Jira Service Desk 3.16.x Long Term Support release performance report

Before we started the test, we needed to determine what size and shape of dataset, represents a typical large Jira Service Desk instance. To achieve that, we used our Analytics data to form a picture of our customers' environments and what difficulties they face when scaling Jira Service Desk in a large organization. Learn more

The following table presents the rounded values of the 99th percentile of each data dimension. We used these values to generate a sample dataset with random test data.

Baseline data set

We chose a mix of actions that would represent a sample of the most common user actions. An action in this context is a complete user operation, like opening an issue in the browser window. The following table details the actions that we included in the script, for our testing persona, indicating how many times each action is repeated during a single test run.

The performance tests were all run on a set of AWS EC2 instances. For each test, the entire environment was reset and rebuilt, and then each test started with some idle cycles to warm up instance caches. Below, you can check the details of the environments used for Jira Service Desk Server and Data Center, as well as the specifications of the EC2 instances.

To run the tests, we used 20 scripted browsers and measured the time taken to perform the actions. Each browser was scripted to perform a random action from a predefined list of actions, and immediately move on to the next action. Please note that it resulted in each browser performing substantially more tasks than would be possible by a real user, and you should not equate the number of browsers to represent the number of real-world concurrent users.

Each test was run for 40 minutes, after which statistics were collected.

Here are the details of our test environment: