Added initial stub for BDC

README.md

@@ -10,9 +10,7 @@ Find a problem? Spot a bug? [Post an issue here](https://github.com/Microsoft/sq
 
 ## SQL Server Engine Workshops
 
-- [Workshop Name](https://github.com/BuckWoody/workshops)
-- [Workshop Name](https://github.com/BuckWoody/workshops)
-- [Workshop Name](https://github.com/BuckWoody/workshops)
+- [SQL Server 2019 Big Data Clusters](./SQL2019BDC/README.md)
 
 
 *Disclaimer*

sqlserver2019bigdataclusters/README.md

@@ -0,0 +1,162 @@
+![](graphics/microsoftlogo.png)
+
+# Workshop: Microsoft SQL Server Big Data Clusters Architecture
+
+#### <i>A Microsoft Course from the SQL Server team</i>
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<dl style="text-align: right;">
+
+  <dt><a href="#about">About this Workshop</a></dt>
+  <dt><a href="#businessapplications">Business Applications of this Workshop</a></dt>
+  <dt><a href="#technologies">Technologies used in this Workshop</a></dt>
+  <dt><a href="#prereqs">Before Taking this Workshop</a></dt>
+  <dt><a href="#details">Workshop Details</a></dt>
+  <dt><a href="#related">Related Workshops</a></dt>
+  <dt><a href="#modules">Workshop Modules</a></dt>
+  <dt><a href="#nextsteps">Next Steps</a></dt>
+
+</dl>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/textbubble.png"> <h2><a name="about">About this Workshop</a></h2>
+
+Welcome to this Microsoft solutions workshop on *Microsoft SQL Server Big Data Clusters Architecture*. In this workshop, you'll learn how SQL Server Big Data Clusters implements large-scale data processing and machine learning, and how to select and plan for the proper architecture to enable machine learning to train your models using Python, R, Java or SparkML to operationalize these models, and how to deploy your intelligent apps side-by-side with their data.
+
+The focus of this workshop is to understand how to deploy an on-premise, hybrid or local environment of a Big Data Cluster, and understand the components of the big data solution architecture.
+
+You'll start by understanding the concepts of big data analytics, and you'll get an overview of the technologies (such as containers, Kubernetes, Spark and HDFS, machine learning, and other technologies) that you will use throughout the workshop. Next, you'll understand the architecture of SQL Server Big Data Clusters. You'll learn how to create external tables over other data sources to unify your data, and how to use Spark to run big queries over your data in HDFS or do data preparation. You'll review a complete solution for an end-to-end scenario, with a focus on how to extrapolate what you have learned to create other solutions for your organization.
+
+This README.MD file explains how the workshop is laid out, what you will learn, and the technologies you will use in this solution.
+
+(You can view all of the [source files for this workshop on this GitHub site, along with other workshops as well. Open this link in a new tab to find out more.](https://github.com/BuckWoody/workshops))
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/checkmark.png"> <h3>Learning Objectives</h3>
+
+In this workshop you'll learn:
+<br>
+
+- When to use Big Data technology
+- The components and technologies of Big Data processing
+- Abstractions such as Containers and Container Management as they relate to SQL Server and Big Data
+- Planning and architecting an on-premises, in-cloud, or hybrid big data solution with SQL Server
+- How to install SQL Server Big Data Clusters on-premises and in the Azure Kubernetes Service (AKS)
+- How to work with Apache Spark
+- The Data Science Process to create an end-to-end solution
+- How to work with the tooling for SQL Server Big Data Clusters (Azure Data Studio)
+- Monitoring and managing SQL Server Big Data Clusters
+- Security considerations for SQL Server Big Data Clusters
+
+Starting in SQL Server 2019, Big Data Clusters allows for large-scale, near real-time processing of data over the HDFS file system and other data sources. It also leverages the Apache Spark framework which is integrated into one environment for management, monitoring, and security of your environment. This means that organizations can implement everything from queries to analysis to Machine Learning and Artificial Intelligence within SQL Server, over large-scale, heterogeneous data. SQL Server Big Data Clusters can be implemented fully on-premises, in the cloud using a Kubernetes service such as Azure's AKS, and in a hybrid fashion. This allows for full, partial, and mixed security and control as desired.
+
+The goal of this workshop is to train the team tasked with architecting and implementing SQL Server Big Data Clusters in the planning, creation, and delivery of a system designed to be used for large-scale data analytics. Since there are multiple technologies and concepts within this solution, the workshop uses multiple types of exercises to prepare the students for this implementation.
+
+The concepts and skills taught in this workshop form the starting points for:
+
+  * Data Professionals and DevOps teams, to implement and operate a SQL Server Big Data Cluster system.
+  * Solution Architects and Developers, to understand how to put together an end-to-end solution.
+  * Data Scientists, to understand the environment used to analyze and solve specific predictive problems.
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/building1.png"> <h2><a name="businessapplications">Business Applications of this Workshop</a></h2>
+
+Businesses require near real-time insights from ever-larger sets of data from a variety of sources. Large-scale data ingestion requires scale-out storage and processing in ways that allow fast response times. In addition to simply querying this data, organizations want full analysis and even predictive capabilities over their data. 
+
+Some industry examples of big data processing are in Retail (*Demand Prediction, Market-Basket Analysis*), Finance (*Fraud detection, customer segmentation*), Healthcare (*Fiscal control analytics, Disease Prevention prediction and classification, Clinical Trials optimization*), Public Sector (*Revenue prediction, Education effectiveness analysis*), Manufacturing (*Predictive Maintenance, Anomaly Detection*) and Agriculture (*Food Safety analysis, Crop forecasting*) to name just a few.
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/listcheck.png"> <h2><a name="technologies">Technologies used in this Workshop</a></h2>
+
+The solution includes the following technologies - although you are not limited to these, they form the basis of the workshop. At the end of the workshop you will learn how to extrapolate these components into other solutions. You will cover these at an overview level, with references to much deeper training provided.
+
+ <table style="tr:nth-child(even) {background-color: #f2f2f2;}; text-align: left; display: table; border-collapse: collapse; border-spacing: 2px; border-color: gray;">
+
+  <tr><th style="background-color: #1b20a1; color: white;">Technology</th> <th style="background-color: #1b20a1; color: white;">Description</th></tr>
+
+  <tr><td><i>Linux</i></td><td>Operating system used in Containers and Container Orchestration</td></tr>
+  <tr><td><i>Docker</i></td><td>Encapsulation level for the SQL Server Big Data Cluster architecture</td></tr>
+  <tr><td><i>Kubernetes</i></td><td>Management, control plane for Containers</td></tr>
+  <tr><td>Microsoft Azure</td><td>Cloud environment for services</td></tr>
+  <tr><td>Azure Kubernetes Service (AKS)</td><td>Kubernetes as a Service</td></tr>
+  <tr><td><i>Apache HDFS</i></td><td>Scale-out storage subsystem</td></tr>
+  <tr><td><i>Apache Knox</i></td><td>The Knox Gateway provides a single access point for all REST interactions, used for security</td></tr>
+  <tr><td><i>Apache Livy</i></td><td>Tob submission system for Apache Spark</td></tr>
+  <tr><td><i>Apache Spark</i></td><td>In-memory large-scale, scale-out data processing architecture used by SQL Server </i></td></tr>
+  <tr><td><i>Python, R, Java, SparkML</i></td><td><i>ML/AI programming languages used for Machine Learning and AI Model creation</i></td></tr>
+  <tr><td>Azure Data Studio</td><td>Tooling for SQL Server, HDFS, Kubernetes cluster management, T-SQL, R, Python, and SparkML languages</td></tr>
+  <tr><td>SQL Server Machine Learning Services</td><td>R, Python and Java extensions for SQL Server</td></tr>
+  <tr><td>Microsoft Data Science Process (TDSP)</td><td>Project, Development, Control and Management framework</td></tr>
+  <tr><td><i>Monitoring and Management</i></td><td>Dashboards, logs, API's and other constructs to manage and monitor the solution</td></tr>
+  <tr><td><i>Security</i></td><td>RBAC, Keys, Secrets, VNETs and Compliance for the solution</td></tr>
+
+</table>
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/owl.png"> <h2><a name="prereqs">Before Taking this Workshop</a></h2>
+
+You'll need a local system that you are able to install software on. The workshop demonstrations use Microsoft Windows as an operating system and all examples use Windows for the workshop. Optionally, you can use a Microsoft Azure Virtual Machine (VM) to install the software on and work with the solution.
+
+You must have a Microsoft Azure account with the ability to create assets, specifically the Azure Kubernetes Service (AKS).
+
+This workshop expects that you understand data structures and working with SQL Server and computer networks. This workshop does not expect you to have any prior data science knowledge, but a basic knowledge of statistics and data science is helpful in the Data Science sections. Knowledge of SQL Server, Azure Data and AI services, Python, and Jupyter Notebooks is recommended. AI techniques are implemented in Python packages. Solution templates are implemented using Azure services, development tools, and SDKs. You should have a basic understanding of working with the Microsoft Azure Platform.
+
+If you are new to these, here are a few references you can complete prior to class:
+
+-  [Microsoft SQL Server](https://docs.microsoft.com/en-us/sql/relational-databases/database-engine-tutorials?view=sql-server-ver15)
+-  [Microsoft Azure](https://docs.microsoft.com/en-us/learn/paths/azure-fundamentals/)
+
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/bulletlist.png"> <h3>Setup</h3>
+
+<a href="SQL2019BDC/00%20-%20Prerequisites.md" target="_blank">A full prerequisites document is located here</a>. These instructions should be completed before the workshop starts, since you will not have time to cover these in class. <i>Remember to turn off any Virtual Machines from the Azure Portal when not taking the class so that you do incur charges (shutting down the machine in the VM itself is not sufficient)</i>.
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/education1.png"> <h2><a name="details">Workshop Details</a></h2>
+
+This workshop uses Azure Data Studio, Microsoft Azure AKS, and SQL Server (2019 and higher) with a focus on architecture and implementation.
+
+<table style="tr:nth-child(even) {background-color: #f2f2f2;}; text-align: left; display: table; border-collapse: collapse; border-spacing: 5px; border-color: gray;">
+
+  <tr><td style="background-color: Cornsilk; color: black; padding: 5px 5px;">Primary Audience:</td><td style="background-color: Cornsilk; color: black; padding: 5px 5px;">System Architects and Data Professionals tasked with implementing Big Data, Machine Learning and AI solutions</td></tr>
+  <tr><td>Secondary Audience:</td><td> Security Architects, Developers, and Data Scientists</td></tr>
+  <tr><td style="background-color: Cornsilk; color: black; padding: 5px 5px;">Level: </td><td style="background-color: Cornsilk; color: black; padding: 5px 5px0;"> 300</td></tr>
+  <tr><td>Type:</td><td>In-Person</td></tr>
+  <tr><td style="background-color: Cornsilk; color: black; padding: 5px 5px;">Length: </td><td style="background-color: Cornsilk; color: black; padding: 5px 5px;">8-9 hours</td></tr>
+
+</table>
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/pinmap.png"> <h2><a name="related">Related Workshops</a></h2>
+
+ - [Technical guide to the Cortana Intelligence Solution Template for predictive maintenance in aerospace and other businesses](https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/cortana-analytics-technical-guide-predictive-maintenance)
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/bookpencil.png"> <h2><a name="modules">Workshop Modules</a></h2>
+
+This is a modular workshop, and in each section, you'll learn concepts, technologies and processes to help you complete the solution.
+
+<table style="tr:nth-child(even) {background-color: #f2f2f2;}; text-align: left; display: table; border-collapse: collapse; border-spacing: 5px; border-color: gray;">
+
+  <tr><td style="background-color: AliceBlue; color: black;"><b>Module</b></td><td style="background-color: AliceBlue; color: black;"><b>Topics</b></td></tr>
+
+  <tr><td><a href="SQL2019BDC/01%20-%20The%20Big%20Data%20Landscape.md" target="_blank">01 - The Big Data Landscape </a></td><td> Overview of the workshop, problem space, solution options and architectures</td></tr>
+  <tr><td style="background-color: AliceBlue; color: black;"><a href="SQL2019BDC/02%20-%20SQL%20Server%20BDC%20Components.md" target="_blank">02 - SQL Server BDC Components</a> </td><td td style="background-color: AliceBlue; color: black;"> Abstraction levels, frameworks, architectures and components within SQL Server Big Data Clusters</td></tr>
+  <tr><td><a href="SQL2019BDC/03%20-%20Planning,%20Installation%20and%20Configuration.md" target="_blank">03 - Planning, Installation<br> and Configuration</a> </td><td> Mapping the requirements to the architecture design, constraints, and diagrams</td></tr>
+  <tr><td style="background-color: AliceBlue; color: black;"><a href="SQL2019BDC/04%20-%20Operationalization.md" target="_blank">04 - Operationalization</a> </td><td style="background-color: AliceBlue; color: black;"> Connecting applications to the solution; DDL, DML, DCL</td></tr>
+  <tr><td><a href="SQL2019BDC/05%20-%20Management%20and%20Monitoring.md" target="_blank">05 - Management and <br> Monitoring</a> </td><td> Tools and processes to manage the Big Data Cluster</td></tr>
+  <tr><td style="background-color: AliceBlue; color: black;"><a href="SQL2019BDC/06%20-%20Security.md" target="_blank">06 - Security</a> </td><td style="background-color: AliceBlue; color: black;"> Access and Authentication to the various levels of the solution</td></tr>
+
+</table>
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="./graphics/geopin.png"><b><a name="nextsteps">Next Steps</a></b></p>
+
+Next, Continue to <a href="SQL2019BDC/00%20-%20Prerequisites.md" target="_blank"><i> prerequisites</i></a>

sqlserver2019bigdataclusters/SQL2019BDC/00 - Prerequisites.md

@@ -0,0 +1,198 @@
+![](../graphics/microsoftlogo.png)
+
+# Workshop: Microsoft SQL Server Big Data Clusters Architecture
+
+#### <i>A Microsoft Course from the SQL Server team</i>
+
+<p style="border-bottom: 1px solid lightgrey;"></p>
+
+<img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/textbubble.png"> <h2>00 prerequisites</h2>
+
+The "Microsoft SQL Server Big Data Clusters Architecture" workshop is taught using the following components, which you will install and configure in the sections that follow. 
+
+*(Note: Due to the nature of working with large-scale systems, it may not be possible for you to set up everything you need to perform each lab exercise.  Participation in each Activity is optional - we will be working through the exercises together, but if you cannot install any software or don't have an Azure account, the instructor will work through each exercise in the workshop. You will also have full access to these materials so that you can work through them later when you have more time and resources.)*
+
+For this workshop, you will use Microsoft Windows as the base workstation, although Apple and Linux operating systems can be used in production. You can <a href="https://developer.microsoft.com/en-us/windows/downloads/virtual-machines" target="_blank">download a Windows 10 Workstation Image for VirtualBox, Hyper-V, VMWare, or Parallels for free here</a>. 
+
+The other requirements are:
+
+- **Microsoft Azure**: This workshop uses the Microsoft Azure platform to host the Kubernetes cluster (using the Azure Kubernetes Service), and optionally you can deploy a system there to act as a workstation. You can use a free Azure account, an MSDN Account, your own account, or potentially one provided for you, as long as you can create about $100.00 (U.S.) worth of assets.
+- **SQL Server Big Data Cluster credentials** - As of this writing, you must have an invitation code to install and configure SQL Server Big Data Clusters.
+- **Azure Command Line Interface**: The Azure CLI allows you to work from the command line on multiple platforms to interact with your Azure subscription, and also has control statements for AKS.
+- **Python (3)**: Python version 3.5 (and higher) is used by the SQL Server programs to deploy and manage a SQL Server Big Data Cluster.
+- **The pip3 Package**: The Python package manager *pip3* is used to install various SQL Server BDC deployment and configuration tools. 
+- **The kubectl program**: The *kubectl* program is the command-line control feature for Kubernetes.
+- **The mssqlctl program**: The *mssqlctl* program is the deployment and configuration tool for SQL Server Big Data Clusters.
+- **Azure Data Studio**: The *Azure Data Studio*, along with various Extensions, is used for both the query and management of SQL Server BDC. In addition, you will use this tool to participate in the workshop.
+
+*Note that all following activities must be completed prior to class - there will not be time to perform these operations during the workshop.*
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 1: Set up a Microsoft Azure Account</b></p>
+
+You have multiple options for setting up Microsoft Azure account to complete this workshop. You can use a free account, a Microsoft Developer Network (MSDN) account, a personal or corporate account, or in some cases a pass may be provided by the instructor. (Note: for most classes, the MSDN account is best)
+
+**Unless you are explicitly told you will be provided an account by the instructor in the invitation to this workshop, you must have your Microsoft Azure account and Data Science Virtual Machine set up before you arrive at class.**
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png"><b>Option 1 - Free Account</b></p>
+
+The free account gives you twelve months of time, and a limited amount of resources. Set this up prior to coming to class, and ensure you can access it from the system you will bring to the class.
+
+- [Open this resource, and click the "Start Free" button you see there](https://azure.microsoft.com/en-us/free/)
+
+**NOTE: You can only use the Free subscription once, and it expires in 12 months. Set up your account and create the DSVM per the instructions below, but ensure that you turn off the VM in the Portal to ensure that you do no exceed the cost limits on this account. You will turn it off and on in the classroom per the instructor's directions.**
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png"><b>Option 2 - Microsoft Developer Network Account (MSDN) Account</b></p>
+
+The best way to take this workshop is to use your [Microsoft Developer Network (MSDN) benefits if you have a subscription](https://marketplace.visualstudio.com/subscriptions).
+
+- [Open this resource and click the "Activate your monthly Azure credit" button](https://azure.microsoft.com/en-us/pricing/member-offers/credit-for-visual-studio-subscribers/)
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png"><b>Option 3 - Use Your Own Account</b></p>
+
+You can also use your own account or one provided to you by your organization, but you must be able to create a resource group and create, start, and manage a Data Science Virtual Machine (DSVM) and an Azure AKS cluster. 
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png"><b>Option 4 - Use an account provided by your instructor</b></p>
+
+Your workshop invitation may have instructed you that they will provide a Microsoft Azure account for you to use. If so, you will receive instructions that it will be provided.
+
+**Unless you received explicit instructions in your workshop invitations, you much create either a free, MSDN or Personal account. You must have an account prior to the workshop.**
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 2: Request Access Credentials to SQL Server 2019 BDC features</b></p>
+<br>
+As of this writing, the SQL Server Big Data Cluster feature is enabled for preview customers. You can request access at this site:
+
+https://aka.ms/eapsignup 
+
+When you access that site, put the words **Purpose: SQL Bits 2019 Workshop** in the *Please describe the specific application or workload that you will be testing with SQL Server 2019?* box. You will be automatically approved. For the *Platform*, select **Azure Kubernetes Service (AKS)**.
+
+You will use these credentials in a subsequent step. It can take up to a week to receive your code. 
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 3: Prepare Your Workstation</b></p>
+<br>
+The instructions that follow are the same for either a "base metal" workstation or laptop, or a Virtual Machine. It's best to have at least 4MB or RAM on the management system, and these instructions assume that you are not planning to run the database server or any Containers on the workstation. It's also assumed that you are using a current version of Windows, either desktop or server.
+<br>
+
+*(You can copy and paste all of the commands that follow in a PowerShell window that you run as the system Administrator)*
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png">Updates<p>
+
+First, ensure all of your updates are current. You can use the following commands to do that in an Administrator-level PowerShell session:
+
+<pre>
+write-host "Standard Install for Windows. Classroom or test system only - use at your own risk!"
+Set-ExecutionPolicy RemoteSigned
+
+write-host "Update Windows"
+Install-Module PSWindowsUpdate
+Import-Module PSWindowsUpdate
+Get-WindowsUpdate
+Install-WindowsUpdate
+</pre>
+
+*Note: If you get an error during this update process, evaluate it to see if it is fatal. You may recieve certain driver errors if you are using a Virtual Machine, this can be safely ignored.*
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png">Install Chocolaty Windows package Manager</p>
+
+Next, install the Chocolaty Windows Package manager to aid in command-line installations:
+
+<pre>
+write-host "Install Chocolaty" 
+Set-ExecutionPolicy Bypass -Scope Process -Force; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))
+choco feature enable -n allowGlobalConfirmation
+</pre>
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/checkbox.png">Review Environment Variables</p>
+
+Your environment variables control how the cluster will be built.  
+
+<p><a href="https://docs.microsoft.com/en-us/sql/big-data-cluster/quickstart-big-data-cluster-deploy?view=sqlallproducts-allversions#define-environment-variables" target="_blank">Refer to this documentation for both the latest statements, and for what they need to be set to. These change based on the current release of the Private Preview.</a> Do not set these at this time, just review the page.</p> 
+
+The variables for **name**, **password** and **e-mail** for the Big Data Cluster is provided to you when you request access to the Early Adopter program. 
+
+*(Note that in production, you'll set these environment variables permanently using the Control Panel or by adding them with a Registry command, and may be handled by an improved installation experience)*
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 4: Install Azure CLI</b></p>
+
+The Azure Command Line Utility is used to set up and control Azure resources. Run the following commands in your elevated PowerShell window:
+
+<pre>
+write-host "Install Azure CLI"
+start "https://aka.ms/installazurecliwindows"
+</pre>
+
+You'll need to click the MSI file once it downloads, and take all defaults. 
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 5: Install Python 3 and git</b></p>
+
+While `git` has not been mentioned as a requirement for SQL Server, it's used for the workshop. First you'll install Python.
+
+<pre>
+write-host "Install Python 3"
+choco install python3 
+
+write-host "Install git"
+choco install git
+</pre>
+
+Note: Python can install in multiple locations based on various conditions. To see the Python intepreter location in current use in Windows, type: 
+
+`where python`
+
+(In Linux, `which Python`)
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 6: Install kubectl</b></p>
+
+The `kubectl` program is used to deploy, configure and manage Kubernetes Clusters. It is used in several parts of the Big Data Clusters program.
+
+<pre>
+write-host "Install kubectl"
+choco install kubernetes-cli 
+</pre>
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 7: Install mssqlctl</b></p>
+
+the `mssqlctl` program then deploys the SQL Server Big Data Cluster environment onto Kubernetes. 
+
+<i>Note - you must delete the old version before the class. It is updated quite frequently during the preview phase.</i>
+
+<pre>
+setx path "%path%;C:\Users\<replace with your login name>\AppData\Roaming\Python\Python37\Scripts"
+
+choco upgrade kubernetes-cli
+
+python -m pip install --upgrade pip
+
+pip uninstall mssqlctl
+
+pip install --extra-index-url https://private-repo.microsoft.com/python/ctp-2.2 mssqlctl
+</pre>
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/point1.png"><b>Activity 8: Install Azure Data Studio and Extensions</b></p>
+
+The primary management tool for working with SQL Server Big Data Clusters is Azure Data Studio. You will also use this tool in your workshop.
+
+<pre>
+write-host "Install Azure Data Studio" 
+start "https://go.microsoft.com/fwlink/?linkid=2038320"
+</pre>
+
+Once again, download the MSI and run it from there. It's always a good idea after this many installations to run Windows Update again:
+
+<pre>
+write-host "Re-Update Windows"
+Get-WindowsUpdate
+Install-WindowsUpdate
+</pre>
+
+*Note 1: If you get an error during this update process, evaluate it to see if it is fatal. You may recieve certain driver errors if you are using a Virtual Machine, this can be safely ignored.*
+
+**Note 2: If you are using a Virtual Machine in Azure, power off the Virtual Machine using the Azure Portal every time you are done with it. Turning off the VM using just the Windows power off in the VM only stops it running, but you are still charged for the VM if you do not stop it from the Portal. Stop the VM from the Portal unless you are actively using it.**
+
+<p><img style="margin: 0px 15px 15px 0px;" src="../graphics/owl.png"><b>For Further Study</b></p>
+<ul>
+    <li><a href="https://docs.microsoft.com/en-us/sql/big-data-cluster/big-data-cluster-overview?view=sqlallproducts-allversions" target="_blank">Official Documentation for this section</a></li>
+</ul>
+
+<p><img style="float: left; margin: 0px 15px 15px 0px;" src="../graphics/geopin.png"><b >Next Steps</b></p>
+
+Next, Continue to <a href="01%20-%20The%20Big%20Data%20Landscape.md" target="_blank"><i> 01 - The Big Data Landscape</i></a>.