Facebook Ads integration extraction fails with the following error: 

SingerSyncError POST: 400 Message: (#3018) The start date of the time range cannot be beyond 37 months from the current date.

Resolution

If you are suddenly seeing this error, it is likely due to resetting the integration or table while having an older Start Date. 

To resolve, change the Start Date in your Facebook Ads integration settings to a value within the last 37 months. This aligns with Facebook's current policy and allows the integration to function properly.

If you have any questions about this limitation or to discuss potential options for accessing older data, please contact Facebook. They may have additional insights or alternative solutions for businesses needing to access older advertising data.

Going forward, it's important to be aware of this 37-month limitation when working with Facebook Ads data, especially when setting up or resetting integrations. Regular data backups or exports might be advisable to retain historical data beyond this window for long-term analysis and reporting needs.

Can we find out who changed the date? 

Qlik Stitch does not track this type of user activity. You will need to check with other users in your organisation. 

Cause

This is a Facebook Ads API limitation documented by Stitch.

Environment

• Qlik Stitch

To investigate Task failure, It is necessary to collect the Diagnostics Package from Qlik Cloud Data Integration.

Option One: Project-level

1. Click on the 3 dots menu of the task in question
2. Click View task logs
   
   
   
   

Option Two: Monitor view within the task

1. Click on the 3 dots menu in the right-hand corner
2. Click View task logs
   
   
   
   
   
3. Once the logs are open, click Download
4. Select Diagnostics package
5. Click Download
   
   
   
   
   
6. A small notification will pop up at the top of the page when the download starts:
   
   
   
   And then when it completes:
   
   
   
   
   

Often, Support will request that specific logging components be increased to Verbose or Trace in order to effectively troubleshoot. To modify, click on the "Logging options" located in the right-hand corner of the logs view. The options presented in the UI do not use the same terminology as what you see in the logs themselves. For better understanding, please refer to this mapping:

Please note that if the View task logs option is not present in the dropdown menu, it indicates that the type of task you are working with does not have available task logs. In the current design, only Replication and Landing tasks have task logs.

Environment

• Qlik Data Gateway  
• Qlik Cloud 

This article gives an overview of the available blocks in the dbt Cloud connector in Qlik Application Automation.
The purpose of the dbt cloud connector is to be able to schedule or trigger your jobs in dbt from action in Qlik Sense SaaS.

Authentication

Authentication to dbt Cloud happens through an API key. The API key can be found in the user profile when logged into dbt Cloud under API Settings. Instructions on the dbt documentation are at: https://docs.getdbt.com/dbt-cloud/api-v2#section/Authentication

Available Blocks

The blocks we have available are built around the objects Jobs and Runs. Furthermore for easy use of the connector there are helper blocks for accounts and projects. For any gaps we have raw API request blocks to allow more freedom to end users where our blocks do not suffice.

Blocks for Jobs:

• List Jobs
• Get Job
• Run Job

Blocks for Runs:

• List Runs
• Get Run
• List Run Artifacts
• Wait for Run to Finish
• Cancel Run

How to run a job and reload Qlik App:

The following automation is added as an attachment and shown as an image and will run a job in dbt Cloud and if successful reloads an app in Qlik Sense SaaS. It will always send out an email, this of course can be changed to a different channel. Also it would be possible to extend this to multiple dbt jobs:

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 aims to answer the following questions:

• Is Stitch real-time?
• Why is my data taking so long to replicate?
• What is the ETL process for Stitch like?
• And what can it tell me about where my data is? 

Stitch Replication Overview

Stitch is a cloud-based ETL platform, which means it is not real-time and may experience latency due to the nature of cloud infrastructure and its step-based processing model.

Replication Process

Stitch’s replication process consists of three independent steps: 

Extraction → Preparation → Loading

Each step takes time to complete and is influenced by various factors.

For more information, see: Stitch’s Replication Process | stitchdata.com

Performance Factors

The speed and efficiency of Stitch’s replication process can be affected by:

• Volume and size of data: Impacts both extraction and loading times.
• Data structure: Flat data is processed more quickly; nested structures (e.g., JSON) can slow extraction.
• Source system/API limitations: API quotas and rate limits can delay extraction.
• Destination system performance: Affects how quickly data can be loaded.

These factors can vary over time and across integrations, which is why replication durations are not always predictable.

Extraction

The replication frequency determines how often Stitch initiates a new extraction job (when one isn’t already in progress). Stitch tracks your tables and updates them based on the replication method you’ve selected.

However, this frequency does not guarantee that data will be prepared and loaded within the same time window. For example, a 30-minute frequency does not mean the full replication cycle completes in 30 minutes.

Stitch extracts one table at a time per integration (sequentially). It must finish extracting one table before moving to the next.

Preparation

Once data is extracted, Stitch begins the preparation phase, which involves cutting records into rectangular staging files. This step is batch-based and starts as soon as data is returned from the source. The duration of this phase depends on the structure and volume of the data.

Loading

Stitch can load up to 5 tables concurrently per destination. If 5 tables are already loading, others must wait until a slot becomes available. For example, with 10 integrations and 20 tables each, Stitch will load 5 tables at a time per destination.

Stitch’s loading systems check every 15–20 minutes for batches of records that are fully prepared and ready to be loaded into your destination.

What may appear as missing data is often just incomplete processing. Most data discrepancies resolve themselves once Stitch finishes processing.

Related Content

• Replication Frequency
• System architecture
• Data Loading

Environment

• Qlik Stitch

The Qlik Cloud and Qlik Sense Enterprise on Windows Straight Table come with a menu option to Adjust Column Size.

Clicking this option does not have an immediate effect. 

What does it do?

Adjust Column Size sets the column into a state that allows you to change its width using your arrow keys. Once in this state, you can use the left and right arrow keys to make the column larger or smaller. 

Environment

• Qlik Cloud
• Qlik Sense Enterprise on Windows

IBM DB2 iSeries connector in Qlik Cloud Data Integration requires setting up a Data Gateway - Data Movement (see Setting up Data Movement gateway) and installing the supported DB2 iSeries ODBC driver on the same server (see Preparing the installation | IBM DB2 for iSeries).

This article aims to guide you through the process.

Currently, Qlik Cloud Data Integration supports DB2i ODBC driver version 1.1.0.26, as can be confirmed by viewing the /opt/qlik/gateway/movement/drivers/manifests/db2iseries.yaml after the data gateway is installed.

Steps

1. After the data gateway is set up, run the following on your server:

   • cd /opt/qlik/gateway/movement/drivers/bin

   • sudo mkdir -p /opt/qlik/gateway/movement/drivers/db2iseries

   • sudo wget -O /opt/qlik/gateway/movement/drivers/db2iseries/ibm-iaccess-1.1.0.26-1.0.x86_64.rpm   “https://public.dhe.ibm.com/software/ibmi/products/odbc/rpms/x86_64/ibm-iaccess-1.1.0.26-1.0.x86_64.rpm”

   • ./install db2iseries

   • sudo systemctl restart repagent

2. Once this is complete and you verify your gateway is running (sudo systemctl status repagent), continue to set up the source connector.

To ensure CDC works with this connector, set the internal property useStorageForStringSize to true. There is a known issue with BOOLEAN datatype and driver version 1.1.0.26, and this parameter will ensure smooth replication. Otherwise, you will see an error like:

[TASK_MANAGER ]I: Starting replication now (replicationtask.c:3500
[SOURCE_CAPTURE ]E: Error parsing [1020109] (db2i_endpoint_capture.c:679
[TASK_MANAGER ]I: Task error notification received from subtask 0, thread 0, status 1020109 (replicationtask.c:3641
[TASK_MANAGER ]W: Task 'TASK_gG1--Wsyl3drvCJf636TqQ' encountered a recoverable error (repository.c:6372)
[SORTER ]I: Final saved task state. Stream position QCDI_TEST:QSQJRN0001:6504, Source id 3, next Target id 1, confirmed Target id 0, last source timestamp 1759171643379185 (sorter.c:772)
[SOURCE_CAPTURE ]E: Error executing source loop [1020109] (streamcomponent.c:1946)
[TASK_MANAGER ]E: Stream component failed at subtask 0, component st_0_EP_SYcKapbEJQZiVETw_g5z4w [1020109] (subtask.c:1504)
[SOURCE_CAPTURE ]E: Stream component 'st_0_EP_SYcKapbEJQZiVETw_g5z4w' terminated [1020109] (subtask.c:1675)

To configure useStorageForStringSize:

1. Set the Internal Parameter 
   
   Name: useStorageForStringSize
   Value: true
   
   
   
   
2. Then run Recreate Tables on the task after the parameter is set

Environment

• Qlik Talend Cloud

The Qlik Talend tESBConsumer component fails to call a web service with the error:

Unable to create message factory for SOAP: Error while searching for service

This may occur after recently upgrading Qlik Talend and moving from JDK 11 to JDK 17. Post upgrade, the following error is encountered when calling a web service using tESBConsumer:

##Log##
tESBConsumer:Failed webservice call- Problem writing SAAJ model to stream
[WARN ] 13:14:53 org.apache.cxf.phase.PhaseInterceptorChain- Interceptor for {http://xmlns.oracle.com/Enterprise/Tools/services}PROCESSREQUEST#{http://xmlns.oracle.com/Enterprise... has thrown exception, unwinding now
org.apache.cxf.binding.soap.SoapFault: Problem writing SAAJ model to stream: Unable to create message factory for SOAP: Error while searching for service [jakarta.xml.soap.MessageFactory]
Caused by: jakarta.xml.soap.SOAPException: Unable to create message factory for SOAP: Error while searching for service [jakarta.xml.soap.MessageFactory]
    at jakarta.xml.soap.MessageFactory.newInstance(MessageFactory.java:96) ~[jakarta.xml.soap-api-3.0.2.jar:3.0.2]
    at org.apache.cxf.binding.soap.saaj.SAAJFactoryResolver.createMessageFactory(SAAJFactoryResolver.java:57) ~[cxf-rt-bindings-soap-4.1.0.jar:4.1.0]
    at org.apache.cxf.binding.soap.saaj.SAAJOutInterceptor.getFactory(SAAJOutInterceptor.java:86) ~[cxf-rt-bindings-soap-4.1.0.jar:4.1.0]
    at org.apache.cxf.binding.soap.saaj.SAAJOutInterceptor.handleMessage(SAAJOutInterceptor.java:122) ~[cxf-rt-bindings-soap-4.1.0.jar:4.1.0]
    ... 16 more

Resolution

To resolve this, the necessary SAAJ implementation and its dependencies must be explicitly provided as separate libraries in the application's classpath. This typically involves including the following:

• Jakarta SOAP API: This provides the API interfaces for SAAJ.
• The dependencies, which can be added to the Studio job by utilizing tLibraryLoad components to load the compatible saaj-impl jar: 
  
  https://repo1.maven.org/maven2/com/sun/xml/messaging/saaj/saaj-impl/3.0.2/saaj-impl-3.0.2.jar
  https://repo1.maven.org/maven2/com/sun/xml/messaging/saaj/saaj-impl/3.0.4/saaj-impl-3.0.4.jar

Cause

The jakarta.xml.soap.SOAPException 'Unable to create message factory for SOAP error', specifically mentions an error while searching for the service [jakarta.xml.soap.MessageFactory]. This indicates a problem with the availability or configuration of the SAAJ (SOAP with Attachments API for Java) implementation.

This issue commonly arises in environments using Java 11 or later, as JAX-WS and its related technologies, such as SAAJ, were removed from the standard Java Development Kit (JDK) in these versions.

Environment

• Qlik Talend Studio

Long access times to Qlik Cloud or when performing reloads using the Direct Access Gateway may be caused by high network latency between your location and the AWS datacenter hosting the affected tenant. 

A possible browser test to check the network connection from a computer to AWS can be found at AWS Latency Test.

This test does not concern Qlik Cloud's platform, and can therefore be used to determine if there are purely network-related issues.

1. Find the correct AWS region for your tenant. You can do so by cross-referencing regions and IP addresses as documented in Allowlisting domains and IP addresses.
   
   For instance, the region for .de tenants is in Frankfurt:
   
   
   
   
2. On the AWS Latency Test, select your region and a couple of other ones to compare results
   
   
   
   
3. Wait for the test results to be returned:
   
   
   
   
4. In case of immediate apparent problems, involve your network team to discuss possible remediations

This is just a first-step tool, not a conclusive one. A latency of 300ms or more might still not affect user experience in Qlik Cloud, but it's still worth using the tool quickly for a first assessment.

Related Content

How to verify and measure transfer speed from Direct Access gateway to Qlik Cloud

Environment

• Qlik Cloud Analytics

In a setup with a local and remote Qlik Replicate server, the remote server's IP address has changed. Does this IP address change require any additional configuration steps?

Resolution

To avoid any issues after an IP address change:

1. Stop all file channel replication tasks on the local Qlik Replicate server
2. Stop all file channel replication tasks on the remote Qlik Replicate server
3. Update the remote Qlik Replicate server IP address in all local file channel tasks
4. Resume the file channel tasks on the remote Qlik Replicate server
5. Verify the connection to the remote Qlik Replicate server
6. Resume all file channel tasks on the local Qlik Replicate server.

Environment

• Qlik Replicate

Is it possible to limit the available output formats for an OnDemand report, such as only allowing PDF rather than allowing multiple formats?

Answer

Qlik NPrinting On-Demand Reports cannot be limited to a certain format (such as PDF). The Qlik Sense On-Demand reporting object will continue to present all available formats to export On-Demand reports to. This is by design.

Environment

• Qlik NPrinting

In some cases, the otherwise correctly enabled Qlik NPrinting audit feature fails to produce output. For information on how to correctly enable auditing, see Audit trail.

Resolution

On the Qlik NPrinting Server:

Always export and backup your client_audit certificate before proceeding.

1. Open the Services MMC from the Windows server control panel
2. Stop the Qlik NPrinting auditing service
3. Open the Windows Certificate Manager > Certificates > Local Computer > Personal certificate folder
   
   
    
4. Delete the client_audit certificate from the cert store shown in the image above
5. Start the Qlik NPrinting Audit service

This will result in the creation of a new certificate and enable the audit service to work normally once again.

Cause

The client_audit certificate that secures the Qlik NPrinting auditing service has become corrupted or contains an invalid signature.

Environment

• Qlik NPrinting

The Qlik Analytics Migration Tool provides a structured and repeatable process for migrating analytics assets to Qlik Cloud. It enables teams to define migration plans, validate each step, and coordinate across roles to ensure secure and accurate execution.

Content

• Core Capabilities
• What Makes the Tool Different
• Why Move to Qlik Cloud
• How to Get Started
• Qlik Analytics Migration Tool (Quick Video Demo)

Core Capabilities

• Migrate Qlik Sense Client-Managed apps, streams, users, groups, data files, data connections, and much more
• Preserve content ownership, access rights, and user-generated content such as apps, private and community sheets, as well as bookmarks through dynamic user mapping
• Automatically rewrite load scripts to reflect updated cloud data connections and paths
• Configure structured plans and jobs to manage projects at scale
• Enable multi-user access to support collaboration and phased execution
• Log, validate, and roll back migration steps as needed
• Partially supports QlikView and Qlik NPrinting migrations to reduce redevelopment

What Makes the Tool Different

• Designed from real-world experience and refined for enterprise use
• Fully branded, hardened, and extended since acquisition
• Supports phased and repeatable execution across migration stages
• Adjusts load scripts and metadata automatically during migration
• Maintains user identity, private content, and access policies

Why Move to Qlik Cloud

Qlik Cloud provides continuous innovation, centralized governance, and integrated AI that is not available in on-premises environments. Customers migrating to Qlik Cloud immediately benefit from:

• Qlik Predict for AI-driven forecasting and predictions built into dashboards
• Qlik Answers for intuitive, natural language search and explanation
• Continuous cloud-native feature delivery with automated upgrades
• Real-time access to governed and streaming data sources
• Simplified DevOps, reduced infrastructure management, and tighter security control

How to Get Started

• Download the Qlik Analytics Migration Tool from Qlik's Download page. 
  
  
  
  
• Review full documentation at Qlik Analytics Migration Tool overview | Help.qlik.com 

Qlik Analytics Migration Tool (Quick Video Demo)

Learn More, Ask Questions, Share Experiences

The Qlik Community is the central place to get answers, exchange ideas, and collaborate with peers using the Qlik Analytics Migration Tool. Whether you're preparing for a full environment shift or running phased pilots, we encourage you to share your approach and learn from others moving to Qlik Cloud in the Move to Cloud forum.

Environment

• Qlik Cloud

Over a period of time, attrep_changes tables will significantly contribute to the overall storage cost as the image of a dropped table will persist on Snowflake Storage for the purpose of Time Travel and Fail-Safe (see Working with Temporary and Transient Tables | docs.snowflake.com for details).

Resolution

Create the attrep_changes table as a transient with a limited-to-absent support for Time Travel and Fail Safe. This needs to be done in Snowflake.

1. Create a transient schema (CREATE SCHEMA | docs.snowflake.com) with:
   
   
   • DATA_RETENTION_TIME_IN_DAYS set to 0
     
     
     
     
   • MAX_DATA_EXTENSION_TIME_IN_DAYS set to 0 (Maximum number of days for which Snowflake can extend the data retention period for tables to prevent streams on the tables from becoming stale)
     
     See MAX_DATA_EXTENSION_TIME_IN_DAYS for more information.
     
     
2. In Qlik Replicate, configure the task so that all of the control tables will be created in the transient schema:
   
   
   

Example:

CREATE OR REPLACE TRANSIENT SCHEMA IF NOT EXISTS TRANSIENT_SCHEMA
        DATA_RETENTION_TIME_IN_DAYS = 0
        MAX_DATA_EXTENSION_TIME_IN_DAYS = 0
        COMMENT = 'Transient Schema for Qlik Replicate Control Tables';

No out-of-the-box solution exists in Qlik Replicate for a configurable option to create the attrep_changes table as a transient one. Log an Idea with Qlik if this is a requirement.

Cause

• attrep_changes tables are defined for each task and are dropped or created for each bulk being applied to the target
• attrep_changes tables are created as normal SF tables, which means that they have a Time Travel and Fail-Safe feature enabled (storing old data images and mirroring data)
• The volume of uncompressed data in each instance of attrep_changes table usually varies between 500 MB and 2 GB
• Usually, customers configure a bulk to be dropped into Snowflake every 10 to 20 minutes.
• If we assume that the data is stored uncompressed, then a worst-case scenario would be:
  • 2GB * 6 drops/hour * 24 hours * 90 days (default data retention in enterprise account) = 25,920GB à 26 billable Terabytes after 90 days.
  • Even with a 60% compression ratio, this still produces 9 TB per table after 90 days.

Environment

• Qlik Replicate

If users are behind a proxy, the Qlik Web Connector may return the following errors:

• 407 proxy authentication errors and
• 503 Service Unavailable

Environment:

Qlik Web Connectors 

Under these circumstances, the user has to configure the proxy from the deploy.config file, which is normally located in the root of your Qlik Web Connectors folder.

Disabling the proxy:

This is the best approach for Error 503 Service Unavailable errors. 

Open the deploy.config file, search for Proxy in order to locate the settings and configure them as below.

<Proxy>
    <UseProxy>false</UseProxy>
    <ProxyAddress></ProxyAddress>
    <ProxyUsername></ProxyUsername>
    <ProxyDomain></ProxyDomain>
    <ProxyPassword></ProxyPassword>
</Proxy>
 

Configuring the proxy - Setting it up to true:

This is the best approach for 407 proxy authentication errors. 

If you are behind a proxy you will just need to set UseProxy to true and you might need to enter the proxy credentials as below.

<Proxy>
    <UseProxy>true</UseProxy>
    <ProxyAddress>proxy.sub-domain.mymaindomain.com:port</ProxyAddress>
    <ProxyUsername>username</ProxyUsername>
    <ProxyDomain></ProxyDomain>
    <ProxyPassword>password</ProxyPassword>
</Proxy>

The Data Load Editor in Qlik Sense Enterprise on Windows 2025 experiences noticeable performance issues.

Resolution

The issue is caused by defect SUPPORT-6006. Qlik is actively working on a fix.

Fix Version

A fix is planned for the next possible patches. Review the Release Notes for SUPPORT-6006.

Workaround

A workaround is available. It is viable as long as the Qlik SAP Connector is not in use.

1. In a Windows file browser, navigate to C:\Program Files\Common Files\Qlik\Custom Data\
2. Move the QvSapConnectorPackage directory to a different location

No service restart is required.

Internal Investigation ID(s) 

SUPPORT-6006

Environment

• Qlik Sense Enterprise on Windows

Qlik Sense and Vulnerability “CVE-2025-7783” in NPM Library form-data

In mid-July 2025, a vulnerability was disclosed in the NPM library form-data (GitHub Security Advisory). Qlik became aware of this issue through its standard Secure Development Lifecycle (SDL) processes.

Following an internal review, Qlik R&D and Security teams identified that potentially vulnerable versions of the form-data library were included in some installations of Qlik Sense Enterprise for Windows. However, due to the specific way Qlik utilizes this library, the conditions required for exploitation are not met.

Although the vulnerability was determined to be non-exploitable within Qlik Sense, customers who prefer to upgrade to a version that includes the patched form-data library can do so by installing one of the following releases:

• May 2025 Patch 6
• November 2024 Patch 18 
• May 2024 Patch 24 

Note: An earlier version of this information was mistakenly published indicating that this CVE was directly related to Qlik Sense for Windows.

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

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 Analytics
• Qlik Automate

Description

• Error "Object reference not set to an instance of an object" when previewing NPrinting Designer Excel Template Editor reports that contain merged cells

Diagnosis:

• After upgrade, open an NPrinting Report in the NP designer and preview a report that his known to contain merged cells
• Preview the Report
• Error encountered "The preview request failed with message: Object reference not set to an instance of an object"

Environment

• Discovered following an upgrade from older unsupported NP versions (NP November 2019) to Current Supported NP versions

Resolution

• Please note that this issue has been resolved and will be available in NPrinting May 2022 SR 4.
• Keep an eye on the Qlik Community Downloads site and Product release notes for new product and service releases.

Workaround:

• None at this time

Cause

• Product Defect ID: OP-95768

Related Content

• Release Notes | Qlik Community
• Downloads | Qlik Community

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.