This article describes how to resolve the NPrinting connection verification error:

x Qlik NPrinting webrenderer can reach Qlik Sense hub error

Environment

• NPrinting: all versions
• Qlik Sense: all versions
  • multi-node QS proxy environment
  • NLB (Network Load Balancer or Alias URL) server address used in front of cluster of Qlik Sense proxy nodes (which are linked to a Virtual Proxy. Proxy nodes will not work with NPrinting unless they are linked to a QS virtual proxy)

Resolution

• Although it is possible to use an NLB address in front of your QS proxy nodes that are used by NPrinting, the error generated in the NP connection verification process will appear as described in the article title
• This error can safely be ignored as this does not affect generation of NPrinting connections
• To eliminate the 'error' message, you would need to update your NPrinting connection to use a virtual proxy node address/computer name behind the NLB address . It must be the computer name and not an alias url).
• The proxy node used must be linked to a virtual proxy with the following required attribute
  
  • Microsoft Windows NTML authentication on the Qlik Sense proxy. (SAML and JWT are not supported. If your virtual proxy uses SAML or JWT authentication, you need to add a new virtual proxy with NTLM enabled for Qlik NPrinting connections).
  • A link between the proxy node and virtual proxy.
  • For all NPrinting to Qlik Sense requirements visit https://help.qlik.com/en-US/nprinting/Content/NPrinting/DeployingQVNprinting/NPrinting-with-Sense.htm#anchor-1

Related Content

• https://help.qlik.com/en-US/nprinting/Content/NPrinting/Troubleshooting/Verify-connection-to-Sense-errors.htm
• https://help.qlik.com/en-US/nprinting/Content/NPrinting/DeployingQVNprinting/NPrinting-with-Sense.htm#Requirem

Internal Investigation ID

• QB-2871

With the new inclusion of the Get Chart Image block in the Qlik Reporting connector in Qlik Application Automation, you now have more options to notify a group of users with more in-depth data and charts using Slack, Microsoft Teams, and email.

This article will guide you in sending your first chart image to Slack with Qlik Application Automation.

It explains a basic example of a template configured in Qlik Application Automation for this scenario.

You can make use of the template which is available in the template picker. You can find it by navigating to Add new -> New automation -> Search templates and searching for 'Send a Chart Image to Slack' or 'Embed a chart image in an email' in the search bar, and clicking the Use template option.

For guidance on sending charts via Microsoft Teams and mail, go to the "Next Steps" section at the end of this article.

You can download examples of the automations from this article: Send-chart-image-to-slack.json, Send-chart-image-to-outlook.json, Send-chart-image-to-mail.json, Send-chart-image-to-microsoft-teams.json

Full Automation

Configure the Automation

1. Open the automation editor and search for the Qlik Cloud Services connector on the left-hand menu.
   
   
2. Drag the blocks “Select Field Value” and “Create Bookmark” to the canvas and fill in the required inputs. You can add multiple Select Field Value blocks to apply selections to various fields. The Create Bookmark block is then used to create a temporary bookmark that can pass the selections to the Get Chart Image block.
   
   
   
   
   
   
   

   Warning: Whenever the “Get Chart Image” block is to be used, we advise you to only use it with temporary bookmarks or pre-existing persistent bookmarks.

2. Search for the Qlik Reporting connector on the left-side menu, then drag the "Get Chart Image" block to the editor and attach it below the previous block.
   
   Choose the same app you chose when creating the temporary bookmark and use the ID value received from the “Create Bookmark” block. 
   
   
   
   The height and width inputs are not required and default to 1000 if the fields are empty.
   
   Manually insert the Object ID input; it can not yet be retrieved through an API call.
   
   To find the chart ID from the app, open the app, then click Edit Sheet, right-click the chart, and open the Share/Embed menu from the menu dropdown that appears. You will see the object ID of the chart under the chart preview section as shown below:
   
   
   

    

3. Add the 'Condition' block to check whether the "Get Chart Image" block has returned a successful response.
   
   
   
   
   1. If the condition block outcome evaluates to true:
      
      
      • Search for Slack connector from the left-side menu, add the "Upload File To Channel" block, and fill in all the required inputs.
        
        
        
        
      • The chart image gets posted on the Slack channel as shown below:
        
        
         

   2.  If the condition block outcome evaluates to false:

      • Add the "Update Run Title" block to specify that the "Get Chart Image" block failed due to an error.
        
        
        
        
      • Add an "Error" block to throw an error message from the "Get Chart Image" block and set the current automation run to be in a failed state.
        
        
        

Configure and send the Output

Embed the chart in the email

Gmail does not support embedding base64 encoded images due to security constraints. To work around this, we advise sending the chart image as an attachment through the Send Mail block in the Mail connector if you use a Gmail account.

See Gmail blocking small embedded inline images in email template for details on the restriction. 

1. To embed the image in an email, you'll need to replace the Slack block with Send Mail block from the Microsoft Outlook 365 connector or the Send Mail block from the Mail connector and configure the block's Type parameter to HTML.
2. In the body of the HTML, start adding a <img> tag and set the src parameter of the img tag to "data&colon;image/png;base64,".
   

   
   

3. Add the Get Chart Image block output at the end of the src parameter.
   

   
   

4. Click the Get Chart Image label in the input parameter, and pick the Add formula option; then search for the "base64 encode" formula to apply it to the output from the Get Chart Image block.
   
   
   
   
   

   
   

5. Finalize the img tag with an optional width and height to style the image.
   
   

Send the chart to a channel in Microsoft Teams

1. To send the image to Microsoft Teams, replace the Slack block with the Send Html Message With Base 64 Image block from the Microsoft Teams connector.
2. Configure the "Base 64" parameter of the block by mapping it to the output of the Get Chart Image block.
   

   
   

3. Click the field mapping for the Get Chart Image again and open the formula picker. Search for the base64 encode formula and apply it.
   
   
   
   
    
4. Set the Image Content Type parameter to image/png and (optionally) provide additional HTML content that will be inserted before or after the image.
   

   
   

The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.

Environment

• Qlik Cloud 
• Qlik Application Automation 

Related Content

• Distributing Chart Images through Automation

To help Qlik customers manage costs more effectively, Qlik has developed the Qlik Snowflake Monitoring application, designed to provide invaluable insights about your Snowflake costs, usage, inventory, security, performance and contract utilization. This app utilizes Qlik's Associative Engine to connect directly to your Snowflake instance and reveal insights from Snowflake's detailed metadata, offering valuable information that traditional query-based tools and Snowflake's own reports are unable to provide.

Leveraging Qlik Application Automation, and Data Alerts, you can:

• Install* & update the app with a fully guided, click-through installer, using an out-of-the-box Qlik Application Automation template.
• Get alerted when new versions of the Snowflake Monitor are available using Data Alerts.

*Minor configuration is required on first run to create the required data connections.

Content:

• Part One: 'Qlik Snowflake Monitoring App Installer' templateoverview
• Features
• Note on manual install
• Part Two: Creating and setting up analytics data connections
• Snowflake connection
• Note on Snowflake authentication
• REST connection to repository
• Note on update compatibility
• Part Three: Set up a Data Alert to notify when a new version of the app is available
• Summary

Part One: 'Qlik Snowflake Monitoring App Installer' template overview

This automation template is a fully guided installer/updater for the Qlik Snowflake Monitor. Leverage this automation template to easily install and update this application. The application itself is community-supported; and it is provided through Qlik’s Open-Source Software GitHub and thus is subject to Qlik’s open-source guidelines & policies.

For more information, refer to the GitHub Repository.

Features

• Easy app installation and updates
• Create new spaces or use existing spaces
• Automatic setup of settings, roles, and permissions
• Always installs the newest version from Qlik's OSS GitHub
• Tags apps to easily track installations and versions
• Works with both user and capacity-based subscriptions
• Compatible with all Snowflake tenant levels

Note on manual install

If the monitoring app was installed manually (i.e. not through the application automation installer), then the app will not be detected as existing. The automation will install new copies side-by-side. Any subsequent executions of the automation will detect the newly installed monitoring application and check their versions. This is because the application is tagged with ‘QCS - QSM - {App Name}’ and ‘QCS – QSM - {Version}’ during the installation process through the automation. Manually installed applications will not have these tags and therefore will not be detected.

Part Two: Creating and setting up analytics data connections

The Qlik Snowflake Monitor requires two connections, one to your Snowflake instance to feed the data for your analytics, and one REST connection to the qlik-oss repository to run a version check on the monitor.

Snowflake connection

You will need to create a custom User, Role and Warehouse on your snowflake tenant. This is to ensure this user and role can see the monitoring details and can be monitored.

1. Update the credentials in the SQL script from GitHub 
2. Run the SQL as ‘ACCOUNTADMIN’ from your Snowflake tenant to create a warehouse to retrieve the relevant data. Make sure you change the password and store this securely.
3. Create a snowflake data connection in the Qlik analytics space into which the application was deployed, using the following details:
   
   
   • Server: The full hostname for the Snowflake account, not prefixed with http:// or https://
   • Port: Leave as default unless it needs changing.
   • Database: SNOWFLAKE
   • Schema: ACCOUNT_USAGE
   • Warehouse: QLIK_MONITORING_WH
   • Role: QLIK_MONITORING_ROLE
     
     

   For Authentication, this setup is defaulted to username & password.

   • Username: QLIK_MONITORING
   • Password: As specified in your configuration above
     
     

   Finally, you need to name the connection as follows:

   • Connection Name: SNOWFLAKE_MONITORING_DATA
     
     
   
   

    

Note on Snowflake authentication

If you wish to use an alternative authentication method, please follow the documentation accordingly on both Snowflake & Qlik.

REST connection to repository

The REST connection is used to fetch version details from the GitHub repository. On reload it will look for the the latest released version in github and check this against the version you have installed. You can later use this in ‘Part Three’ to create an alert when updates to the application are available. To create a REST connection the following information is required:

• URL: https://raw.githubusercontent.com/qlik-oss/qlik-snowflake-monitor/main/manifest.json 
• METHOD: GET
• Allow “WITH CONNECTION”: Enabled
• Connection Name: REST Monitoring Versioning API
  
  
  
  

Once these two connections have been set up, you can reload the application. The application has been created to accommodate Snowflake tenants of all sizes. If you have a small tenant, you will find the initial run of the load script can take around 30 minutes, and for larger tenants this can be over an hour or two. Subsequent runs will utilize cached QVDs that update daily to reduce reload times each subsequent day.

Note on update compatibility

If a new release of the application is made, occasionally a full reload of data is required, but generally, if the data schema is unchanged the existing QVDs will be maintained. This is through the use of versions in the names of the QVDs used to store the data.

Part Three: Set up a Data Alert to notify when a new version of the app is available

The application has the following two variables:

• vLatestVersion: The latest version of the app released on Qlik’s OSS GitHub.
• vIsLatestVersion: A Boolean of whether the app’s current version is equal to the latest version of the app released on Qlik’s OSS GitHub (1 if true, 0 if false).

To create a new Data Alert for updates to the monitoring app, follow these steps:

1. Right-click on a chart in the app, select Alerts and then Create new alert.
2. Clear out the defaults and provide the alert with a name such as Qlik Snowflake Monitor Update Available.
3. Select Add measure and select the fx icon to enter a custom expression. Enter the expression ’$(vLatestVersion)'. Ensure it is wrapped in single quotes, then provide the label for the expression Latest Version.
4. Select Add measure and select the fx icon to enter a custom expression. Enter the expression $(vIsLatestVersion), then provide the label for the expression Is Latest Version.
5. Confirm the Details & data tab resembles the following:
   
   
   
   
6. Navigate to the next tab, Conditions.
7. Set the Measure to Is Latest Version, the Operator to Equal to, and the Value to 0. This way, if the app is not the latest version (0), it will trigger the alert.
8. Confirm that the Conditions tab resembles the following:
   
   

   

6. Navigate to the Distribution tab and confirm that the alert is evaluated When data is refreshed.

Summary

The Qlik Snowflake Monitor can be easily installed by following these steps above. If you wish to find out more, check out this Ometis blog post and this Ometis Webinar to get a run through of the analytics this application can offer.

If you face any issues, please use the GitHub and raise an issue through the repository.

This article provides an overview of how to notify your team on Microsoft Teams based on a measure with Qlik Application Automation.

The template is available via the template picker. You can find it by navigating to Add new -> New automation -> Search templates searching for 'Notify your team on Microsoft Teams based on a measure.json' in the search bar, and clicking the Use template option.

You will find a version of this automation attached to this article: "Notify-your-team-on-Microsoft-Teams-based-on-a-measure.json".

Content:

• Full Automation
• Automation structure
• Related Content
• Environment

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add the 'Select Field Values By Query' block from the Qlik Cloud Services connector to apply the selection to the app. Configure all the required input parameters.
   
   
2. Add the 'Get Measure Value' block from the Qlik Cloud Services connector to get a measure value of the selected data.
   
   
3. Add a 'Condition' block to check if the measure value has exceeded a specific threshold value.
   
   
   
   
4. Add the 'Send Message' block from the Microsoft Teams connector to the Yes branch of the 'Condition' block to notify that the measure value has exceeded the threshold.
   

Related Content

• How to get started with Microsoft Teams

Environment

• Qlik Cloud
• Qlik Application Automation

This article provides an overview of how to export a Qlik Sense app without data to an Amazon S3 bucket and import it back to the Qlik Cloud tenant from the file on Amazon S3 using Qlik Application Automation.

The template is available on the template picker. You can find it by navigating to Add new -> New automation -> Search templates, searching for 'Scheduled app export to an Amazon S3 bucket (without data)' or 'Import an app from a file on Amazon S3' in the search bar, and clicking the Use template option.

You can download examples of the automations from this article: Scheduled-app-export-to-an-Amazon-S3-bucket.json, Import-an-app-from-a-file-on-Amazon-S3.json.

Content:

• Export Qlik Sense app without data to Amazon S3 bucket
• Full Automation
• Automation structure
• Import an app from a file on Amazon S3
• Full Automation
• Automation structure
• Environment

Export Qlik Sense app without data to Amazon S3 bucket

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add the 'Get App Information' block from the Qlik Cloud Services connector to retrieve the app information. This is later used to create the file in Amazon S3.
   
   
2. Add the 'Export App To Base64 Encoded File' block from the Qlik Cloud Services connector to export the app to a base64-encoded string. The app is always exported without data.
   
   
3. Add the 'Create File' block from the Amazon S3 connector to create a file in the S3 bucket. The file will contain the app's base64-encoded string in .txt format. The file name is given as the app name retrieved from the 'Get App Information' block output in Step 1, along with the current date specified in the path parameter. Configure all the other mandatory input parameters.
   
   
   
   
4. Add the 'Write Line To File' block from the Amazon S3 connector to write the base64 encoded content from Step 2 to the above-created file in the S3 bucket. The Data input parameter is mapped to the output from the 'Export App To Base64 Encoded File' block.
   
   
   
   
5. Add the 'Save And Close File' block from the Amazon S3 connector to make the file available in the S3 bucket.

Import an app from a file on Amazon S3

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add the 'Open File' block from the Amazon S3 connector to open the file on S3 that contains the base64 export of the app. Configure all the mandatory input parameters.
   
   
   
   
2. Add the 'Read Data From File' block from the Amazon S3 connector to read the data from the file opened in the previous step.
   
   
3. Add the 'Import App From Base64 Encoded File' block from the Qlik Cloud Services connector to create a new app in your Qlik Cloud tenant.

The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.

Related Content

• How to get started with Amazon S3 connector 
• How to import a Qlik Sense app with an automation 

Environment

• Qlik Cloud  
• Qlik Application Automation 

Content:

• Step-by-Step:
• Limitations
• Related Content

Step-by-Step:

To create a Mail connection in Application Automation, do the following:

1. In Qlik Sense SaaS Hub select Add New > New automation
2. On the create dialog, select Connections in the menu
   
   
   
   
3. In Explore, search for Mail and select the Mail connector. Press Add
4. Fill out the details for your SMTP server. Press Save and Ok

The Mail connection will now be listed in My connections.

Verify the Mail connection by creating a simple automation.

1. In Qlik Sense SaaS Hub, select Add New > New automation
2. Give the automation a name and press Save
3. In the automation editor, click on the Mail connection in the left pane
   
   
   
   
4. Drag the Send Mail block on to the canvas, connecting it to the Start block
   
5. In the right pane, fill out the required fields to send a test email
   
   
   
   
6. Press Save and Run to execute the automation
7. Verify the test email being sent successfully and received in the mailbox
   
   If you receive any error when running the test automation, verify the details of your SMTP server being correct (Host, Password still accurate, Port etc):
   
   
   
   
8.  In the menu select Connections to go back to the connections page
9. In My connections, select the Mail connection and press Edit connection
10. Confirm all settings being correct and press Save
11. Run the test automation again to confirm the email being sent

Limitations

• The Mail Connector does not at present support SSO. See Qlik Application Automation: "Send Mail" block doesn't work with Gmail's with Okta integration
  
  
• The configuration for an Email server that already exists on a tenant cannot be used within an automation. A new connection must be created in Qlik Application Automation.
  
  
  
  
• The connection will not be verified during creation. As a best practice it is always recommended to verify the Mail connection with a simple automation, before using the Send Mail block in more advanced automations.

Related Content 

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

Loop and Reduce will remove an app's section access that was defined through the load script. Offline usage needs to be enabled in your tenant's management console in order to use the Loop And Reduce block on an app outside a personal space. More information on offline usage.

See How to Loop and Reduce with always one selected value fields if your app contains always one selected value fields.

This article explains how a loop and reduce operation can be performed on a Qlik Sense app by using Qlik Application Automation. It covers two examples, in the first one, the reloaded apps will be (re)published to one space. In the second example, each reduced app will be (re)published to a separate space.

This article covers two advanced examples, a more basic example can be found here .

Covered in this article:

• 1. Loop and reduce to one space
• 2. Loop and reduce to multiple spaces

The source app used in this article can be downloaded here.

Attached to this article are 2 files of the exported automations used in this article. More information on importing automations can be found here.

1. Loop and reduce to one space

In this example, all reduced apps will be (re)published to the same space.

Create a new automation and follow these steps to perform a loop and reduce action on a Qlik Cloud app:

1. Go to the Qlik Cloud Services connector and search for the block "Loop And Reduce". Drag this block inside the automation editor.
   
   
2. Specify the id for the app that should be used as a source app. The reduction will be performed on this app. Next, specify the field name over which the loop should run, for each unique value of the specified field name, a reduced app will be created. In this example, CountryName will be used as the reduction value.
   
   

    

3. The reduced apps are stored on the Temporary File services. The Loop And Reduce block will return a list of file ids together with the unique value of the reduction field and a list of sheet ids for the sheets that were public on the source app.
   
   
4. The next step is to import the apps from the Temporary File services. To do this search for the block "Import App From Export Id" and drag this block in the loop that's created by the Loop And Reduce block. This block will import one app from the temporary file services into your personal space.
   Tip: specify the reduced value that's outputted by the Loop and Reduce block in the Name parameter of the Import block. See the below image for an example:
   
   

    

5. When an app is imported, all sheets will be made private, this is the default behavior of the import app block. The next step is to publish the sheets that were public in the source app.
   
   
6. Because each reduced app will have a list of sheets that were public, a Loop block is necessary to loop over the list. Search for a "Loop" block in the block menu or find it under Basic and connect it right below the "Import App From Export Id" block. Specify the "Public Sheets" list returned by the Loop And Reduce block as the value for the "Loop over items of list" input parameter of the Loop block.
   
   

    

7. Now to publish each sheet of the imported app, search for the block "Publish Sheet" in the Qlik Cloud Services connector and drag that block in the loop generated by the "Loop" block. In this block, specify the id that's returned by the Import App block as App Id and use the current item in the loop as Sheet Id.
   
   

    

8. Nex step is to publish or republish the imported app to a managed space. This can be done with the block "Publish App To Managed Space". Search for this block in the Qlik Cloud Services connector and connect it below the loop block. Set the Run Mode to "(Re)publish by name", if the managed space already contains an app with the same name as the imported app, the imported app will be republished, or else it will be published.
   
   
9. In the configuration of the Publish App To Managed Space block, set the App Id equal to the id returned by the Import App From Export Id block. For the Space Id, perform a lookup or manually enter an id, make sure you're specifying a managed space. The Data parameter should be set to "source".
   
   

    

10. Finally, when your app is published to a managed space, the imported app will still exist in your personal space. To remove this app, search for the block "Delete App" in the Qlik Cloud Services connector and connect it to the Publish App To Managed Space block. Specify the id returned by Import App From Export Id as the App Id in the block's settings.
    
    

An example of a completed automation:

Attached example file: loop_and_reduce_to_same_space.json

2. Loop and reduce to multiple spaces

In this example, each reduced app will be published to a different space. We'll use the Insurance Claims app and the automation for the first example again. Since this app reduces on the field CountryName, we'll start by creating a managed space for each unique value that's found for CountryName. This results in the following list of spaces:

Next is to create a mapping for each unique reduction value and the corresponding space's id. There are multiple ways to achieve this. In this example, this mapping is stored in a JSON list of objects with the keys reduction_value and space_id. Feel free to use an automation to create the managed spaces and build this list.

Example:

[
	{
		"reduction_value": "Scotland",
		"space_id": "6138a3062c1054d8158c189a"
	},
	{
		"reduction_value": "Northern Ireland",
		"space_id": "6138a318faed485d36ae911f"
	},
	{
		"reduction_value": "England",
		"space_id": "6138a337faed485d36ae9126"
	},
	{
		"reduction_value": "Wales",
		"space_id": "6138a33f98b0d0bf7e719dfb"
	},
	{
		"reduction_value": "Guernsey",
		"space_id": "6138a349faed485d36ae912b"
	},
	{
		"reduction_value": "Isle of Man",
		"space_id": "6138a35aba392246d331e611"
	},
	{
		"reduction_value": "Jersey",
		"space_id": "6138a3653ec592fe53a8d55b"
	}
]

The next step is to store the mapping in the automation. Execute the following steps to do this:

1. Search for the Variable block and add this to the automation.
   
   
2. Go to the block's settings, click Manage variables and add a new variable of type list.
   
   
3. Go to the operations section of the variable and set the first operation to empty the variable.
   
   
4. Add a second operation Merge other list into... and click the List input field of that operation, in the dropdown that appears, select Add Formula.
   
   
5. From the formula picker, search for the formula Object and select it. Copy the JSON mapping to the json input field of the Object formula and click Save.
   
   
6. Add the block to the beginning of the automation from the first part of this article:
   
   

    

7. The next step is to find the right space id for each reduced app. To do that, add the block Lookup Item In List in the automation right before the block Publish App To Managed Space.
   
   
8. Go to the settings of the Lookup Item In List block and specify the variable that contains space_id/reduction_value mapping as input list. The condition inside the lookup should compare the mapping's reduction_value to the Reduced Value of the current item in the loop of Loop And Reduce. See the below image for an example:
   
   
   

    

9. Finally, specify the space_id from the output of the lookup block as Space Id in the settings of the Publish App To Managed Space.
   
   

    

Attached example file: loop_and_reduce_to_mulitple_spaces.json

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

This article provides an overview of how to notify your team on Microsoft Teams using data from multiple apps with Qlik Application Automation.

The template is available via the template picker. You can find it by navigating to Add new -> New automation -> Search templates searching for 'Notify your team on Microsoft Teams with data from multiple apps' in the search bar, and clicking the Use template option.

You will find a version of this automation attached to this article: "Notify-your-team-on-Microsoft-Teams-with-data-from-multiple-apps.json".

Content:

• Full Automation
• Automation structure
• Related Content

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add two 'Get Measure Value' blocks from the Qlik Cloud Services connector to get a measure value from the first and second apps.
   
   
2. Add the 'Select Field Value' block from the Qlik Cloud Services connector to apply a selection to the third app before getting the measure value.
   
   
3. Now add 'Get Measure Value' block from the Qlik Cloud Services connector to get a measure value from the third app.
   
   
4. Add a 'Send Message' block from the Microsoft Teams connector to send a message to the Teams channel with the information from the above three apps. Specify the Team ID and the Channel ID input parameters. You can use the do-lookup functionality to find value for all these parameters. 

Related Content

• How to get started with Microsoft Teams

Environment

• Qlik Cloud  
• Qlik Application Automation 

This article provides an overview of how to send straight table data to Microsoft Teams as a table using Qlik Application Automation.

The template is available on the template picker. You can find it by navigating to Add new -> New automation -> Search templates, searching for 'Send straight table data to Microsoft Teams as a table' in the search bar, and clicking the Use template option.

You will find a version of this automation attached to this article: "Send-straight-table-data-to-Microsoft-Teams-as-a-table.json".

Content:

• Full Automation
• Automation structure
• Related Content

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add the 'Get Straight Table Data' block from the Qlik Cloud Services connector to get data from the straight table for a specific app to send to the Microsoft Teams channel as a table. Specify the app ID, Sheet ID, and Object ID in the input parameters. You can use the do-lookup functionality to find value for all these parameters. There is a limit of 100,000 records that can be retrieved through the 'Get Straight Table Data' block. This block will not work with other table types.
   
   
2. Add a 'Loop' block to loop over the keys from the 'Get Straight Table Data' block response which acts as the table header. Use the '{getkeys: {$.GetStraightTableData}}' formula in the 'Loop' block. Within the 'Loop' block add the following blocks:
   
   
   1. Add an object variable called 'teamsTextBlockObject' to build the header and pass this variable to another list variable called 'cardTableColumn'.
      
      
   2. Add another 'Loop' block to loop over all the values for the current key of the straight table. Within the 'Loop' block add the following blocks:
      
      
      1. Add a 'Condition' block to check whether the column value is empty or not.
         
         
         • If the condition block outcome evaluates to true:
           
           
           • Add the 'teamsTextBlockObject' object variable, set the text value as 'NA' since the column value is null/empty, and pass this variable to the 'cardTableColumn' list variable.
             
             
         • If the condition block outcome evaluates to false:
           
           
           • Add the 'teamsTextBlockObject' object variable, set the text value as the column value of the straight table, and pass this variable to the 'cardTableColumn' list variable.
             
             
   3. Add another object variable called 'columnObject' and pass this variable to the 'columns' list variable. These variables are used to build the straight table data into a specific format which is required to build the structure of the team's message as a card attachment.
      
      
3. Add a string variable called 'title' which is used to provide the title to the message.
   
   
4. Add the 'Create Attachment Adaptive Card' block from the Microsoft Teams connector to build the structure for card attachment. Make sure to transform the 'columns' list to JSON text using the JSON formula.
   
   
   
   
5. Add 'Send Message' block from the Microsoft Teams connector to send straight table data as a table to the Teams channel with the card attachment which was created in the previous block.
   Specify the Team ID and the Channel ID in the input parameters. You can use the do-lookup functionality to find the value of all these parameters. 
   
   
   

An example output of the table sent to the Teams channel:

The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.

Related Content

• How to get started with Microsoft Teams
• Send straight table data to Microsoft Teams as a message 
• Send straight table data to email as HTML table

Environment

• Qlik Cloud  
• Qlik Application Automation 

This article provides an overview of how to send straight table data as a message to Microsoft Teams using Qlik Application Automation.

The template is available on the template picker. You can find it by navigating to Add new -> New automation -> Search templates, searching for 'Send straight table data to Microsoft Teams as a message' in the search bar, and clicking the Use template option.

You will find a version of this automation attached to this article: "Send-straight-table-data-to-Microsoft-Teams-as-a-message.json".

Content:

• Full Automation
• Automation structure
• Related Content

Full Automation

Automation structure

The following steps describe how to build the demo automation: 

1. Add the 'Select Field Value' block from the Qlik Cloud Services connector to apply a selection to the straight table.
   
   
2. Add the 'Get Straight Table Data' block from the Qlik Cloud Services connector to get data from the straight table for a specific app to send to the Microsoft Teams channel as a table. Specify app ID, Sheet ID, and Object ID input parameters. You can use the do-lookup functionality to find value for all these parameters. The 'Get Straight Table Data' block is limited to retrieving  100,000 records. This block will not work with other table types.
   
   
3. Add a string variable called 'message' within 'Get Straight Table Data' block to append a list item element (<li>) to the message variable. Specify key-value pairs for the dimensions from your straight table to be included in the message.
   
   
4. Add a 'Send Message' block from the Microsoft Teams connector to send straight table data as a message to the Teams channel. Map the 'message' variable to the Content input parameter and enclose it in an unordered list element <ul>. Ensure you don't send too many records; Microsoft Teams has a limit of 28 KB per message. Specify the Team ID and the Channel ID input parameters. You can use the do-lookup functionality to find value for all these parameters. 
   
   

An example output of the message sent to the Teams channel:

The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.

Related Content

• Video - Send straight table data to a Microsoft Teams channel as a message 
• How to get started with Microsoft Teams
• Send straight table data to Microsoft Teams as a table 

Environment

• Qlik Cloud  
• Qlik Application Automation 

This article gives an overview of the available blocks in the Github connector in Qlik Application Automation. It will also go over some basic examples of retrieving file/blob contents from your repos as well as other functionalities within a GitHub account.

As with most connectors provided for automations the authentication for this connector is based on the oAuth2 Protocol, so when connecting to it you provide the user name and password of the account directly to the Github platform to request access so it is done in the most secure manner there is.

Let's now go over a few basic examples of how to use the Github connector:

How to list owned repositories and check their contents from your Github account:

1. Create an automation;
2. From the left menu, select the Github connector;
3. drag and drop the "List my repositories" block
4. drag and drop the "List repositories contents" block inside the loop created by the first block:

Now the "list my repositories" block offers a couple of filtering options depending what result you want (all repos or just the private or public ones and if you want the result to come in sorted by some rule) but they are mostly optional. Not filling them in will return by default all repositories.

As for the "List repository contents" block you will need to fill in the username you use for your github account as well as the repository name which can be filled in with the results gotten from the first block. You can leave the path parameter empty to get the contents from the root folder or you can specify a path and the contents of that path will be returned.

As stated, if you expect to retrieve only one record, the use of "get repository content" block is more better suited. Also, you might want to switch this "List repository contents" block On Error status to either warning or ignore since Github API platform returns a 404 error if one of the queried repositories is empty.

Now if you are planning to use the "Get repository content" block another warning should be mentioned and that this block only works for files or blobs up to a maximum of 1 MB in size, as per Githubs platform limitations. The response of this block should look like:

As you can see we have a couple of information stubs of that file, but most importantly from here is the SHA property, which is needed if you are planning to later on use the "Create or update file contents" block, required input parameter for the update of a file/blob.

Now if you're planning on updating files that are bigger than 1MB and you require the SHA of that file, we suggest using the list repository contents block and search for the required file and SHA in that result.

As for other functionalities of the Github connector we support also getting and listing commits or issues present in a repository, listing of users and many other requests but, if you are in need of a request that isn't present, we also offer the functionality to create your own requests to the Github API by making use of the RAW API blocks. These API blocks and their uses are explained in a separate article.

You can find attached to this article a simple JSON example which you can upload to your workspace, if you want to see a quick example of how to use version control to back up your QCS apps I suggest visiting the related article.

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

Related Content

How to: Qlik Application Automation for backing up and versioning Qlik Cloud apps on Github

With Microsoft and Google terminating support for Basic Authentication, Qlik suggests using a dedicated tool (such as Sendgrid, Mailchimp, or Mailgun) for bulk emails. While Qlik does not specifically endorse any of these services over the others, here's an example on how to setup Qlik Cloud Services SMTP settings with Sendgrid, taking advantage of their free tier. Going beyond that tier might require adopting a paying subscription from either Sendgrid or any of their competitors.

Environment

Qlik Cloud 

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

1. Go to Sendgrid.com  and click on "Try For Free"
   
   
   
   
   
   
2. Create a free account, by providing your email address and picking a password
   
   
   
   
   
   
3. After completing a form with the personal/company information, create a Single Sender from the main dashboard
   
   
   
   
   
   
4. Complete the creation of a sender by adding the details
   
   
   
   
   
   
   
5. After verifying the email address, check that the information is correct
   
   
   
   
   
6. In the "Email API" section, select "Integration Guide" and then "SMTP Relay"
   
   
   
   
   
7. Create a key by giving it a name of your choice
   
   
   
   
   
8. Mark down the settings to use for the SMTP config
   
   Server: smtp.sendgrid.net
   Port: 465 (SSL)
   Username: apikey
   Password: Your API Key
   
    
   
   
   
   
9. Open a new browser tab and, in your Qlik Cloud tenant, go to Management Console --> Settings -->  Email Server and enter the information from above
   
   
   
   
   
   
   
10. After testing the sending of an email, go back to the Sendgrid page, select the checkbox and  Verify integration
    
    
    
    
11. Go to the Activity Feed in Sendgrid to check the status of sent emails
    
    
    
    
    
12. The same settings can be applied in the "Send Mail" block in Qlik Application Automation, under the "Connection" tab. This block can also be used with Qlik Reporting Service.
    
    

Related Content

Implement advanced SMTP authentication options for alerts and subscriptions in Qlik Cloud
How to use Mailchimp bulk email service SMTP with Qlik Cloud Services and Qlik Application Automation 

This article describes the setup of an automation to run every time an app reload fails.

This can be done using the new Reload status filter on the App Reload Finished webhook event.

The automation can trigger an alert to Microsoft Teams, Slack, or another messaging tool. It can also be used to create a ticket in Jira or ServiceNow to make sure someone in your team will follow up on the failed reload.

Configuring the automation

Start by creating a new automation from your Qlik Cloud tenant. You can do this through the Add new button in the upper-right corner of the Qlik hub. Choose to start with a blank template, give the automation a name, and follow the below steps to configure the webhook.

1. Select the Start block in the automation canvas and configure the below settings in the Block Configuration menu on the right side of the canvas:
   
   
   1. Run Mode: Webhook
   2. Connector: Qlik Cloud Services
   3. Event: App Reload Finished
   4. Filter: Configure values for the App IDs and Space IDs parameters to narrow the webhook to specific apps or spaces. Then set the Reload status to "Failed (error)".
      
      In the below example, the webhook is configured to listen to failed reloads in the "Finance" space.
      

      
      

2. Add a block to take action on the failed reload.
   
   In this example, we'll send a message to a Teams channel in order to alert our team. For this, we'll use the Send Message block from the Microsoft Teams connector. You can find this connector and the block in the Block Library menu on the left side of the canvas. Click the connector to show all blocks and drag the Send Message block below the Start block.
   
   
   
   
   
   
3. Select the Send Message block to open the Block Configuration menu.
   
   Go to the Connection tab to create a connection to your Microsoft Teams account.
   
   

   

4. Go to the Inputs tab to further configure the Send Message block.
   
   
   1. Use the do lookup functionality to configure the Team ID and Channel ID parameters.
   2. Type a message in the Content parameter input field. To add information from the Reload Finished event, click the input box and click Output from App Reload Finished. This shows the output from previous runs or an example output.
   3. Click the parameters which you want to include in the message. Things like App Name, App ID, and Description from the Errors list could be interesting here. When the automation is run, these values will be concatenated into a single string.
      
      
      

       

5. Below is an example image of the result in Microsoft Teams. Feel free to replace the block with a Create Ticket block from the Jira or ServiceNow connector or use a different messaging tool like Slack, SendGrid or Email.
   
   
   

    

Related Content:

Qlik Sense Reload and Task Best Practices 
How to get started with Microsoft Teams in Qlik Application Automation 
How to send chat messages using the Microsoft Teams connector  
How to get started with SendGrid in Qlik Application Automation 
How to send a message to a channel in Slack in Qlik Application Automation 

Environment

Qlik Cloud 
Qlik Application Automation 

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

This article explains how the Reporting connector in Qlik Application Automation can be used to generate multi-app reports. It also explains how the generated report can be stored on a cloud storage tool, like Microsoft SharePoint.

Multi-app reports

A multi-app report is a report that contains sheets from multiple apps. This type of report can be created in Qlik Application Automation with the Create Multi App Report and the Add Sheet to Multi App Report blocks.

To add selections to these sheets, you can still use the Add Selection To Sheet block. To add selections to the report, you can use the Add Selection To Report block.

Example

In this example, we'll create an automation that generates a report containing two sheets from two different apps, with selections applied to the second sheet.

Before you continue, please create a new automation and search for the reporting connector in the Block Library: 

1. Search for the Create Multi App Report in the Reporting connector, drag it to the automation editor, and attach it to the Start block. Configure it by specifying a name for the report.
   
2. Add the Add Sheet To Multi App Report block to the automation and configure it to use the output from the Create Multi App Report block and select an app and sheet to add as the first page to the report. 
   
3. Add a second Add Sheet To Multi App Report block to the automation and configure it for a different app and sheet. 
   
4. Add an Add Selection To Sheet block to the automation to add a selection to the second sheet. Configure it to use the output from the second Add Sheet To Multi App Report block and select a field to apply the selection. Provide one or multiple values for the selection.
   

    

5. Add the Generate Report block to the automation and configure it to use the report we've been building. When this block is executed in the automation, it will trigger the actual report generation and its output will be the report PDF file.
   

    

6. Find the Cloud Storage connector in the Block Library and add the Copy File block to the automation. Configure it to use the output from the Generate Report block as the Source File and set the Destination connector to Microsoft SharePoint (or another destination of your choosing). Include the Path from the output of the Generate Report block in the Destination Path parameter to use the generated filename. Use the do lookup functionality to find a Drive Id or a Site Id,  but do not specify both.
   

    

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

Installing, upgrading, and managing the Qlik Cloud Monitoring Apps has just gotten a whole lot easier! With two new Qlik Application Automation templates coupled with Qlik Data Alerts, you can now: 

1. Install/update the apps with a fully guided, click-through installer using an out-of-the-box Qlik Application Automation template. 
2. Programmatically rotate the API key required for the data connection on a schedule using an out-of-the-box Qlik Application Automation template. This ensures the data connection is always operational. 
3. Get alerted whenever a new version of a monitoring app is available using Qlik Data Alerts. Repeat Step 1 to complete the update. 

The above allows you to deploy the monitoring apps to your tenant with a hands-off approach. Dive into the individual components below. 

Some monitoring apps are designed for specific Qlik Cloud subscription types. Refer to the compatibility matrix within the Qlik Cloud Monitoring Apps repository.

Content:

• Part One: 'Qlik Cloud Monitoring Apps Installer' template overview
• Part Two: 'Qlik Cloud Monitoring Apps API Key Rotator' template overview
• Part Three: How to setup a Qlik Alert to know when an app is out of date
• A Qlik Cloud Monitoring Apps Workflow Demo (Video)
• FAQ

Part One: 'Qlik Cloud Monitoring Apps Installer' template overview

This automation template is a fully guided installer/updater for the Qlik Cloud Monitoring Applications, including but not limited to the App Analyzer, Entitlement Analyzer, Reload Analyzer, and Access Evaluator applications. Leverage this automation template to quickly and easily install and update these or a subset of these applications with all their dependencies. The applications themselves are community-supported; and, they are provided through Qlik's Open-Source Software GitHub and thus are subject to Qlik's open-source guidelines and policies.

For more information, refer to the GitHub repository.

Features

• Can install/upgrade all or select apps.
• Can create or leverage existing spaces.
• Programmatically handles pre-requisite settings, roles, and entitlements.
• Installs latest versions from Qlik’s OSS GitHub.
• Creates required API key.
• Creates required analytics data connection.
• Can create custom reload schedules.
• Can reload post-install.
• Tags apps appropriately to track which are installed and their respective versions.
• Supports both user and capacity-based subscriptions

Click-through installer:

Flow:

Note that if the monitoring applications have been installed manually (i.e., not through this automation) then they will not be detected as existing. The automation will install new copies side-by-side. Any subsequent executions of the automation will detect the newly installed monitoring applications and check their versions, etc. This is due to the fact that the applications are tagged with "QCMA - {appName}" and "QCMA - {version}" during the installation process through the automation. Manually installed applications will not have these tags and therefore will not be detected.

 

Part Two: 'Qlik Cloud Monitoring Apps API Key Rotator' template overview

This template is intended to be used alongside the Qlik Cloud Monitoring Apps for user-based subscriptions template. This automation provides the ability to keep the API key and associated data connection used for the Qlik Cloud Monitoring Apps up to date on a scheduled basis. Simply input the space Id where the monitoring_apps_REST data connection should reside, and the automation will recreate both the API key and data connection regularly. Ensure that the cadence of the automation’s schedule is less than the expiry of the API key.

Configuration

Enter in the Id of the space where the monitoring_apps_REST data connection should reside.

Ensure that this automation is run off-hours from your scheduled monitoring application reloads so it does not disrupt the reload process.

Part Three: How to setup a Qlik Alert to know when an app is out of date

Each Qlik Cloud Monitoring App has the following two variables:

• vLatestVersion: the latest version of the app released on Qlik’s OSS GitHub.
• vIsLatestVersion: a Boolean of whether the app’s current version is equal to the latest version of the app released on Qlik’s OSS GitHub (1 if true, 0 if false).

With these variables, we can create a new Qlik Data Alert on a per-app basis. For each monitoring app that you want to be notified on if it falls out of date:

1. Right-click on a chart in the app, select Alerts and then Create new alert.
2. Clear out the defaults and provide the alert with a name such as <Monitoring App Name> is Out of Date.
3. Select Add measure and select the fx icon to enter a custom expression. Enter the expression ’$(vLatestVersion)'. Ensure it is wrapped in single quotes, then provide the label for the expression Latest Version.
4. Select Add measure and select the fx icon to enter a custom expression. Enter the expression $(vIsLatestVersion), then provide the label for the expression Is Latest Version.
5. Confirm the Details & data tab resembles the following:
   
   
   
   
6. Navigate to the next tab, Conditions.
7. Set the Measure to Is Latest Version, the Operator to Equal to, and the Value to 0. This way, if the app is not the latest version (0), it will trigger the alert.
8. Confirm that the Conditions tab resembles the following:
   
   
   
   
9. Navigate to the Distribution tab and confirm that the alert is evaluated When data is refreshed.

Here is an example of an alert received for the App Analyzer, showing that at this point in time, the latest version of the application is 5.1.3 and that the app is out of date:

A Qlik Cloud Monitoring Apps Workflow Demo (Video)

FAQ

Q: Can I re-run the installer to check if any of the monitoring applications are able to be upgraded to a later version?

A: Yes. Run the installer, select which applications should be checked and select the space that they reside in. If any of the selected applications are not installed or are upgradeable, a prompt will appear to continue to install/upgrade for the relevant applications.

Q: What if multiple people install monitoring applications in different spaces?

A: The template scopes the applications install process to a “target” space, i.e., a shared space (if not published) or a managed space. It will scope the API key name to `QCMA – {spaceId}` of that target space. This allows the template to install/update the monitoring applications across spaces and across users. If one user installs an application to “Space A” and then another user installs a different monitoring application to “Space A”, the template will see that a data connection and associated API key (in this case from another user) exists for that space already and it will install the application leveraging those pre-existing assets.

Q: What if a new monitoring application is released? Will the template provide the ability to install that application as well?

A: Yes. The template receives the list of applications dynamically from GitHub. If a new monitoring application is released, it will become available immediately through the template.

Q: I would like to be notified whenever a new version of a monitoring applications is released. Can this template do that?

A: As per the article above, the automation templates are not responsible for notifications of whether the applications are out of date. This is achieved using Qlik Alerting on a per-application basis as described in Part 3.

Q:I have updated my application, but I noticed that it did not preserve the history. Why is that?

A: The history is preserved in the prior versions of the application’s QVDs so the data is never deleted and can be loaded into the older version. Each upgrade will generate a new set of QVDs as the data models for the applications sometimes change due to bug fixes, updates, new features, etc. If you want to preserve the history when updating, the application can be upgraded with the “Publish side-by-side” method so that the older version of the application will remain as an archival application. However note that the Qlik Alert (from Part 3) will need to be recreated and any community content that was created on the older application will not be transferred to the new application.

With Qlik Application Automation, you can get data out of Qlik Cloud and distributing it to different users in formatted Excel. The workflow can be automated by leveraging the connectors for Office 365, specifically Microsoft SharePoint and Microsoft Excel. 

Here I share two example Qlik Application Automation workspaces that you can use and modify to suit your requirements. 

Content:

• Considerations
• Example 1: Scheduled Reports
• Example 2: On-Demand Reports
• Environment

Video:

Considerations

• This example is built on distributing a SharePoint link. It is also possible to use attachments with the Mail block (see Creating a Qlik Reporting Service report).
• Qlik Application Automation has a limit of 100,000 rows when getting data out of a Qlik Sense straight table object.
• The On-Demand example uses an extension in QSE SaaS to send data to the Automation. An update to the Qlik Sense Button object is expected soon, which will provide a native way to pass selections to an Automation.

Example 1: Scheduled Reports

1. Download the 'Scheduled Report.json' file attached to this document.
2. Create a new Automation in QSE SaaS, give it a name, and then upload the workspace you just downloaded by right clicking in the editor canvas, and selecting 'Upload workspace'.
3. Select the 'Create Binary File (Personal One Drive)' block, select 'Connection' in the block configurator to the right, and then create your connection to Microsoft SharePoint.
4. Select the 'Get Straight Table Data' block. Under 'Inputs' in the block configurator, lookup your the App Id, Sheet Id, and Object Id for the relevant QSE SaaS table you wish to output.
5. Select the 'Create Excel Table With Headers' block, select 'Connection' in the block configurator, and then create your connection to Microsoft Excel.
6. Select the 'Send Mail' block. Under 'Inputs' in the block configurator update the 'To' to reflect the addresses you wish to deliver to.
7. With the 'Send Mail' block still selected, select 'Connection' in the block configurator and add your Sender details.
8. To test, Save and then Run the Automation
9. If you receive any warnings or errors, navigate to the relevant blocks and ensure your Connection is selected in the block configurator. 
10. Select the 'Start' block. Under 'Inputs' in the block configurator, change Run Mode to Scheduled and define your required schedule. 

Example 2: On-Demand Reports

Note - These instructions assume you have already created connections as required in Example 1.

1. Download the 'On-Demand Report v3.json' file attached to this document.
2. Download and install the 'qlik-blends' extension. See: 
   https://github.com/rileymd88/qlik-blends/files/6378232/qlik-blends.zip
3. Create a new Automation in QSE SaaS, give it a name, and then upload the workspace you just downloaded by right-clicking in the editor canvas, and selecting 'Upload workspace'.
4. Ensure your Connections are selected in the block configurator for each of the following blocks, 'Create Binary File (Personal One Drive)', 'Create Excel Table With Headers', 'Add Rows To Excel Worksheet Table (Batch)', 'Create Sharing Link', and 'Send Mail'.  Save the Automation.
5. Select the 'Start' block and ensure Run Mode is set to Triggered. Make note of the of URL and Execution Token shown in the POST example. 
6. Open your chosen QSE SaaS application, and Edit the Sheet where you wish to add a Button to trigger an On-Demand report. 
7. Under 'Custom Objects' look for 'qlik-blends' from the Extensions menu and drag this into your Sheet.
8. Under the 'Blend' properties to the right, add-in your POST webhook URL and Token as noted in Step 5.
9. We will now add three measures to the 'qlik-blends' object. It is important you add them in the order described.  Add the first measure, using the following function in the expression editor: GetCurrentSelections()
10. Add the second measure, using the following function DocumentName()
11. The final measure will be the Object ID of the table you wish to use. To find the Object ID, select 'Done Editing'.  Then right click on the table, select 'Share', select 'Embed', then look for the Object ID under the preview. Copy this value, go back into Editing mode and paste this as your third measure value. 
12. With the 'qlik-blends' object selected, under Form select 'Add items'. For 'Item type' select Text. Under default value you can choose to add a default email address. For 'Label' and 'Reference'  type 'Email'. It is critical that Reference is updated to 'Email'.  Turn 'Required input' on. 
13. You can change the Appearance properties to suit your preferences, such as updating the Button label and message, enabling Dialog, and changing the Color under Theme.
14. Back in the Automation, under the Start Block. Set  'Run asynchronously' = yes to allow multiple requests to run at the same time (This will also increase the max run time from 1min to 60min)
15. Once happy, test the On-Demand report by entering an email and clicking the button.

This On-Demand Report Automation can be used across multiple apps and tables.  Simply copy the extension object between apps & sheets, and update the Object ID (Measure 3) for each instance. 

Environment

• Qlik Application Automation 
• Qlik Cloud 
• Microsoft Office 365

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

This article provides an overview of how to manage users using Qlik Application Automation. This approach can be useful when migrating from QlikView, or Qlik Sense Client Managed, to Qlik Sense Cloud when security concerns prevent the usage of Qlik-CLI and PowerShell scripting.

You will find an automation attached to this article that works with the Microsoft Excel connector. More information on importing automation can be found here.

Content

• Prerequisites
• Sheet Configuration
• Automation Configuration
• Running the Automation
• Considerations
• Related Content

Prerequisites

• Access to a Qlik Cloud tenant
• User assigned the role of Tenant Admin
• Office 365 account (for Microsoft Excel)

Sheet Configuration

In this example, we use a Microsoft Excel file as a source file to manage users. A sheet name, for example, Users, must be added and this must also be provided as input when running the automation. The sheet must also contain these headers: userId, Name, Subject, Email, Roles, Licence, and Flag.

Example of sheet configuration:

If users are to be created the Flag column must be set to create. If users are to be deleted, there's no need to include roles, but Flag must be set to delete.

Automation Configuration

1. Add an Input block that takes the name of the worksheet from which data should be read as input. You also need to specify the first and last cell to read data from, as well as if users are to be created or deleted.
   
   
   
   
2. Add two variables of the type number. One to keep track of created users and one to keep track of deleted users. These variables will be used to update the run title when the automation has been completed. Only one of them will be used when running the automation since only one of the modes can be used (Create or Delete). Let's call the variables UsersCreatedCounter and UsersDeletedCounter.Intially set these variables to 0.
   
   
3. Add the Get Current Tenant Id block from Qlik Cloud Services Connector.
   
   

4. Add the List Rows With Headers block from the Microsoft Excel connector to read the values that have been configured in the Excel sheet. 

   • Use the "do lookup" function to find the Drive ID and Item ID of the file you will be using as a source. 
   • Configure the other fields to get the values from the input fields. 
     
     
     
     
5. Inside of the List Rows With Headers loop add the Search Users block from the Qlik Cloud Services connector. Configure Fields and Filter input parameters as shown below.
   
   
   
   
6. Add a Condition block to check if the user exists, if we're in Create mode, and if the Flag column in the Excel file is set to create.
   
   
   
   
   
7. If the conditions are true,  add the below variables by initially setting all these variables to empty:
   
   
   1. Roles: List variable to store a list of roles that needs to be assigned to the user. Configure the variable by clicking on Add operation button and selecting the 'Merge other list into Roles' option. In the List field, use explode formula to convert comma-separated roles from the Role column in the Excel file into a list.
      
      
      
   2. AssignedRoles: Variable of type object to store the role ID as key-value pair.
   3. AssignedRolesList: List variable to store the AssignedRoles object variable as an item.
      
      
8. Add a Loop block to loop through the Roles list variable where the roles of the user are stored from the Excel file.
   
   
   
9. Add the List Roles block from the Qlik Cloud Services connector to retrieve the IDs of the roles. Configure the Filter input parameter as shown below.
   
   
   
10. Add AssignedRoles object variable to store role ID. Configure the variable by clicking on Add operation button and selecting the 'Set key/values of the AssignedRoles' option. Click on Add key/value button and use the ID as the key and the ID from the output of the List Roles block as the value.
    
    
    
    
11. Add the AssignedRolesList variable to store the AssignedRoles object variable as an item to this list variable. To do this click on Add operation button and select the 'Add item to AssignedRolesList' option. In the Item field map the AssignedRoles object variable.
    
    
    
    
12. Add the Raw API Request block from the Qlik Cloud Services connector to create the user. Configure the block as shown below.
    
    
    
    
13. Add the Condition block to check if the user has been created. If the condition is true increment the UsersCreatedCounter variable by 1.
    
    
    
    
    
    
14. Add the Condition block to check if we need to allocate a license to the user created in the above step.
    
    
    
    
15. If the conditions are true, add the Raw API Request block to allocate a license to the user. Configure the input parameters as shown below.
    
    
    
    
16. If the first condition in the List Rows With Headers loop is false, then use another Condition block to find out if we are in Delete mode, if the flag column in the Excel file is set to delete, and if the user exists.
    
    
    
    
17. If the conditions are true, add another Condition block to check if the user has a named license.
    
    
    
    
    1. If the condition outcome evaluates to true, add the Raw API Request block to deallocate the user's license. Configure the input parameters as shown below.
       
       
       
       
       
18. Add the Raw API Request block to delete the user. Configure the input parameters as shown below.
    
    
    
    
19. Add the UsersDeletedCounter variable and increment it by 1.
    
    
20. The last part of this automation is to check the mode and update the automation's run title to display how many users have been created or deleted.
    
    
    
    
    
    

Running the Automation

When running the automation you must provide input to the automation, this includes the name of the worksheet to read data from. You also need to specify the first and last cell to read data from, as well as if users are to be created or deleted. Example :

Considerations

• A multitenant scenario can be supported by utilizing the Qlik Platform Operations connector instead of the Qlik Cloud Services connector. 
• Google Sheets could be used instead of Microsoft Excel.

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.

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Environment

• Qlik Cloud 
• Qlik Application Automation

This article provides a step-by-step guide on building a write back solution with only native Qlik components and automations. 

Content:

• Environment
• Write back use cases
• 1. Ticket creation
• 2. Data annotation
• 3. Update records
• Tutorial: ticket creation
• 1. Configuring the button in the app
• 2. Configuring the automation
• Configuring the toast notification
• Reloads
• Limitations

Disclaimer for reporting use cases: this solution could produce inconsistent results in reports produced with automations; when using the button to pass through selections, the intended report composition and associated data reduction for the report may not be achieved. This is due to the fact that the session state of Qlik Application Automation cannot be transferred to the report composition definition that is passed to the Qlik Reporting Service.

Environment

• Qlik Sense app
• Qlik Application Automation
• A business tool that's used as the data source (we'll use HubSpot in this example)

Write back use cases

When analyzing results in a Qlik Sense app, it could happen you spot a mistake in your data or something that seems odd. To address this, you may want someone from your team to investigate this or you may want to update data in your source systems directly without leaving Qlik. Or maybe your data is just fine but you want to add a new record from within Qlik without having to open your business application. These scenarios fit in the following use cases:

1. Ticket creation: create a ticket to ensure a data review or update task will get followed up by your data team
2. Data annotation: add a comment or tag to one or more records in your source data 
3. Data change: add new records or update existing ones
   
   

1. Ticket creation

This is the least intrusive form of writing back that delegates the change to someone in your data team. The idea is that you create a ticket in a task management system like Jira or ServiceNow. Someone from your team will then pick up the ticket, investigate your comment, and review the data. The difference with sending an alert or email is that the ticketing system guarantees that the request is tracked.

2. Data annotation

Another option to communicate changes is to write a comment or a tag for one or more records directly to the source system. This could be a comment on a deal record in your CRM or it could be stored in a separate database table if you're loading data from a database.

3. Update records

The final use case allows for updating records directly from within the sheet. Make sure you know who has access to the button before setting this up since this will allow users to change records directly.

Tutorial: ticket creation

All the above use cases can be realized in the same way: by configuring a native Qlik Sense button in your sheet to run an automation. Before you start this tutorial, make sure you already have an app and a new, empty automation. The tutorial has 2 parts:

1. Configuring the button in the app
2. Configuring the automation

1. Configuring the button in the app

To configure the app, we'll use the following native Qlik Sense components:

• Button: Used to trigger the automation.
• Variable input: Used to allow users to specify parameters to use in the automation (for example, a variable to store a comment).
• Container: Used to group the variable inputs and the button for a better user experience.
• Table: Used to easily select records for the data annotation or ticket creation use case.

Steps:

1. Open your app and add the Container component to a sheet that already contains a Table with records. Then add (a) Button to the Container component. To configure the button, click the (b) Container and go to (c) Edit properties on the button. Feel free to give the button a proper label, in this tutorial, we'll use "Create Jira ticket". 
   

   
   

2. Configure the button under the 'Actions and navigation' tab by adding a new action and setting it to 'Execute automation' and configure the automation parameter to use the empty automation you created earlier. You can only configure an automation that you own. It is not possible to configure someone else's automation. Tip: you can use the 'View this automation' link to open the automation editor in a new tab.
   

   
   

3. Check the "Include selections" option. This way, on each click, the button will create a temporary bookmark and send its ID to the automation. The temporary bookmark contains the selections that were active when the button was clicked and also the variable state which contains any values the user has supplied for variables through the Variable Input components.
   
   

   

4. Check the "Run mode: triggered" option as well. This will allow everyone who has access to the sheet to run the automation by clicking the button. If you don't select this checkbox, the automation will be executed over an API call, and only users with permission to run the automation will be able to run it through the button. Currently, only the automation owner has this permission.
   
   
   
   

5. Enable the "Show notifications" toggle, this will send a toast notification back to the user in the sheet after the automation completes. Feel free to increase the duration.

6. Add new variables to your app. Do not use load script variables for this; instead, create the variable through the Edit Sheet page. Create the following variables, only give them a name, and you can leave the other fields blank.
   
   1. title_for_jira
   2. comment_for_jira
   3. assignee_for_jira
      
      
7. Add a Variable Input component for each variable to the Container component that already has the Button from earlier. Re-arrange the components in the Container so the Button is last. Set the 'Show as' parameter for the Variable input for the ticket title and comment to the 'Input box'. For the ticket assignee, set it to 'Drop down'.
   
   Note: you'll find the Variable Input under the 'Custom objects' category.
   
   

   

8. To configure the dropdown, you'll need the user IDs of the possible assignees for the Jira ticket. One way of getting those is to use the List Users block in the Jira connector in an automation. Once you have the IDs, configure the dropdown 'Values' parameter by adding alternative values. The Value should be the user's ID and the Label should be the user's name.
   
   

    

9. Your sheet should now look like this:
   
   

   Tip: using a Container component will allow your variable inputs & button to scale better for smaller screens. 
   
   
   
   

2. Configuring the automation

1. Click the 'Copy input block' button in the Button's configuration section. This will copy a preconfigured Inputs block and Apply Bookmark block to your clipboard to get you started with the automation. Next, click the 'View this automation' link to open the automation editor in a new tab.
   

   
   

2. Right-click in the automation canvas and select 'Paste Block(s)'. Connect the new blocks to the Start block. The Apply Bookmark block will ensure that any selections applied by the user, together with the variables state (whatever the user configured for the variables before clicking the button), are available in the automation session.
   
   

   

3. Add a List Current Selections block, and configure it to use the App parameter provided through the Inputs block. This block will return all records the user selected (because they're sent over through the temporary bookmark).
   

   
   

4. Add the Get Expression block for each variable. Configure it to use the App parameter provided through the Inputs block. Use the following format for the expression, =variablename. For example: =title_for_jira. Do the same for the comment and assignee variables.
   
   

   

5. If you haven't already, this is a good point to make a selection, configure the Variable Inputs and click the button from within the app and make sure that each block is returning the correct selections/variable values. Doing this will make it easier to configure the other blocks.
   
   
6. Add a Create Issue block from the Jira connector and configure the following parameters by using the do lookup functionality. Project, Issue Type & Priority. These will be hard-coded for each new issue.
   
   Tip: use a staging or test project in Jira while building the automation.
   
   
7. Map the expression value for the Summary parameter to the output of the Get Expression Value block that's retrieving the ticket title. Do the same for the assignee and set the Comment variable as the ticket's description.
   
   

   
   
   

8. The deal IDs should be added as a comma-separated list to the issue's Description:
   
   1. Click the description input field and select the output from the List Current Selections block. Click the (a) values list and chose the 'Select first item from list' option on the next screen:
      

      
      

      
      
      

   2. Upon automation run, this will resolve to the first text value selected for the field hs_object_id (which corresponds to the deal ID from HubSpot). To update this to a comma-separated list of IDs, the mapping must first be changed to output a list of all values for hs_object_id. To do this, toggle the formula parsing:

      

   3. Change the final 0 in the formula to an asterisk '*', and turn the formula parsing back on.
      
      
      
      
   4. Click the mapping and choose 'Add formula' from the context menu. Then, search for the Implode formula. This formula will turn a list into a comma-separated list. Configure it to use a comma as a separator:
      
      
      
      
      
      
   5. Do a new test run by selecting multiple deals in your sheet and then clicking the button, this should create a new ticket in Jira with the deal IDs as a comma-separated list.
      

      
      
      
      

9. Add an Update Run Title block to the end of the automation. This will show a toast notification to the user who clicked the button after the automation is completed. Learn more about configuring this and who can see the notification in the next part of this article: "Configuring the toast notification".
   

   
   

   The resulting toast notification in the Qlik Sense app:
   
   

   

Bonus: add a link to the toast notification

Instead of showing a plain message in the toast notification, it's also possible to include a link to point the user to a certain resource. This can be done by configuring the Update Run Title block with the following snippet:

{"message":"Ticket created", "url": "https://<link to jira ticket>"}

Configuring the toast notification

Depending on the button's configuration and the automation run mode, use either the Update Run Title block or the Output block to show the toast notification.

See the below table for each option:

The run mode in the button can be configured by toggling the 'Run mode: triggered' option in the button's settings: 

The run mode in the automation can be configured here in the Start block:

Reloads

After writing back to your source systems, you'll want to do a reload to see your changes reflected in the app. Be mindful of the impact of doing these reloads. If multiple people are using this button at the same time, you don't want to do a reload for each update. 

Problems: 

1. Reload concurrency: the same app can not be reloaded in parallel. If multiple people are using the button at the same time, it won't be possible to do reloads for every click on the button.

Improvements:

1. Partial reloads: use partial reloads to only load new data into the app. This way the reload takes less time.
2. Separate reloads: do not use the automation triggered by the button for reloads. Instead, use a separate process for this. For example:
   1. An additional button on the app that triggers reloads.
   2. A scheduled reload.
   3. Another automation with a "List Incremental" block that runs on a schedule and reads changes from the source. It will trigger a reload only if new records are available in the source. Note: not every connector in automations has an incremental block.

Limitations

1. Public access in triggered mode: when the button is set to run the automation in triggered mode, everyone who can access the sheet and click the button will be able to execute the automation.
2. No impersonation: when the automation runs, it will use the automation owner's Qlik account for the Qlik Cloud & Qlik Reporting connectors. It's not possible to impersonate the user who clicked the button. This means that any form of section access is not applied to the user who clicked the button. 
3. No parallel runs: the automation can not run in parallel. New runs get queued with a maximum queue size of 200 runs.
4. Execution token is visible: when the button is set to run the automation in triggered mode, clicking the button exposes the automation's Execution Token from the network traffic in the developer console. This token can only be used to trigger that automation and has no use for other automations or other APIs. Generating a new token can be done by copying the automation.
5. Toast notification timeout: the button will wait on the automation for a maximum of 10 minutes to return the toast notification. If the automation takes longer, it will still run to completion, but no toast notification will be shown.
6. General limits: more information on limitations can be found here: 
   
   1. Button limits
   2. Automation limits

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.