Enhancing Performance of ScriptRunner for Jira Data Center - Script Fields in Atlassian Jira

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Jira, part of Atlassian's suite of tools, is a cornerstone for teams managing work in diverse industries. From tracking software bugs to overseeing complex project workflows, Jira’s flexibility empowers teams to tailor processes to their unique needs. Central to its appeal is the ability to search, customize, and extend functionality through features like Jira Query Language (JQL) and ScriptRunner for Jira Data Center - Script Fields.

However, with great flexibility comes responsibility. Misconfigurations, especially in powerful tools like Script Fields, can inadvertently create performance challenges. This blog explores the nuances of indexing, JQL usage, and the impact of Script Fields on Jira DataCenter instances, offering strategies to ensure smooth and efficient operation.

Published 12.5.2025 | Updated 12.5.2025

Author Rafael Pinto Sperafico

Understanding Jira Indexing and JQL

Automatic vs. Manual Indexing

Jira relies on indexing to deliver fast and reliable searches:

  • Automatic Indexing: Occurs when an issue is created, updated, deleted, or transitioned mostly.
  • Manual Indexing: Triggered by administrators to rebuild index when needed.

Leveraging JQL

Jira Query Language (JQL) allows users to search issues with precision. For example:

project = "CUSTOM" ORDER BY created DESC

This retrieves all issues in the "CUSTOM" project, ordered by creation date.

Accessing Data Using JQL

Via Jira Issue Search (UI)

The web UI provides a visual way to execute JQL and view results:

<JIRA_BASE_URL>/browse/CUSTOM-1?jql=project%20%3D%20CUSTOM%20ORDER%20BY%20created%20DESC

Via Jira REST API

Integrate Jira with external systems using REST API queries:

<JIRA_BASE_URL>/rest/api/2/search?jql=project%20%3D%20CUSTOM%20ORDER%20BY%20created%20DESC

Via Jira Issues Macro in Confluence

Display Jira data in Confluence using macros:

<JIRA_BASE_URL>/sr/jira.issueviews:searchrequest-xml/temp/SearchRequest.xml?jqlQuery=project%20%3D%20CUSTOM%20ORDER%20BY%20created%20DESC

ScriptRunner for Jira DataCenter: Script Fields

Script Fields in ScriptRunner allow Groovy-based customizations to enhance issue data. For instance:

Random number

// enable/disable cache
// https://docs.adaptavist.com/sr4js/latest/features/script-fields
enableCache = {-> true}
 
// sleep for 10 seconds
sleep(10000)
 
// create instance of Random class
Random random = new Random();
 
// Generate random integers in range 0 to 999
int randomValue = random.nextInt(1000);
log.warn("Issue: ${issue.getKey()}, Random value: ${randomValue}")
 
// return value to be defined in Script Field
return String.valueOf(randomValue)

Benchmark Results

With Cache Enabled

  • The script executes once, updating the field after 10 seconds.

With Cache Disabled

  • The script executes multiple times, significantly delaying responses

Scenario Cache Execution Comment
Jira Issue Search (UI)

 Enabled 1x Issue gets rendered and after 10 seconds the script field
Random number  gets updated with a new random value.
Disabled 7x Since there is a sleep of 10s, Jira UI will await for over 60
seconds before failing on rendering the result of the JQL
query.
Jira REST API Enabled 1x JSON response is given after 10 seconds
Disabled
Jira Issue Macro Enabled 1x XML response is given after 10 seconds
Disabled 3x XML response is given after 30 seconds

Additional Insight: Execution Metrics in ScriptRunner

ScriptRunner provides execution statistics that are invaluable for debugging and performance assessment. As noted in its documentation on Script Fields, the execution count is recorded regardless of the cache setting. This highlights:

  • Even with caching, the field’s script executes once per relevant rendering or search operation.
  • When caching is disabled, these metrics can reveal a dramatic increase in execution frequency, correlating directly to system delays.

This underscores the importance of monitoring execution counts and understanding how cache settings affect the behaviour of Script Fields, especially in large-scale Jira instances.

The Performance Challenge

Search for Script Field Value(s)

The Random number field demonstrates the issue:

  • Cached: Executes once.
  • Uncached: Executes multiple times, causing delays.

Performance Implications

Requests to retrieve Script Field values scale with issue volume:

  • 1 issue = 10 seconds
  • 100 issues = 1000 seconds. This creates significant bottlenecks for large datasets.

Strategies to Prevent Performance Bottlenecks

Optimize Data Retrieval

  • UI: Use the List view and display only required fields.
  • REST API: Specify only necessary fields in API requests.
  • Confluence: Narrow displayed columns in Jira Issues Macro.

Use Pre-Computed Fields with Cron Jobs

Instead of live computation:

  • Create a Custom Field for pre-computed data - not a Script Field
    • Random number - cron job , custom field to receive the random value generated
    • Random number - last updated , custom field to receive a timestamp from when custom field was last updated
Schedule a Cron Job to populate values periodically:

import com.atlassian.jira.component.ComponentAccessor
import com.atlassian.jira.issue.Issue
import com.atlassian.jira.user.ApplicationUser
 
ApplicationUser applicationUser = ComponentAccessor.getJiraAuthenticationContext().getLoggedInUser()
 
final String jql = 'project = PROJ ORDER BY created DESC'
 
long issueCount = Issues.count(jql)
log.info("${issueCount} issues were found with jql=\"${jql}\"")
 
List<Issue> issues = Issues.search(jql).toList()
issues.each { issue ->
    // create instance of Random class
    Random random = new Random();
 
    // Generate random integers in range 0 to 999
    int randomValue = random.nextInt(1000);
 
    log.info("Random value ${randomValue} generated")
 
    Issues
        .getByKey(issue.getKey())
        .update {
            log.info("Update issue \"${issue.getKey()}\"")
            setCustomFieldValue('Random number - cron job', String.valueOf(randomValue))
            setCustomFieldValue('Random number - last updated', new Date().format("yyyy-MM-dd'T'HH:mm:ssZ", TimeZone.getTimeZone("UTC")))
    }
}

Conclusion

Customizing Jira with ScriptRunner's Script Fields can deliver powerful features, but improper configuration leads to performance degradation. By optimizing searches, limiting unnecessary field executions, and precomputing field values with cron jobs, you can harness the full potential of Jira DataCenter while maintaining performance.

This blog post provides a practical guide for administrators and developers to ensure Jira remains performant while utilising the extensive capabilities of ScriptRunner for Jira DataCenter.

Ready to Optimize Your Jira Experience?

Are you facing performance challenges with ScriptRunner in your Jira DataCenter environment? Or perhaps you're planning a migration to Atlassian Jira Cloud?

Our team of experts can help you:

  • Review your current ScriptRunner setup to identify performance bottlenecks
  • Recommend optimizations for your Script Fields and custom scripts
  • Create a seamless migration strategy from Jira DataCenter to Cloud
  • Adapt your existing scripts to work efficiently in ScriptRunner for Jira Cloud
  • Ensure your customizations continue to deliver value without compromising performance

Don't let performance issues or migration concerns hold you back. Whether you're looking to improve your current DataCenter implementation or make the move to Cloud, our consultants bring years of experience in Atlassian ecosystems and ScriptRunner customizations.


Get in Touch

Contact us today for a no-obligation consultation. We'll help you harness the full potential of ScriptRunner while maintaining optimal performance — wherever you choose to run Jira.

Contact Our Atlassian Experts →



Acknowledging the Author and Team Behind the Insights

IMG_7964 (1)

 

This blog post, Enhancing Performance of ScriptRunner for Jira Data Center - Script Fields in Atlassian Jira, has been authored by Rafael Pinto Sperafico, an experienced professional specializing in Atlassian tools. With a robust background in project management, agile methodologies, and a focus on performance optimization in Jira environments, Rafael brings invaluable expertise to this topic. You can explore more about his professional journey on LinkedIn.

Furthermore, this content reflects the collective insights of Ambientia's Atlassian Team, a group renowned for its technical acumen, long-term client relationships, and exceptional team spirit. Ambientia has been at the forefront of leveraging Atlassian products to drive meaningful business transformations.

To dive deeper into their approach and success stories, visit Ambientia’s feature on their Atlassian Team. Here, you’ll learn how they blend technical expertise with collaboration to provide outstanding solutions. Even if you don’t speak Finnish, the page showcases their commitment to excellence and innovation in the Atlassian ecosystem.

 

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