In September 2022, we introduced our own product QOps. DataLabs team fully accompanies the client during the installation and use of the product and offers 24/7 support. We regularly receive feedback regarding QOps usage, that allows us to look at our own product through the user’s eyes. Below we have prepared answers to the most common questions:

1. Are triggers and additional properties saved for Qlik apps?

Yes. However, it is worth considering that some properties require a minimal data model to be maintained in the application. To do this, QlikView provides a «reduce» mode.

For Qlik Sense apps, an additional «always one selected» field is retained. To do this, it is necessary to save selections additionally, since this is a bit at odds with the concept of QOps to save only the source code and properties.

2. Is it possible to merge the visual part in Qlik Sense?

The situation when several developers work on the same sheet, and everyone does own part of the work is possible with QOps. For its implementation it is necessary to adhere to a competent branch strategy to avoid merge conflicts. It is also worth paying attention to the correct resolution of merge conflicts in case occur to not disrupt interaction with the Qlik API.

3. Is it possible to work with Bitbucket and Jenkins?

Yes, it is possible. Source codes for a Qlik application can be hosted in a Bitbucket repository, and with the help of CI/CD web-hooks, a process can be built on top of Jenkins.

4. How does QOps differ from analogues and what are the advantages of using it?

QOps is primarily focused on the implementation of interaction with Qlik API and CI/CD implementation. Thus, QOps makes available in the console all the commands necessary to work with Qlik applications and ensures the integrity of applications when using additional code in variables or extensions.

The work of analogs is carried out only in the browser. It is also worth noting that they currently don’t support CI/CD across Git-based version control hosting systems and direct user interaction with the source code.

5. Is it possible to use QOps to protect code in Qlik applications?

Yes, it’s possible. QOps allows users to save and manage changes to source code.

6. Is it possible to migrate source code of a QlikView application to Qlik Sense using QOps?

No. But it is possible to manage the source code of both QlikView and Qlik Sense with QOps.

7. What is QOps architecture and what is required for installation?

QOps is installed using the installer. We provide step by step instructions for installing and using the product. You can find the documentation at qops.datalabsua.com

If you encounter difficulties during the installation process, you can contact QOps support for a prompt solution to the problem.

8. Is there a trial period for using QOps?

Email us [email protected] or fill out the form at qops.datalabsua.com

9. Model and conditions for purchasing QOps

The purchase model is a pack of 10 licenses. CI/CD implementation requires an additional license for each runner where QOps will be used. Additionally, a Qlik license is required. Detailed information can be found by filling out the form on QOps website.

Each client is special and has unique needs. If you have any questions, we will be happy to answer them:

[email protected]

+1 716 226 8951

+359 87 741 65 41

+44 2392 16 0664

+380 98 004 88 80

Each product is accompanied by instructions that clearly indicate the rules of use, warnings and risks that may arise in case of improper use. It’s fair to talk about some of misusing QOps risks.

QOps opens the way for developers to directly modify the Qlik source code.

The source codes for Qlik Sense applications are built using JSON objects. JSON (JavaScript Object Notation) is a text-based structured data interchange format based on JavaScript. This format can also be used in any programming language.

This structure of the application source code in Qlik Sense reduces the risk of damage, which is due to the developer’s ability to revise JSON files and make changes to their structure. However, risks still exist:

1. The occurrence of conflicts when changing the same lines of code in different branches of the repository. For example, the page size may not match the placement coordinates of the object. The result is a critical API error that prevents QOps from building the application.
2. Blocking the application as a result of merging changes. For example, the user makes changes that are not supported by Qlik’s internal API.

QlikView code is built on xml objects and xml data. Incorrect use of QOps (for example, violation of checksum integrity, violation of changes logic in features inside xml files) can lead to incorrect operation of the application or a complete stop of work.

This can be avoided by using the correct branching strategy (read more about the branching strategy here), as well as avoiding merge conflicts. The solution of such conflicts involves time planning and the presence of a specialist who coordinates all changes and directly manages this process.

It is also worth noting that the developer and user may not know for sure how Qlik will perceive a particular piece of code. However, a good approach to the development process, avoiding new objects or adding new objects in accordance with Qlik API will help to avoid errors.

To solve any problems and nuances that may arise in the process of using QOps, there is a 24/7 support service. A team of specialists quickly identifies errors and finds a solution.

More information here

In the modern world, data is the most valuable resource that opens new opportunities for development, new ideas and efficient operations. Its value creates high cybercriminals’ interest who steal or corrupt data for their own benefit. Their methods are becoming more sophisticated and inconspicuous, and the consequences become more serious, that incur large financial and reputational losses. The issue of data security is of key importance and is not bypassed by standard security programs.

Data security is a technology set for protecting data from intentional and accidental destruction, alteration and disclosure of data. Most data threats are external, however, don’t neglect the internal data protection system.

Data protection methods include:

• data encryption;
• data classification;
• access definition to data depending on functions and roles;
• data movements and changes monitoring and control;
• creating backups and restoring data.

Many companies outsource some of their work. It’s a common and convenient practice. But  it requires a serious approach to ensuring data security. Companies that care about their customers and data integrity will not give any partner free access to data. Sensitive data (customer information, banking information, confidential information, etc.) needs special protection. The design and implementation of any BI solution must take this into account.

When developing QOps, data security requirements were considered. Data protection and validation is ensured in QOps by:

• separation of source code and data (data is not saved);
• management of access rights depending on the source code storage location.

GitHub, GitLab, Bitbucket hosting systems provide the ability to set up a private or public repository. A private repository implies access to certain users (team members, administrator, etc.). In the situation with public repository everyone has access. Often in hosting systems, public repositories are provided through a subscription. A private repository with corresponding keys assumes a paid basis.

In closed systems, in order to increase data security, separate servers are also allocated for public and confidential data (customer data, phone numbers, email, etc.). Access to such data is severely limited. To protect personal data in Europe, there is a regulation (GDPR), that determines the rules and procedures for such data processing by companies and organizations. Any company that provides a service or sells a product to citizens of the European Union must comply with these requirements.

To comply with GDPR rules and ensure data protection when QOps works with secure Qlik servers, it is possible to connect through QOps Proxy. Thus, the certificate required to connect to the Qlik Server API is located on the same confidential server and does not go beyond it. This prevents the risks of third-party users connecting, taking possession of the certificate and password, as well as gaining access to data in the future. A special authentication method using AzureAD allows to connect the authorized user’s work machine to the QOps Proxy. In turn, the latter, using a certificate, connects to the server and sends only the data and source code to which the user has access.

The complete architecture of the interaction between QOps installed on the user’s local computer and QOps installed in the server environment is as follows. As you can see, this complies with data security requirements and provides flexibility in managing the source codes of Qlik applications using a git-repository, git-runners and a convenient development environment and source code editor VS Code.

More information you will find on QOps website

Developer’s workflow consists of many different tasks and projects. Tracking systems are used to structure them and organize convenient work. Small projects use Excel spreadsheets quite successfully for this purpose. However, project development requires more convenient solution implementation.

A tracking system is a software product, project management system that ensures the fulfillment of tasks, workflow planning, monitoring processes and results. This tool is useful for all team members: developers, project managers, team leads, top management, etc.

Now, the market offers large number of options for tracking systems: Jira, Mantis, Trello, Redmine, PivotalTracker, Bugzilla, Commind, etc. One of the most popular solutions is Jira.

Jira is a comprehensive solution from the Australian company Atlassian, which includes Jira WM (for working with business processes), Jira SM (for service disk building), Jira Software (for software development projects). These products are grouped into the Jira Family Product.

This tool is a paid system with an interactive dashboard for monitoring tasks movement and controlling their progress in a specific project. It is also a bug tracking and a convenient tool for project management, especially for agile teams. The main Jira goal is to simplify workflow management. The system has a wide functionality with the ability to supplement it with the help of plugins. There is a trial version of this tool for 7 days, which is available on the developer’s official website after user registration.

Jira benefits:

• Wide functionality (the ability to adapt the tool to projects of any complexity);
• Great potential for integration (ability to integrate with various services such as GitHub, Salesforce, Outlook, Slack, Gmail, Teams);
• Possibility to expand the functionality using plugins (Tempo, Script Runner, EazyBI, Big Picture, Structure);
• Ability to work with Scrum and Kanban methods.

It is worth noting the rather long tool setting process for a specific project, workflows and a complex interface. The reason for this is the wide functionality of the system. However, tool study and practice allow to fine-tune it and optimize it during use.

Jira features depending on teams, roles and purposes of use:

• Project Manager (PM): a great assistant for the project manager However, a complex and multifaceted tool requires detailed study to effectively use all its functions. Using tool capabilities, PM get a possibility to propose interesting initiatives for process optimization. Official Jira certification increases the competitiveness of a specialist;
• For project management teams: the ability to use a ready-made template that the tool offers or create own process with the ability to track all tasks, their way through all process stage. The administrator has the ability to configure access with different rights for different users. Also, the tool allows to create detailed reports if there is information about the project;
• For software development teams: the availability of planning tools allows members to manage budgets and requirements. Jira integrates with various CI/CD tools. This contributes to transparent management of the entire software development cycle. Gradual and safe introduction of new functionality is ensured by built-in features enabling and disabling features;
• For DevOps teams: Atlassian’s open, integrated toolset is based on Jira Software. The tool integrates with native and third-party tools, as well as code management solutions (Bitbucket, GitHub, GitLab), documentation and knowledge management tools (Confluence), monitoring and management tools, etc. This tool flexibility accelerates a quality software delivery;
• For Product Management Teams: Teams have the ability to create a roadmap for all projects. This allows to make long-term plans, track progress and share information;
• For bug tracking: tasks (bugs/problems that occur during software development) can be seen in the backlog and prioritized. Automatic issues prioritization is provided by Jira’s workflow management system;
• To manage tasks: create tasks for all team members, add detailed information, due dates and reminders. It is possible to divide large tasks into several small ones, create subtasks for certain team members. Other users can track tasks progress and receive a notification when it is completed. The current tasks status can be viewed using the dashboard.

The ability to integrate a tracking system and host a remote git repository is very convenient in managing Qlik projects. QOps can be used as a bridge between the source code in a repository and the final application. This kind of integration allows to automatically embed links to tasks in the tracking system into the source code of the application. As well as this feature allows management to track the progress of tickets and the corresponding source code migration between environments and/or versions.

More information at the link

CI/CD pipelines help to minimize potential risks in the process of integrating code changes into the repository, isolate the impact of possible errors and simplify fixing process. The main CI/CD goal is to speed up development process and value delivery to the end user. However, there are always ways and tools to make the process even more efficient. The matrix approach is one such option.

The basic pipeline structure involves the execution of tasks simultaneously at a certain stage. Tasks at the next stage can be completed if the previous ones are completed. This process continues at all stages. Different tasks in a pipeline take different times to complete. So, team members must wait to make their changes to the project. This significantly slows down the workflow and reduces productivity. Also, the presence of the same pipelines and creation scripts can lead to pipelines blocking. To optimize resources and increase productivity, it makes sense to create tasks clones and run them in parallel.

Previously, it was necessary to manually define tasks for their parallel execution. With the advent of parallel matrix jobs, it became possible to create jobs at runtime based on specified variables.

The matrix strategy uses variables when defining a job and allows to provide automatic creation of multiple job executions. This strategy can be used in the process of testing code in different languages and/or different operating systems. The matrix can be created with different job configurations specifying one or more variables. By defining variables (one or more), task will be applied for each variable combination.

It is also worth considering one feature. So, organizations often use mono-repositories for better project management. However, pipeline performance is degraded when there are many projects in the repository and one pipeline definition is used to run different automated processes for different components. Using parent and child pipelines makes pipelines more efficient. This approach minimizes the chance of merge conflicts and allows editing of pipeline parts if necessary.

On the one hand, pipelines optimization reduces the time developers spend on maintenance. On the other hand, it frees up time and space for new ideas, creativity and increased productivity. For example, using a matrix, it is possible to break down large pipelines into manageable parts for more efficient maintenance and maximization of tasks amount that run in parallel. The order in which jobs are created dictates the order of the variables in the matrix. The first variable is the first job in the run.

The complex Qlik application architecture consists of several layers (transformers, model, dashboard and extractors). And when using QOps, the matrix strategy is the best suited for managing applications of the same type within the same layer. These include applications in the layer of transformers and extractors.

GitHub, GitLab and Jenkins allow to build pipelines based on a matrix strategy that iterates over the available tasks according to cartesian multiplication. This was done to expand CI/CD capabilities, namely in testing on different platforms or, for example, with different frameworks versions.

The screenshot below contains an example pipeline source file for GitHub, where transformer overloading is implemented using a matrix strategy. The keyword for this is matrix in strategy block. The required list of applications is specified as a list on line 403. In this case, the substitution of the iterated application will be performed each time matrix.app is specified.

This is how used applications list in GitHub graphical interface looks like when executing the pipeline. At the same time, scaling the number of processed applications is easily performed. To do this, it is enough just to change their list and not make changes to the executable part of the code.

More information you will find at the link