Merge pull request #109715 from craigcaseyMSFT/vcraic0330a

v-albemi · web-flow · commit 889c080565b8 · 2020-03-31T12:40:11.000-07:00
fix broken links from CATS report
diff --git a/articles/azure-government/documentation-government-csp-list.md b/articles/azure-government/documentation-government-csp-list.md
@@ -40,7 +40,7 @@ Below you can find a list of all the authorized Cloud Solution Providers, which
 |[Alliance Enterprises, Inc.](https://www.allianceenterprises.com)|
 |[Alvarez Technology Group](https://www.alvareztg.com/)|
 |[Amalgama Technologies Inc](http://amalgamatetech.com/)|
-|[Ambonare](https://www.ambonare.com)|
+|[Ambonare](https://www.redriver.com/ambonare)|
 |[American Technology Services](https://networkats.com/)|
 |[Anautics](https://anautics.com)|
 |[APEX TECHNOLOGY MANAGEMENT INC](https://www.apex.com)|
diff --git a/articles/azure-maps/mobility-service-data-structure.md b/articles/azure-maps/mobility-service-data-structure.md
@@ -26,13 +26,13 @@ The `metroID` is a metro area's ID that can be used to call the [Get Metro Area
 
 ## Stop IDs
 
-Transit stops can be referred to by two types of IDs, the [General Transit Feed Specification (GFTS)](https://gtfs.org/) ID and the Azure Maps stop ID. The GFTS ID is referred to as the stopKey and the Azure Maps stop ID is referred to as stopID. When frequently referring to transit stops, you're encouraged to use the Azure Maps stop ID. stopID is more stable and likely to stay the same as long as the physical stop exists. The GTFS stop ID is updated more often. For example, GTFS stop ID can be updated per the GTFS provider request or when a new GTFS version is released. Although the physical stop had no change, the GTFS stop ID may change.
+Transit stops can be referred to by two types of IDs, the [General Transit Feed Specification (GFTS)](http://gtfs.org/) ID and the Azure Maps stop ID. The GFTS ID is referred to as the stopKey and the Azure Maps stop ID is referred to as stopID. When frequently referring to transit stops, you're encouraged to use the Azure Maps stop ID. stopID is more stable and likely to stay the same as long as the physical stop exists. The GTFS stop ID is updated more often. For example, GTFS stop ID can be updated per the GTFS provider request or when a new GTFS version is released. Although the physical stop had no change, the GTFS stop ID may change.
 
 To start, you can request nearby transit stops using [Get Nearby Transit API](https://aka.ms/AzureMapsMobilityNearbyTransit).
 
 ## Line Groups and Lines
 
-Mobility Service uses a parallel data model for Lines and Line Groups. This model is used to better deal with changes inherited from [GTFS](https://gtfs.org/) routes and the trips data.
+Mobility Service uses a parallel data model for Lines and Line Groups. This model is used to better deal with changes inherited from [GTFS](http://gtfs.org/) routes and the trips data.
 
 
 ### Line Groups
diff --git a/articles/cost-management-billing/understand/download-azure-invoice.md b/articles/cost-management-billing/understand/download-azure-invoice.md
@@ -109,7 +109,7 @@ You must have an account admin role on a subscription or a support plan to opt i
     [![Screenshot that shows billing profile list](./media/download-azure-invoice/cmb-email-invoice.png)](./media/download-azure-invoice/cmb-email-invoice-zoomed-in.png#lightbox)
 1. Select **Opt in** and accept the terms.  
     ![Screenshot that shows the opt-in flow step 2](./media/download-azure-invoice/invoice-article-step02.png)
-1. The invoice is sent to your preferred communication email address. You can update the email address in the [contact info of your billing account](https://https://portal.azure.com/#blade/Microsoft_Azure_GTM/ModernBillingMenuBlade/Properties).  
+1. The invoice is sent to your preferred communication email address. You can update the email address in the [contact info of your billing account](https://portal.azure.com/#blade/Microsoft_Azure_GTM/ModernBillingMenuBlade/Properties).  
     ![Screenshot that shows the opt-in flow step 3](./media/download-azure-invoice/invoice-article-step03-verify-email.png)
 
 ## Share your MOSP invoices with others by email
diff --git a/articles/expressroute/expressroute-locations.md b/articles/expressroute/expressroute-locations.md
@@ -94,7 +94,7 @@ The following table shows locations by service provider. If you want to view ava
 | **[Colt](https://www.colt.net/uk/en/news/colt-announces-dedicated-cloud-access-for-microsoft-azure-services-en.htm)** |Supported |Supported |Amsterdam, Amsterdam2, Chicago, Dublin, Frankfurt, London, London2, Newport, New York, Osaka, Paris, Silicon Valley, Silicon Valley2, Singapore2, Tokyo, Washington DC |
 | **[Comcast](https://business.comcast.com/landingpage/microsoft-azure)** |Supported |Supported |Chicago, Silicon Valley, Washington DC |
 | **[CoreSite](https://www.coresite.com/solutions/cloud-services/public-cloud-providers/microsoft-azure-expressroute)** |Supported |Supported |Chicago, Denver, Los Angeles, New York, Silicon Valley, Silicon Valley2, Washington DC, Washington DC2 |
-| **[DE-CIX](https://www.de-cix.net/en/de-cix-service-world/directcloud/find-a-cloud-service/detail/microsoft-azure)** | Supported |Supported |Amsterdam2, Frankfurt, Marseille|
+| **[DE-CIX](https://www.de-cix.net/en/de-cix-service-world/cloud-exchange/find-a-cloud-service/detail/microsoft-azure)** | Supported |Supported |Amsterdam2, Frankfurt, Marseille|
 | **[Devoli](https://devoli.com/expressroute)** | Supported |Supported | Auckland, Melbourne, Sydney |
 | **du datamena** |Supported |Supported | Dubai2 |
 | **eir** |Supported |Supported |Dublin|
@@ -237,7 +237,7 @@ If you are remote and don't have fiber connectivity or you want to explore other
 | **[Altice Business](https://golightpath.com/transport)** |Equinix |New York, Washington DC |
 | **[Arteria Networks Corporation](https://www.arteria-net.com/business/service/cloud/sca/)** |Equinix |Tokyo |
 | **[Axtel](https://alestra.mx/landing/expressrouteazure/)** |Equinix |Dallas|
-| **[Beanfield Metroconnect](https://www.beanfield.com/business/cloud-connect)** |Megaport |Toronto|
+| **[Beanfield Metroconnect](https://www.beanfield.com/business/cloud-exchange)** |Megaport |Toronto|
 | **[Bezeq International Ltd.](https://www.bezeqint.net/english)** | euNetworks | London |
 | **[BICS](https://bics.com/bics-solutions-suite/cloud-connect/)** | Equinix | Amsterdam, Frankfurt, London, Singapore, Washington DC |
 | **[BroadBand Tower, Inc.](https://www.bbtower.co.jp/product-service/data-center/network/dcconnect-for-azure/)** | Equinix | Tokyo |
@@ -260,7 +260,7 @@ If you are remote and don't have fiber connectivity or you want to explore other
 | **[Gulf Bridge International](https://www.gbiinc.com/microsoft-azure-expressroute/)** | Equinix | Amsterdam |
 | **[HSO](https://www.hso.co.uk/products/cloud-direct)** |Equinix | London, Slough |
 | **[IVedha Inc](http://www.ivedha.com/cloud/manage-azure-cloud/express-route-4/)**| Equinix | Toronto |
-| **[Kaalam Telecom Bahrain B.S.C](http://www.kalaam-telecom.com/en/inbusiness/expressroute.html)**| Level 3 Communications |Amsterdam |
+| **[Kaalam Telecom Bahrain B.S.C](http://www.kalaam-telecom.com/azure/)**| Level 3 Communications |Amsterdam |
 | **LGA Telecom** |Equinix |Singapore|
 | **[Macroview Telecom](http://www.macroview.com/en/scripts/catitem.php?catid=solution&sectionid=expressroute)** |Equinix |Hong Kong SAR 
 | **[Macquarie Telecom Group](https://macquariegovernment.com/secure-cloud/secure-cloud-exchange/)** | Megaport | Sydney |
diff --git a/articles/lab-services/classroom-labs/class-type-jupyter-notebook.md b/articles/lab-services/classroom-labs/class-type-jupyter-notebook.md
@@ -30,10 +30,10 @@ Enable the settings described in the table below for the lab account. For more i
 
 | Lab account setting | Instructions |
 | ------------------- | ------------ |
-| Marketplace image | Enable the [Data Science Virtual Machine - Windows 2016](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-windows) image for use within your lab account. |
+| Marketplace image | Enable the [Data Science Virtual Machine - Windows 2019](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-win-2019) image for use within your lab account. |
 
 >[!TIP]
->This article will focus on configuring a template machine that uses the Windows Server operating system.  It's also possible to set up a data science class with Python and Jupyter Notebooks using [Data Science Virtual Machine for Linux (CentOS)](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-ads.linux-data-science-vm) or [Data Science Virtual Machine for Linux (Ubuntu)](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.linux-data-science-vm-ubuntu) images from the Azure Marketplace.
+>This article will focus on configuring a template machine that uses the Windows Server operating system.  It's also possible to set up a data science class with Python and Jupyter Notebooks using [Data Science Virtual Machine for Linux (Ubuntu)](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.linux-data-science-vm-ubuntu) images from the Azure Marketplace.
 
 ### Lab settings
 
@@ -46,7 +46,7 @@ Use the settings in the table below when setting up a classroom lab.  For more i
 
 ## Template machine
 
-The [Data Science Virtual Machine - Windows 2016](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-windows) image provides the necessary deep learning frameworks and tools required for this type of class.  The image includes Jupyter Notebooks and Visual Studio Code.  [Jupyter Notebooks](http://jupyter-notebook.readthedocs.io) is a web application that allows data scientists to take raw data, run computations, and see the results all in the same environment.  For our template machine, the web application will be running locally.  [Visual Studio Code](https://code.visualstudio.com/) is an IDE that provides a rich interactive experience when writing and testing a notebook.  For more information, see [Working with Jupyter Notebooks in Visual Studio Code](https://code.visualstudio.com/docs/python/jupyter-support).
+The [Data Science Virtual Machine - Windows 2019](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-win-2019) image provides the necessary deep learning frameworks and tools required for this type of class.  The image includes Jupyter Notebooks and Visual Studio Code.  [Jupyter Notebooks](http://jupyter-notebook.readthedocs.io) is a web application that allows data scientists to take raw data, run computations, and see the results all in the same environment.  For our template machine, the web application will be running locally.  [Visual Studio Code](https://code.visualstudio.com/) is an IDE that provides a rich interactive experience when writing and testing a notebook.  For more information, see [Working with Jupyter Notebooks in Visual Studio Code](https://code.visualstudio.com/docs/python/jupyter-support).
 
 The remaining task to set up the class is to provide local notebooks.  For instructions how to use the Azure Machine Learning samples, see [how to configure an environment with Jupyter Notebooks](../../machine-learning/how-to-configure-environment.md#jupyter).  You can also provide your own notebooks on the template machine.  The notebooks will be copied to all student machines when the template is published.
 
diff --git a/articles/machine-learning/data-science-virtual-machine/linux-dsvm-walkthrough.md b/articles/machine-learning/data-science-virtual-machine/linux-dsvm-walkthrough.md
@@ -26,7 +26,7 @@ In this walkthrough, we analyze the [spambase](https://archive.ics.uci.edu/ml/da
 Before you can use a Linux DSVM, you must have the following prerequisites:
 
 * **Azure subscription**. To get an Azure subscription, see [Create your free Azure account today](https://azure.microsoft.com/free/).
-* [**Linux Data Science Virtual Machine**](https://azure.microsoft.com/marketplace/partners/microsoft-ads/linux-data-science-vm). For information about provisioning the virtual machine, see [Provision the Linux Data Science Virtual Machine](linux-dsvm-intro.md).
+* [**Linux Data Science Virtual Machine**](https://azure.microsoft.com/marketplace/apps/microsoft-dsvm.linux-data-science-vm-ubuntu). For information about provisioning the virtual machine, see [Provision the Linux Data Science Virtual Machine](linux-dsvm-intro.md).
 * [**X2Go**](https://wiki.x2go.org/doku.php) installed on your computer with an open XFCE session. For more information, see [Install and configure the X2Go client](linux-dsvm-intro.md#x2go).
 * For a smoother scrolling experience, in the DSVM's Firefox web browser, toggle the `gfx.xrender.enabled` flag in `about:config`. [Learn more](https://www.reddit.com/r/firefox/comments/4nfmvp/ff_47_unbearable_slow_over_remote_x11/). Also consider setting `mousewheel.enable_pixel_scrolling` to `False`. [Learn more](https://support.mozilla.org/questions/981140).
 * **Azure Machine Learning account**. If you don't already have one, sign up for a new account on the [Azure Machine Learning home page](https://azure.microsoft.com/free/services/machine-learning//).
diff --git a/articles/machine-learning/data-science-virtual-machine/reference-centos-vm.md b/articles/machine-learning/data-science-virtual-machine/reference-centos-vm.md
@@ -47,7 +47,7 @@ Data scientists use various tools to complete these tasks. It can be time-consum
 
 The Linux DSVM can ease this burden substantially. Use the Linux DSVM to jump-start your analytics project. The Linux DSVM helps you work on tasks in various languages, including R, Python, SQL, Java, and C++. Eclipse provides an easy-to-use IDE for developing and testing your code. The Azure SDK, included in the DSVM, helps you build your applications by using various services on Linux for the Microsoft cloud platform. Other languages are preinstalled, including Ruby, Perl, PHP, and Node.js.
 
-There are no software charges for the DSVM image. You pay only the Azure hardware usage fees that are assessed based on the size of the virtual machine you provision with the DSVM image. For more information about the compute fees, see the [Data Science Virtual Machine for Linux (CentOS) listing](https://azure.microsoft.com/marketplace/partners/microsoft-ads/linux-data-science-vm/) in Azure Marketplace.
+There are no software charges for the DSVM image. You pay only the Azure hardware usage fees that are assessed based on the size of the virtual machine you provision with the DSVM image. For more information about the compute fees, see the [Data Science Virtual Machine for Linux listing](https://azure.microsoft.com/marketplace/apps/microsoft-dsvm.linux-data-science-vm-ubuntu) in Azure Marketplace.
 
 
 ## Machine Learning Server
@@ -174,7 +174,7 @@ The open-source database PostgresSQL is available on the DSVM, with services run
 SQuirreL SQL is a graphical SQL client that can connect to various databases (including SQL Server, PostgresSQL, and MySQL) and run SQL queries. You can run SQuirreL SQL from a graphical desktop session (through the X2Go client, for example) by using a desktop icon. Or you can run the client by using the following command in the shell:
 
 ```bash
-/usr/local/squirrel-sql-3.7/squirrel-sql.sh	/usr/local/squirrel-sql-3.7/squirrel-sql.sh
+/usr/local/squirrel-sql-3.7/squirrel-sql.sh    /usr/local/squirrel-sql-3.7/squirrel-sql.sh
 ```
 
 Before the first use, set up your drivers and database aliases. The JDBC drivers are located at /usr/share/java/jdbcdrivers.
diff --git a/articles/machine-learning/team-data-science-process/platforms-and-tools.md b/articles/machine-learning/team-data-science-process/platforms-and-tools.md
@@ -45,7 +45,7 @@ It also includes **ML and AI tools** like xgboost, mxnet, and Vowpal Wabbit.
 
 Currently DSVM is available in **Windows** and **Linux CentOS** operating systems. Choose the size of your DSVM (number of CPU cores and the amount of memory) based on the needs of the data science projects that you are planning to execute on it. 
 
-For more information on Windows edition of DSVM, see [Microsoft Data Science Virtual Machine](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-windows) on the Azure Marketplace. For the Linux edition of the DSVM, see [Linux Data Science Virtual Machine](https://azure.microsoft.com/marketplace/partners/microsoft-ads/linux-data-science-vm/).
+For more information on Windows edition of DSVM, see [Microsoft Data Science Virtual Machine](https://azuremarketplace.microsoft.com/marketplace/apps/microsoft-dsvm.dsvm-win-2019) on the Azure Marketplace. For the Linux edition of the DSVM, see [Linux Data Science Virtual Machine](https://azure.microsoft.com/marketplace/apps/microsoft-dsvm.linux-data-science-vm-ubuntu).
 
 To learn how to execute some of the common data science tasks on the DSVM efficiently, see [10 things you can do on the Data science Virtual Machine](../data-science-virtual-machine/vm-do-ten-things.md)
 
@@ -106,15 +106,15 @@ The TDSP team from Microsoft has published two end-to-end walkthroughs that show
 
 If you are following the TDSP on **Windows**, you need to install the **Git Credential Manager (GCM)** to communicate with the Git repositories. To install GCM, you first need to install **Chocolaty**. To install Chocolaty and the GCM, run the following commands in Windows PowerShell as an **Administrator**:  
 
-	iwr https://chocolatey.org/install.ps1 -UseBasicParsing | iex
-	choco install git-credential-manager-for-windows -y
-	
+    iwr https://chocolatey.org/install.ps1 -UseBasicParsing | iex
+    choco install git-credential-manager-for-windows -y
+    
 
 ### Install Git on Linux (CentOS) machines
 
 Run the following bash command to install Git on Linux (CentOS) machines:
 
-	sudo yum install git
+    sudo yum install git
 
 
 ### Generate public SSH key on Linux (CentOS) machines
@@ -133,7 +133,7 @@ If you are using Linux (CentOS) machines to run the git commands, you need to ad
 1. Copy the entire ssh key including *ssh-rsa*. 
 1. Log in to your Azure DevOps Services. 
 1. Click **<Your Name\>** at the top-right corner of the page and click **security**. 
-	
+    
    ![Click your name and then click security](./media/platforms-and-tools/resources-2-user-setting.png)
 
 1. Click **SSH public keys**, and click **+Add**. 
diff --git a/articles/mysql/howto-data-in-replication.md b/articles/mysql/howto-data-in-replication.md
@@ -66,7 +66,7 @@ The following steps prepare and configure the MySQL server hosted on-premises, i
 
 4. Create a new replication role and set up permission
 
-   Create a user account on the master server that is configured with replication privileges. This can be done through SQL commands or a tool like MySQL Workbench. Consider whether you plan on replicating with SSL as this will need to be specified when creating the user. Refer to the MySQL documentation to understand how to [add user accounts](https://dev.mysql.com/doc/refman/5.7/en/adding-users.html) on your master server. 
+   Create a user account on the master server that is configured with replication privileges. This can be done through SQL commands or a tool like MySQL Workbench. Consider whether you plan on replicating with SSL as this will need to be specified when creating the user. Refer to the MySQL documentation to understand how to [add user accounts](https://dev.mysql.com/doc/refman/5.7/en/user-names.html) on your master server. 
 
    In the commands below, the new replication role created is able to access the master from any machine, not just the machine that hosts the master itself. This is done by specifying "syncuser@'%'" in the create user command. See the MySQL documentation to learn more about [specifying account names](https://dev.mysql.com/doc/refman/5.7/en/account-names.html).
 
diff --git a/articles/network-watcher/network-watcher-intrusion-detection-open-source-tools.md b/articles/network-watcher/network-watcher-intrusion-detection-open-source-tools.md
@@ -33,7 +33,7 @@ Both open source tools can be set up on an Azure VM, allowing you to perform thi
 
 ### Install Suricata
 
-For all other methods of installation, visit https://suricata.readthedocs.io/en/latest/install.html
+For all other methods of installation, visit https://suricata.readthedocs.io/en/suricata-5.0.2/quickstart.html#installation
 
 1. In the command-line terminal of your VM run the following commands:
 
@@ -71,7 +71,7 @@ tail -f /var/log/suricata/fast.log
 
 ### Set up the Elastic Stack
 
-While the logs that Suricata produces contain valuable information about what’s happening on our network, these log files aren’t the easiest to read and understand. By connecting Suricata with the Elastic Stack, we can create a Kibana dashboard what allows us to search, graph, analyze, and derive insights from our logs.
+While the logs that Suricata produces contain valuable information about what's happening on our network, these log files aren't the easiest to read and understand. By connecting Suricata with the Elastic Stack, we can create a Kibana dashboard what allows us to search, graph, analyze, and derive insights from our logs.
 
 #### Install Elasticsearch
 
@@ -269,7 +269,7 @@ The sample dashboard provides several visualizations of the Suricata alert logs:
 
     ![image 7][7]
 
-For more documentation on creating custom visualizations and dashboards, see [Kibana’s official documentation](https://www.elastic.co/guide/en/kibana/current/introduction.html).
+For more documentation on creating custom visualizations and dashboards, see [Kibana's official documentation](https://www.elastic.co/guide/en/kibana/current/introduction.html).
 
 ## Conclusion
 
