Is Your Jira Dying from Custom Field Bloat?
A diagnostic guide for Jira Data Center administrators
The Numbers That Should Worry You
Atlassian ran performance tests that every Jira admin should know about:
| Custom Fields Count | JQL Search Time |
|---|---|
| Baseline | < 1 second |
| 1,400 fields | ~3 seconds |
| 2,800 fields | ~9 seconds |
Doubling the custom field count tripled the search time. Your users won’t complain about “custom field bloat.” They’ll say “Jira is slow.” They’ll blame the server, the network, the database. But the real culprit might be sitting in your Custom Fields admin page, quietly multiplying.
The Symptoms You’re Probably Ignoring
Before we run any queries, let’s check if you recognize these patterns:
- JQL queries take 2+ seconds to return results
- Autocomplete in the search bar feels sluggish
- Saved filters timeout on large projects
- Creating new issues has noticeable lag
- Opening issue detail view takes longer than it used to
- Bulk operations crawl or timeout
- The Custom Fields admin page takes forever to load
- Screen configuration feels unresponsive
- Workflow transitions have delays
If you’re nodding along to three or more of these, custom field bloat is likely a contributing factor.
The 30-Second Health Check
Let’s start with the simplest possible diagnostic. One query. One number.
If you have access to your Jira database (read-only is fine), run this:
Write down that number. Now, here’s the uncomfortable truth: there’s no official “safe” threshold. But here’s what we know from the field:
What About Jira’s Built-in Tools?
If you’re on Jira Data Center, you have access to the Instance Optimizer:
Administration → System → Instance optimizer → Custom fields optimization
This tool scans your fields and identifies those with “global context” — fields available to all projects when they’re only used by a few. It’s genuinely useful for one specific optimization.
For a complete picture, you need to go deeper. That’s where SQL queries come in.
Running Queries Without SSH Anxiety
Here’s where most custom field audit guides lose people. They assume you’re comfortable SSH-ing into your server, connecting to PostgreSQL, and running queries in a terminal.
For many Jira administrators — especially those who came from the project management side rather than sysadmin — that’s a significant barrier.
There’s an easier way.
Tools like Home Directory, Database & Log File Browser for Jira let you run database queries directly from Jira’s admin interface. No SSH. No terminal. No memorizing PostgreSQL connection strings.
The Hidden Costs You’re Not Tracking
Custom field bloat isn’t just about search speed. Consider these ripple effects:
Every custom field — used or not — takes space in Jira’s Lucene index. More fields = larger index = slower reindexing = longer maintenance windows.
Field metadata is cached in memory. Hundreds of unused fields consume RAM that could serve actual user requests.
Ever tried to find the right “Status” field when there are four with similar names? Bloat creates cognitive overhead for your entire admin team.
New Jira administrators inherit your mess. Every unnecessary field is documentation they need to understand and cleanup they’ll eventually need to do.
📋 Your Action Items Before Part 2
- Run the count query — know your starting number
- Check Instance Optimizer — see what Jira’s built-in tool finds
- Note your symptoms — which performance issues are you seeing?
This baseline will make the diagnostic queries in Part 2 much more actionable.
The Bottom Line
Custom field bloat is a slow poison. It doesn’t crash your instance dramatically — it just makes everything slightly worse, month after month, until “Jira is slow” becomes accepted reality.
The good news: it’s fixable. Not overnight, and not without some research. But with the right queries and a systematic approach, you can reclaim that performance.
Your users deserve a Jira that responds in milliseconds, not seconds.
This article is Part 1 of the “Custom Field Health Check” series for Jira Data Center administrators.
Inspired by the custom field management work of Rachel Wright (Strategy for Jira) and Rodney Nissen (The Jira Guy), whose detailed guides and SQL queries laid the foundation for systematic custom field auditing.