As the use of the Tableau server grows, so does the need to maintain its continuous availability. Enter, the concept of Tableau High Availability — a strategy commonly employed to ensure consistent availability.

To limit the possibility of unanticipated downtime, these solutions necessitate that the fundamental component of the tableau server is redundant. To achieve this goal, deployment in a distributed environment is required to operate superfluous key processes on separate servers.

A multi-node Tableau high availability server installation can help to maximize the tableau server’s efficiency and availability. The procedures you take while building a multi-node tableau server setup are meant to create redundancy, reducing potential downtime. This blog discusses Tableau High Availability, its capabilities, and how to build up a highly available (HA) installation scenario on Tableau Server.

What is Tableau?

Tableau High Availability - Tableau
Image Source

Tableau is a well-known Business Intelligence (BI) and Data Visualization application that is used by businesses and organizations all over the world for reporting and analyzing massive amounts of data. Tableau, created by Pat Hanrahan, Christian Chabot, and Chris Stolte, aids in the transformation of raw data into a format that is easily comprehended by professionals at all levels of a business. Tableau has helped major industries reduce analysis time and make their companies more data-driven since its launch in 2003.

Tableau’s innovation was exclusively centered on Visual Analysis, and it has a multitude of capabilities and gives you far more control over the appearance of your display. Tableau’s intuitive visualizations assist you in communicating your data graphically and in a visually appealing and intelligible style.

Key Features of Tableau

Here are some of the primary elements that have contributed to Tableau’s enormous success:

  • Multiple Dashboards: Tableau includes a simple interface that allows even non-technical users to perform quick data analysis and produce visuals. Users can use its simple drag-and-drop capability to construct high-level graphs and dashboards.
  • Extensive Data Sources: Tableau includes over 200 connectors and drivers that enable users to securely connect to a variety of third-party applications and external data sources, including Relational Databases, Big Data, Cloud, Spreadsheets, and more.
  • Easy Collaborations: Tableau allows users working on separate projects to collaborate with one another. Users can also share the dashboard on the Cloud, making it available to anyone from any location.
  • Big-game Visuals: Tableau includes an extensive range of advanced Data Visualization tools. Users can quickly visualize data using Charts, Tables, Graphs, Plots, Maps, and so on.
  • Tableau Public: Tableau has a sizable user, developer, and analyst community. Being a part of this community allows you to constantly learn, upgrade your skill, make significant connections, and mentor newcomers.

Introduction to Tableau High Availability

A Tableau high availability installation is a sort of distributed installation that is designed to withstand failure in crucial server components while maintaining full server functioning.

Installing a single node is the most basic approach to operating Tableau Server. You have a fully functional Tableau Server with all Tableau Services Manager (TSM) and Tableau Server activities running on that single node, however, this may not be the best approach to using Tableau high availability Server.

You can choose how to deploy Tableau high availability on your organization’s needs and resources. You have the following installation options:

1) Single-node Installation

This installation is appropriate for testing, performing trials, and environments that can tolerate periodic downtime and system availability owing to a lack of redundancy. On a single system, all server processes are executed.

In the case of a failure with one of the server processes, there is less redundancy and fewer safeguards. You must also ensure that the computer on which Tableau Server is installed has sufficient capacity to manage the operations and demands of users and data.

2) Distributed Installation

This form of installation, also known as a multi-node installation, necessitates the use of many computers in order to install and operate server operations on those spread nodes. Spreading the server operations across numerous nodes can improve Tableau Server’s stability and efficiency by adding redundancy and computational power. A distributed installation can also allow automated repository failover if properly configured.

3) Installation with High Availability (HA)

Tableau High Availability installation is a form of multi-node installation that includes at least three nodes and multiple instances of critical processes (the Repository, File Store/Data Engine (Hyper), Coordination Service, and Client File Service) running on various computers. There is built-in redundancy of those important activities in a Tableau high availability implementation, including multiple File Stores and automated Repository failover. The goal is to reduce system downtime by eliminating single points of failure and, if practicable, enabling the detection of problems with failover.

Downtime in Tableau High Availability is still conceivable if an initial node fails or a node running Application Server (VizPortal) recovers from a failure. Depending on how your system is designed and used, dashboards and views may load more slowly than planned, and timeouts are conceivable.

What Makes Hevo’s ETL Process Best-In-Class

Providing a high-quality ETL solution can be a difficult task if you have a large volume of data. Hevo’s Automated, No-code Platform empowers you with everything you need to have for a smooth data replication experience.

Check out what makes Hevo amazing:

  • Fully Managed: Hevo requires no management and maintenance as it is a fully automated platform.
  • Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
  • Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making. 
  • Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
  • Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

How to Deploy Tableau for High Availability Environments?

In this architecture, one node serves as the gateway, routing requests to the other two worker servers. All server processes are run by both worker servers. Though all of the tableau server’s operations should be redundant, the gateway, data engine processes, and repository process must be made redundant. Both workers had instances of the repository and data engine processes prior to tableau server version 8, but only one of the two workers was actively accepting queries.

Even though only one data engine process is considered primary, both actively receive queries. Previously, the second worker had standby copies of the processes and was immediately elevated to status if the primary worker failed. Check that each additional node matches the distributed criteria before installing Tableau Server on them. For more information, see Distributed Requirements.

A three-node system can assist you to lessen the vulnerability of the primary:

Tableau High Availability- Three-node system
Image Source

The tableau high availability setup process is similar to the basic cluster configuration described in this post, on when and how to deploy a server on several physical machines.

The following are the steps for deploying a Tableau high availability configuration:

  1. Install the tableau server on the primary machine (note the IP address of this machine).
  2. Stop the tableau server service on the same machine.
  3. Install the tableau server worker on all other workstations, including the cluster (the primary server IP is needed for this step).
  4. Launch the Configuration tool.
  5. Click the Add button after selecting the servers tab.
  6. Enter the first worker’s IP address in the Add Tableau Server dialogue box.
  7. Indicate the number of each process type.
  8. Ensure that the extracted storage, as well as the repository storage, are both included in the host’s settings. Select OK.
  9. On the primary system, start the tableau server service.
  10. Examine the server status and see that the extract engine and repository instances on the new worker appear to be down. This will be fixed once the parent server has sent all data for these processes to the new worker machine.
  11. After the worker has extracted the engine and repository, the processes are switched from service down to service stand by, and the tableau server service on the primary machine is restarted.
  12. Launch the configuration utility on the primary server
  13. Clear the extract stored in the configuration utility on this host, as well as the primary server’s repository storage checkboxes. Remove all other processes in order to configure this system just as a gateway. Select OK.
  14. Click the add button on the servers tab.
  15. Enter the IP address of the second worker and the quantity of each type of process in the add tableau server dialogue box. Check the extracted storage as well as the repository storage in this host’s settings. Select OK.
  16. You can configure e-mail alerts regarding the cluster status as an optional step in the configuration utility’s e-mail alerts tab.
  17. Restart the tableau server service after closing the configuration utility.

When the service is restored, go to the tableau server maintenance page and verify the condition of the cluster. Only the gateway service should be listed with the IP address of the principal server.

The two worker server IP addresses should also be shown alongside the remaining tableau server processes. One worker will have an active data engine and repository, while the other will have backups of these activities.

Tableau High Availability - Server Status
Image Source

This confirms the Tableau high availability deployment.


We recognize how critical it is for people to be able to access and comprehend their data quickly. We also recognize that events, whether related to hardware, software, networks, or even human error, will always pose a danger to the availability of business intelligence systems.

That is why Tableau’s high availability is an out-of-the-box solution that is simple to configure and set up. In the event of a component failure, Tableau Server processes will automatically restart to keep your system operational. A well-configured multi-node deployment also employs multiple processes to ensure server uptime.

To meet the growing storage and computing needs of data, you would need to invest some of your engineering bandwidth in integrating data from all sources, cleaning and transforming it, and finally loading it to a Cloud Data Warehouse for further Business Analytics. All of these issues can be efficiently addressed by a Cloud-Based ETL tool like Hevo Data, A No-code Data Pipeline, that has awesome 100+ pre-built Integrations that you can choose from.

Visit our Website to Explore Hevo

Hevo can help you integrate your data from numerous sources and load them into destinations like Amazon Redshift, Google BigQuery, Snowflake, and Firebolt to analyze real-time data. It will make your life easier and Data Migration hassle-free.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. Hevo offers plans & pricing for different use cases and business needs, check them out!

Share your experience of learning how to deploy Tableau High Availability in the comments section below. We would love to hear from you!

Davor DSouza
Research Analyst, Hevo Data

Davor is a data analyst at heart with a passion for data, software architecture, and writing technical content. He has experience writing more than 100 articles on data integration and infrastructure.

No-Code Data Pipeline for Your Data Warehouse