Name partition.
+
+#. Create a new swap partition as shown in Figure 8.
+
+   .. figure:: figures/multi-boot-08.png
+
+      Figure 8: |CL|: Create swap partition.
+
+   #. Select the *free space* partition located at the bottom of the column.
+
+   #. Select :guilabel:`New`. See :ref:`Figure 4<multi-boot-04>`.
+
+   #. Accept the default first sector.
+
+   #. Specify the desired size of the swap partition. For this example, we
+      used 8 GB. See the `recommended swap partition sizes`_ for guidance.
+
+   #. Set the partition type to :guilabel:`8200 (Linux swap)`.
+
+   #. Name the partition :file:`CL-swap`.
+
+#. Create a new EFI partition as shown in Figure 9.
+
+   .. figure:: figures/multi-boot-09.png
+
+      Figure 9: |CL|: Create EFI partition.
+
+   #. In the :guilabel:`Partition Type` column, select :guilabel:`free space`
+      located at the bottom of the column.
+
+   #. Select :guilabel:`New`. See :ref:`Figure 4<multi-boot-04>`.
+
+   #. Accept the default first sector.
+
+   #. Specify the desired size of the partition. For this example, we used
+      1024 MB. This partition will hold |CL|, the kernels of the other
+      operating systems, and their boot information. Its size depends on the
+      number of installed operating systems. In general, allocate about 100 MB
+      per operating system. For this example, we used 1024 MB.
+
+   #. Set the partition type to :guilabel:`ef00 (EFI partition)`.
+
+   #. Name the partition :file:`CL-EFI`.
+
+#. Select :guilabel:`Write` to apply the new partition table.
+
+#. Select :guilabel:`Quit` to exit the `cgdisk` tool.
+
+#. On the :guilabel:`Set mount points` screen, specify the mount points and
+   format settings as shown in Figure 10.
+
+   .. figure:: figures/multi-boot-10.png
+
+      Figure 10: |CL|: Set mount points.
+
+#. On the :guilabel:`User configuration` screen, select
+   :guilabel:`Create an administrative user`, as shown in Figure 11.
+
+   .. figure:: figures/multi-boot-11.png
+
+      Figure 11: |CL|: User configuration.
+
+#. Select :guilabel:`Add user to sudoers?`, as shown in Figure 12.
+
+   .. figure:: figures/multi-boot-12.png
+
+      Figure 12: |CL|: Add user as sudoer.
+
+#. Follow the remaining prompts to complete the installation and finish
+   the out-of-box-experience for |CL|.
+
+#. Log in.
+
+#. Add a Systemd-Boot timeout period or Systemd-Boot will not present the
+   boot menu of available OSes to choose from and will always boot |CL|.
+
+   .. code-block:: bash
+
+      sudo clr-boot-manager set-timeout 20
+
+      sudo clr-boot-manager update
+
+#. Reboot.
+
+If you want to install other OSes, refer to :ref:`multi-boot-detail-proc`.
+
+.. _recommended swap partition sizes:
+   https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/5/html/Deployment_Guide/ch-swapspace.html
@@ -0,0 +1,287 @@
+.. _nvidia:
+
+Install NVIDIA Drivers
+######################
+
+NVIDIA is a manufacture of graphics processing units (GPU), also known as
+graphics cards. 
+
+NVIDIA devices on Linux have two popular device driver options: the opensource
+drivers from the `nouveau project`_ or the proprietary drivers published by
+NVIDIA. The nouveau drivers are built into the |CL-ATTR| kernel and are loaded
+automatically at system boot if a compatible card is detected. 
+
+These instructions show how to use the proprietary NVIDIA drivers which
+require a manual installation.
+
+.. note::
+  
+   Software installed outside of :ref:`swupd <swupd-about>` is not updated with |CL|
+   updates and must be updated and maintained manually.
+
+
+
+.. contents:: :local:
+    :depth: 2
+
+
+
+Prerequisites 
+*************
+
+* A |CL| system with a desktop installed
+* A NVIDIA device installed
+
+
+Install DKMS
+************
+
+The :ref:`Dynamic Kernel Module System (DKMS)
+<kernel-modules-dkms>` allows the NVIDIA kernel modules to be automatically
+integrated when kernel updates occur in |CL|. 
+
+Install the appropriate DKMS bundle using the instructions below:
+
+.. note::
+   The Long Term Support (LTS) kernel variant is more likely to remain
+   compatible between updates with NVIDIA drivers.
+
+
+.. include:: ../guides/maintenance/kernel-modules-dkms.rst
+   :start-after: kernel-modules-dkms-install-begin:
+   :end-before: kernel-modules-dkms-install-end:
+
+
+Download and install the NVIDIA Drivers
+***************************************
+
+
+Download the NVIDIA Drivers for Linux
+=====================================
+
+#. Identify the model of NVIDIA GPU that is installed.
+
+   .. code-block:: bash
+
+      sudo lshw -C display
+
+
+#. Go to the `NVIDIA Driver Downloads website`_ . Search for and download the
+   appropriate driver based on the model of  NVIDIA GPU you have with *Linux
+   64-bit* selected as the Operating System . 
+
+
+#. Open a terminal and navigate to where the
+   :file:`NVIDIA-Linux-x86_64-<VERSION>.run` file was saved. In this
+   example, it was saved in the Downloads folder.
+
+   .. code-block:: bash
+
+      cd ~/Downloads/
+
+#. Make the :file:`NVIDIA-Linux-x86_64-<VERSION>.run` file executable.
+
+   .. code-block:: bash
+
+      chmod +x :file:`NVIDIA-Linux-x86_64-<VERSION>.run`
+
+
+Disable the nouveau Driver
+==========================
+
+The proprietary NVIDIA driver is incompatible with the nouveau driver and
+needs to be disabled before installation can continue.
+
+#. Disable the nouveau driver by creating a blacklist file under
+   :file:`/etc/modprobe.d` and reboot.
+
+   .. code-block:: bash
+
+      sudo mkdir /etc/modprobe.d
+
+      printf "blacklist nouveau \noptions nouveau modeset=0 \n" | sudo tee --append /etc/modprobe.d/disable-nouveau.conf
+      
+
+#. Reboot the system and log back in. It is normal for the graphical
+   environment to not start with no NVIDIA driver loaded.
+
+
+
+Configure the Dynamic Linker
+============================
+
+The NVIDIA installer will be directed to install files under
+:file:`/opt/nvidia` as much as possible to keep its contents isolated from the
+rest of the |CL| system files under :file:`/usr`.  The dynamic linker will
+need to be configured to use the NVIDIA-provided libraries.
+
+
+#. Configure the dynamic linker to look for and cache shared libraries under
+   :file:`/opt/nvidia/lib` and :file:`/opt/nvidia/lib32`.
+
+   .. code-block:: bash
+      
+      echo "include /etc/ld.so.conf.d/*.conf" |  sudo tee --append /etc/ld.so.conf
+      
+      sudo mkdir /etc/ld.so.conf.d
+      printf "/opt/nvidia/lib \n/opt/nvidia/lib32 \n" | sudo tee --append /etc/ld.so.conf.d/nvidia.conf
+      
+
+
+Install the NVIDIA Drivers
+==========================
+
+
+#. A terminal not running on */dev/tty1* is useful to view uninterrupted
+   installation progress. Switch to a secondary virtual terminal by pushing
+   :command:`CTRL + ALT + F2` or remotely login over SSH. 
+
+
+#. Navigate into the directory where the NVIDIA installer was downloaded.
+
+   .. code-block:: bash
+
+      cd ~/Downloads/   
+
+
+#. Run the installer with the advanced options below.
+
+   .. code-block:: bash
+      
+      sudo ./NVIDIA-Linux-x86_64-<VERSION>.run \
+      --utility-prefix=/opt/nvidia \
+      --opengl-prefix=/opt/nvidia \
+      --compat32-prefix=/opt/nvidia \
+      --compat32-libdir=lib32 \      
+      --x-prefix=/opt/nvidia \
+      --documentation-prefix=/opt/nvidia \
+      --no-precompiled-interface \
+      --no-nvidia-modprobe \
+      --no-distro-scripts \
+      --force-libglx-indirect \
+      --dkms \
+      --silent
+
+
+#. The graphical interface may automatically start after the NVIDIA driver
+   is loaded. Return to the working terminal and log back in if necessary.
+
+
+#. Validate the nvidia kernel modules are loaded.
+
+   .. code-block:: bash
+
+      lsmod | grep ^nvidia
+
+
+#. Run a |CL| system verification to restore files that the NVIDIA installer
+   likely deleted.
+
+   .. code-block:: bash
+
+      sudo swupd verify --quick --fix --bundles=lib-opengl
+
+.. note::
+
+   The NVIDIA software places some files under the :file:`/usr` subdirectory
+   which are not managed by |CL| and conflict with the |CL| stateless design.
+   Although a limited version of :command:`swupd verify --fix` is ran above,
+   other uses of the :command:`swupd verify --fix` command should be avoided
+   with the proprietary NVIDIA drivers installed.
+      
+
+
+
+Updating the NVIDIA Drivers
+***************************
+
+The proprietary NVIDIA drivers are installed manually outside of :ref:`swupd
+<swupd-about>` and must be updated manually when needed.
+
+Updating the NVIDIA drivers follows the same steps as initial installation,
+however the desktop environment must first be stopped so that the drivers are
+not in use. 
+
+#. Follow the steps in `Download the NVIDIA Drivers for Linux`_ section to get
+   the latest NVIDIA drivers.
+
+#. Temporarily set the default boot target to the *multi-user* which is
+   a non-graphical runtime.
+
+   .. code-block:: bash
+
+      sudo systemctl set-default multi-user.target
+
+
+#. Reboot the system and log back in. It is normal for the graphical
+   environment to not start.
+
+#. Follow the steps in `Install the NVIDIA Drivers`_ section to update
+   the NVIDIA drivers. This installation will overwrite the previous NVIDIA
+   drivers and files.
+
+#. Set the default boot target back to the *graphical* target.
+
+   .. code-block:: bash
+
+      sudo systemctl set-default graphical.target
+
+
+#. Reboot the system and log back in. 
+
+#. Trigger a flatpak update which will download the runtime corresponding
+   with the new NVIDIA drivers for flatpak apps requiring it.
+
+   .. code-block:: bash
+
+      flatpak update
+
+
+Uninstalling the NVIDIA Drivers
+*******************************
+
+The NVIDIA drivers and associated software can be uninstalled and nouveau
+driver restored by: 
+
+#. Remove the previously created file :file:`/etc/modprobe.d` that
+   prevents nouveau from loading.
+
+   .. code-block:: bash
+
+      sudo rm /etc/modprobe.d/disable-nouveau.conf
+
+
+#. Run the :command:`sudo /opt/nvidia/bin/nvidia-uninstall`
+
+#. Follow the prompts on the screen and reboot the system. 
+
+
+Debugging Installation of NVIDIA Drivers 
+****************************************
+
+* The NVIDIA driver places installer and uninstaller logs under
+  :file:`/var/log/nvidia-install` and :file:`/var/log/nvidia-uninstall`.
+
+* :file:`NVIDIA-Linux-x86_64-<VERSION>.run --advanced-options` shows many
+  parameters to control installation behavior. 
+
+* :file:`NVIDIA-Linux-x86_64-<VERSION>.run --extract-only` extracts
+  installation files into a directory named
+  :file:`NVIDIA-Linux-x86_64-<VERSION>`. 
+
+
+
+Additional resources
+********************
+
+* `Why aren't the NVIDIA Linux drivers open source? <https://nvidia.custhelp.com/app/answers/detail/a_id/1849/kw/Linux>`_
+
+* `Where can I get support for NVIDIA Linux drivers? <https://nvidia.custhelp.com/app/answers/detail/a_id/44/kw/linux>`_
+
+* `NVIDIA Accelerated Linux Graphics Driver Installation Guides <https://download.nvidia.com/XFree86/Linux-x86_64/>`_
+
+.. _`nouveau project`:  https://nouveau.freedesktop.org/wiki/
+
+.. _`NVIDIA Driver Downloads website`: https://www.nvidia.com/download/index.aspx
+
+
@@ -0,0 +1,80 @@
+.. _smb-desktop:
+
+Connect to Windows\* shared location from |CL-ATTR| desktop
+###########################################################
+
+This tutorial explains how to access an existing shared drive on
+Windows\* via Server Message Block (SMB) / Common Internet File System (CIFS)
+from the |CL| GNOME desktop.  CIFS filesystem is generally used to access
+shared storage locations, or share files.
+
+Prerequisites
+*************
+
+* You have already `set up a shared location on Windows`_
+
+Connect to Windows shared location with Nautilus
+************************************************
+
+#. From the desktop, select :guilabel:`Files` from the application menu.
+
+   .. note::
+
+   	  GNOME Files is also known as `Nautilus`.
+
+#. In :guilabel:`Files`, select :guilabel:`Other Locations`.
+
+   .. figure:: figures/smb-desktop-1.png
+      :scale: 100%
+      :alt: Files, Other Locations
+
+      Figure 1: Files, Other Locations
+
+#. In the lower taskbar, beside :guilabel:`Connect to Server`,
+   enter the file-sharing address using the Windows sharing schema:
+
+   .. code-block:: bash
+
+	    smb://servername/Share
+
+   .. figure:: figures/smb-desktop-2.png
+      :scale: 100%
+      :alt: Connect to Server
+
+      Figure 2: Connect to Server
+
+#. Optional: If there are issues with DNS, you can use an IP address in
+   place of the `servername` above. You must still specify the share.
+
+#. Optional: On the Windows machine, in a CLI, retrieve the IP address by
+   entering the command:
+
+   .. code-block:: bash
+
+      ifconfig
+
+   .. note::
+
+      If using the IP address, assure that it is accessible and secure.
+
+#. Select :guilabel:`Connect`.
+
+#. The server will request authentication, as shown in Figure 3.
+
+   .. figure:: figures/smb-desktop-3.png
+      :scale: 100%
+      :alt: Authentication
+
+      Figure 3: Authentication
+
+#. Log in with the same Windows system credentials for which you granted
+   access to the share.
+
+#. Select the appropriate checkbox to save your credentials. Consider
+   carefully the security risks as a result of your selection.
+
+
+.. _set up a shared location on Windows: https://www.howtogeek.com/176471/how-to-share-files-between-windows-and-linux/
+
+
+
@@ -0,0 +1,131 @@
+.. _clear-samba-share-to-Windows:
+
+Enable simple file sharing with a Windows\* machine using Samba\*
+#################################################################
+
+This tutorial describes how to enable simple file sharing from a system
+running |CL-ATTR| to a Windows machine using Samba. For more advanced sharing,
+refer to the `Samba guide`_.
+
+Prerequisites
+*************
+
+This tutorial assumes you have installed |CL| on your host system. For
+detailed instructions, follow the steps in :ref:`bare-metal-install-desktop`.
+
+Before you install any new packages, update |CL| with the following command:
+
+.. code-block:: bash
+
+   sudo swupd update
+
+
+Set up file sharing
+*******************
+
+#.	Log in and get root privileges.
+
+	.. code-block:: bash
+
+		sudo -s
+
+#.	Add the storage-utils bundle, which includes the Samba binaries.
+
+	.. code-block:: bash
+
+		swupd bundle-add storage-utils
+
+	.. note::
+
+		The os-clr-on-clr bundle also includes the Samba binaries.
+
+#.	Create a configuration file called :file:`/etc/samba/smb.conf`. In this
+	example, `[Downloads]` enables a folder share with a specific user.
+	`[Documents]` enables a folder share with any user. The example assumes that a
+	user account `clearlinuxuser` already exists.
+
+	If `valid users` is not specified, then anyone with a user account on the
+	machine and with their Samba password already set can access the folder.
+	However, the account is only able to access files and folders for which
+	they have appropriate permissions.
+
+	Use :command:`chown` or :command:`chmod` to change either the owner of the
+	file or the permissions to allow other users to access the file.
+
+	.. code-block:: console
+
+		[Global]
+		map to guest = bad user
+
+		[Downloads]
+		path=/home/clearlinuxuser/Downloads
+		read only = no
+		guest ok = no
+		valid users = clearlinuxuser
+
+		[Documents]
+		path=/home/clearlinuxuser/Documents
+		read only = no
+		browsable = yes
+		guest ok = yes
+
+#.	Enable the Samba daemon to start every time.
+
+	.. code-block:: bash
+
+		systemctl enable smb
+		systemctl start smb
+
+#.	Use :command:`smbpasswd` to add the initial password for the user
+	account to access the share. Be aware that Samba maintains its own list of
+	passwords for user accounts. The Samba password list can be different than
+	the password used to log in.
+
+	.. code-block:: bash
+
+		smbpasswd -a clearlinuxuser
+
+Setup is complete and a Windows machine on the same network can access the
+shares. Windows uses the format :file:`\\\\[server IP or hostname]\\folder` to
+access shares. Access the shares directly with Windows Explorer or by
+mapping a network drive.
+
+Use the IP address of the |CL| machine for an easy access method. If the
+|CL| machine is behind an Active Directory domain controller or a DNS server,
+use the hostname of the |CL| machine. For other ways to access shares using a
+hostname instead of an IP address, see `Chapter 7 of the Samba guide`_.
+
+
+Map |CL| drive in Windows
+*************************
+
+#.	Open Windows Explorer and click on the left sidebar on :guilabel:`This PC`
+	to change the options available at the top.
+
+#.	Click the :guilabel:`Map Network Drive` icon and enter the path in the
+	format: :file:`\\\\[server IP or hostname]\\[shared folder]`
+
+#.	Check the box :guilabel:`Connect using different credentials`. Enter
+	the Samba user `clearlinuxuser` and the password created with
+	:command:`smbpasswd`. See Figure 1 for details.
+
+	.. figure:: figures/smb-1.png
+		:scale: 70%
+		:alt: Map a network drive in Windows Explorer
+
+		Figure 1: Map a network drive in Windows Explorer.
+
+When complete, Windows Explorer displays the share drive as shown in Figure 2.
+
+.. figure:: figures/smb-2.png
+	:scale: 70%
+	:alt: View a share drive in Windows Explorer
+
+	Figure 2: View a share drive in Windows Explorer.
+
+
+
+
+
+.. _Samba guide: https://www.samba.org/samba/docs/using_samba/ch00.html
+.. _Chapter 7 of the Samba guide: https://www.samba.org/samba/docs/using_samba/ch07.html
--- a/Show More
+++ b/Show More