Generating Insights from Tableau Server Performance Data

Summary

1

Fast and effective problem solving with a deep system health analytics

2

Focus on problem solving, not investigations, with actionable health insights

3

Supporting systemic health in an effective and proactive way using actionable insights

Background

With 5+ years of professional experience in Tableau, working in cooperation with global US companies in different projects, GreenM’s team was confronted with different performance and server health problems.

Investigation and finding the root causes took plenty of engineering time and effort, but it resulted in the growth of our expertise in this important area.

The relevant personal background led us to create our own software product TabTerrier. With TabTerrier, we want to solve the most pressing problems for organizations that:

  • received complaints about Tableau performance and have open questions – what causes the issues, and how to fix them;
  • want to monitor trends to predict and proactively takes action

Nowadays complex systems have loads of components and even more dependencies. Thousands of factors may lead to poor performance or even system failure. On the other hand, wise system management and configuration will provide the best results and save money. But how can one consistently keep track of system health, be sure of stability and not waste resources? Proper analytics and visualization you might say. You’re not wrong.

However, we are still talking about the loads of metrics and visualizations that should be continuously analyzed, compared and searched for dependencies and anomalies. That is very feasible, but will nevertheless consume a lot of time and energy. You just want to understand what has caused insufficient user experience, not to dig into tons of logs and graphics. Just imagine the long way through numerous metrics of hundreds of dashboards. 

Moreover, in the case of system failure, the cost of investigation time is too high. It is time to react right away and know your adversaries.

Challenges

To create own software product, our team faced the following tasks:

Find as many useful Tableau Server metrics as we can. Hardware, software, license, configuration, usage. All of them.

⦿ Identify dependencies and factors, which lead to the health system changing.

⦿ Find not only problems, but their root causes.

⦿ Find possible ways to resolve them.

⦿ Highlight the most important. Meanwhile, provide the full picture and more data to be analyzed if needed.

⦿ Identify trends and forecast system health issues based on historical data.

⦿ Make the solution pluggable, flexible and extendable, such that it is useful for all types of the setup.

To address the need for a powerful insight solution, GreenM team built a product that covers all of the aforementioned aspects. A scalable cloud-based application accumulates and processes all available Tableau Server information. 

We use data from Tableau logs, so the application does not put any load on the actual Tableau Server, which is critically important for analyzing servers with insufficient performance. Plugable design allows adjusting to different Tableau deployments and setup, meanwhile providing a way to add new features and support new Tableau versions smoothly. 

Accumulation of historical data helps to analyze health on a larger scale and identify long-term degradations.  We focus on the most valuable – insights. The application logic is based on best practices and correlation investigations, which helps to find actual and potential issues. 

Moreover, it looks for ways to fix and prevent them in the future. So the customer is able to save debugging and investigation time and act immediately. A powerful, yet simple, interface allows making decisions in fewer steps, which saves a lot of our customer’s resources. 

Now they can focus on what is really important – their data and business. Meanwhile, our product will help to keep the Tableau Server supervised, healthy and performing optimally. 

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Case studies

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