We are increasingly experiencing that Qlik users reach out to us because their Qlik-based BI solution is not performing satisfactorily. The issues vary and may include:
 

• Poor user experience, with the solution running slowly and not meeting expectations.

• High maintenance costs, as even small changes require many consulting hours.

• Slow app reload times, impacting daily usage and decision-making.

• Repeated error messages from the server.

• Loss of connection to the server or data sources.
   

These problems create frustration for both the IT department and end-users. End-users are not concerned with the technical reasons behind the issues – they just want a quick solution. Often, there is no single simple cause of performance problems, and the solution requires a thorough review of both the setup and structure.
 

How did you end up in this situation?

Performance issues rarely arise at the start but develop over time as the solution grows. Many companies start with a small-scale solution, but over time, the system can no longer handle increasing demands.
 

BI solutions are dynamic and are continuously adapted to meet business needs. It is therefore essential to ensure that the solution can grow with the organization's requirements from the outset. Often, BI systems lack an overarching strategic plan and instead evolve from a bottom-up approach. This can lead to an inefficient solution that does not support the organization’s long-term goals.
 

Two types of problems: Infrastructure and structure

• Infrastructure: Server setup, RAM, and CPU resources are essential factors affecting system performance. However, increasing hardware capacity alone is not always enough.

• Structure: Just as important as the infrastructure is how the Qlik solution is developed and structured. Capana follows "Best Practice" for data modeling and Qlik structure to allow the solution to grow over time and avoid performance issues.
   

Best Practice for optimizing Qlik solutions

Capana has over 20 years of experience in developing and optimizing Qlik solutions, and we have developed a set of best practice principles to make the Qlik solution more efficient and cost-effective for the client.
 

Deployment Framework (DFW)

A structured deployment framework ensures the solution is easy to maintain and expand. At Capana, we have developed our own DFW based on Qlik’s recommendations, which we have tailored based on our extensive experience.
 

Checklist for optimal Qlik performance

Here are the most common causes of poor performance in Qlik solutions:

• Dedicated hardware: Virtual hosts can cause unstable performance. Dedicated hardware ensures optimal performance for your Qlik servers.

• CPU vs. RAM: Insufficient RAM resources are often the cause of poor performance, but sometimes it can also be due to insufficient CPU resources. Make sure your system optimizes both RAM and CPU usage.

• SAN over NAS: Use SAN for storing Qlik files instead of NAS. SAN provides better stability and performance.

• Scheduled server restarts: Regular service restarts ensure that old cache is cleared and that the server can perform optimally.

• QMC settings optimization: The settings in the Qlik Management Console (QMC) can impact server performance. Adjust session and document timeouts and RAM allocation to optimize performance.

• Virtual setup (VMware): Incorrect VMware configuration can cause reduced performance. Follow Qlik’s best practices for virtualization.

• Approved hardware: Use approved hardware from Qlik’s recommendations, such as Intel Xeon processors with turbo boost.

• Log analysis: Troubleshooting can be done by analyzing log files from QlikView Server (QVS). Session logs, event logs, performance logs, and audit logs can provide valuable insights into any performance issues.