Why is my SLA still running after issue closure? Troubleshooting common SLA stop condition errors

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You’ve just closed a customer issue. The resolution was logged, the agent moved it to “Done,” and the customer confirmed everything looks good. Yet when you glance at the SLA panel… it’s still counting down. Days later, it’s still active, or worse, it’s breached.

Sound familiar?

This is one of the most frustrating Jira Service Management problems admins face: SLAs that keep running even after the issue is technically complete. Not only does it confuse your support agents, it undermines the accuracy of your SLA reports and makes leadership question metrics they should trust.

Many teams assume that once a ticket hits a "closed" or "done" status, the SLA stops automatically. But Jira’s SLA stop conditions rely on very specific logic, and if your workflow or status configuration doesn’t align perfectly, your SLAs will keep ticking long after they should.

In this article, we’ll break down:

• Why SLA stop conditions can silently fail
• The most common misconfigurations (and how to fix them)
• How to validate your SLA behavior without guessing
• And how tools like SLA Time and Report make this process visual, fast, and foolproof

Let’s troubleshoot this together, because accurate SLAs start with clarity and control.

Understanding how SLA stop conditions work

At the core of every SLA in Jira Service Management is a set of rules: when the clock starts, when it pauses, and when it stops. While it may seem simple - start when a ticket is created and stop when it’s closed, the reality is more nuanced. And if even one piece is off, your SLAs can run indefinitely.

What is an SLA stop condition?

A stop condition defines the moment when an SLA clock should cease running. Typically, this is tied to a workflow status like “Done,” “Closed,” or “Resolved.” But here’s the catch: Jira doesn’t automatically know what “done” means in your context. If your SLA stop condition doesn’t explicitly include the exact status or field change that matches your workflow, it won’t trigger.

🧠 Example: You may assume “statusCategory = Done” is enough, but if your ticket transitions to a status outside that category, the SLA won’t stop.

Common config mistakes

Let’s look at where teams often go wrong:

• Using status names that look complete but aren’t configured as stop triggers.
  For instance, “Awaiting Confirmation” or “Archived” might sound final, but aren’t included in your SLA stop condition.
  
  
• Relying on status categories instead of explicit statuses.
  Jira’s “Done” category is helpful, but if your SLA is configured to stop on “status = Closed” and your issue moves to “Resolved,” the SLA keeps running.
  
  
• Skipping transitions that trigger the stop.
  If agents move tickets manually using a “jump to” transition or reopen issues without cycling through the full flow, stop conditions may never be hit.

🔍 How to check if it’s working

Open any issue with an active SLA. In the SLA panel:

• Do you see a “Completed” time?
• If not, is the status one of those defined in the SLA’s stop condition?
• Use issue history to verify what transitions occurred.

Knowing how Jira interprets transitions is key to ensuring your SLA logic performs as expected.

Top reasons your SLA is still running (and how to fix them)

If your SLA timer keeps going after an issue is "closed," you're not alone. Let’s explore the most common causes, complete with quick-fix guidance to help you correct them without trial and error.

1️⃣ Stop condition doesn’t match the final status

The problem:
Your SLA is configured to stop on status = Closed, but your workflow uses a different status, like Resolved, Done, or even a custom status like Ticket Archived.

The fix:
Update the SLA configuration to include all final statuses that should stop the clock:

status IN (Closed, Resolved, Done, "Ticket Archived")

You can also use statusCategory = Done, but only if all your final statuses belong to that category.

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2️⃣ The issue skipped the stop transition

The problem:
Your workflow includes a specific “Close Issue” transition that triggers the stop, but agents bypassed it using another route (e.g., moved directly from “In Progress” to “Archived”).

The fix:
Ensure that all final transitions include statuses defined in the SLA stop condition. Train agents to use the correct paths or add transition conditions to enforce them.

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3️⃣ Stop condition relies on a custom field change that didn't trigger

The problem:
Your SLA is set to stop when a field (like Resolution) is set, but in your custom workflow, that field isn’t populated automatically.

The fix:

• Make sure your closing transitions update the Resolution field properly.
• Modify SLA logic to use status = Closed instead of relying on resolution IS NOT EMPTY unless you’ve tested both thoroughly.

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4️⃣ The issue was reopened

The problem:
The SLA stopped correctly, but then the issue was reopened and never re-closed. Now the SLA has resumed and keeps ticking.

The fix:
Review the SLA’s goal settings: Does it restart after reopening? Consider using JQL logic like:

(status = Closed AND updated >= -1d)

...or use automation to manage status transitions consistently.

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5️⃣ Stop condition is correct, but the SLA never recalculated

The problem:
You fixed the config, but old issues still show a running SLA due to stale calculations.

The fix:
Use Jira's “Recalculate SLA” feature on the issue, or bulk-recalculate via automation.

💡 Pro tip:  Identifying the exact reason why an SLA didn’t stop can be incredibly time-consuming, especially when you're combing through workflows, custom statuses, and issue histories manually. That’s where SLA Time and Report for Jira becomes your trusted helper.

With this app, you can instantly visualize each SLA cycle, see exactly when the timer started, paused, or should have stopped, and spot misfires in seconds. Even better, it offers a built-in “Reset SLA” feature, allowing you to quickly correct SLA behavior on affected issues without touching the workflow or writing complex automation rules.

Whether you're fixing one ticket or cleaning up a whole queue, it's the fastest way to restore SLA accuracy and regain control over your support metrics.

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🛠 Can you fix it manually in Jira?

Yes, you can, but it's not always easy or scalable.

To manually fix an SLA that just won't stop:

• You'll need to inspect the SLA configuration and ensure the stop condition includes the correct statuses.
• Then, check the issue's history to see if those statuses were actually reached.
• If needed, you can trigger a recalculation - either through the issue menu or by creating a temporary automation rule.

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🧠 Here's the catch, though:

This process takes time, a keen eye for detail, and a lot of manual digging, especially if multiple issues are affected or if workflows vary across your teams.

💡 A smarter alternative: Let the app do the work

SLA Time and Report for Jira takes the guesswork out of SLA troubleshooting:

• Instantly visualize the full SLA lifecycle for any issue.
• Quickly identify exactly where the stop condition failed.
• Use the built-in "Reset SLA" feature to correct timers in just a few clicks—no workflow edits, no automation hacks required.

Whether you're fixing one SLA or auditing dozens, it's the fastest, most transparent way to regain control and restore trust in your metrics.

Next, we'll show you how it works in a real example.

Real-world example: Before and After fixing SLA behavior

Let’s walk through a simplified example that illustrates just how much easier it is to resolve SLA misfires using SLA Time and Report, compared to digging through raw Jira configurations.

❌ Before: SLA keeps running after issue closure

Imagine an issue goes through the following statuses:

• To Do → In Progress → Resolved
  

The team considers “Resolved” as complete, but the SLA stop condition is only configured for status = Closed. The issue never enters that status, so the SLA keeps running, even though functionally, the ticket is done.

This leads to:

• False SLA breaches
• Confused agents wondering why their tickets look late
• Misleading metrics in SLA reports

Manually fixing this requires:

• Opening each issue
• Reviewing its history
• Matching transitions to the SLA stop logic
• Recalculating SLAs, if your plan even allows it

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✅ After: Visual debugging and quick fix with SLA Time and Report

With SLA Time and Report, you just:

1. Open the issue in the app
2. Instantly see the SLA timeline, including exact start and stop points
3. Notice the SLA hasn’t stopped after “Resolved”
4. Use the Reset SLA button to stop it or apply logic-based corrections

Even better? You can filter and batch fix similar issues across your queue, using visual indicators and SLA filters like:

• SLA Status = In Progress
• Final Status = Resolved

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Don’t let SLA confusion derail your support metrics

When SLAs don’t stop as expected, the impact goes beyond a single issue. Your agents get frustrated, your reports become unreliable, and customer trust takes a hit. And while Jira does offer tools to manage SLAs, fixing these kinds of misfires manually can be slow, error-prone, and hard to scale.

That’s why tools like SLA Time and Report are more than just helpful—they’re essential.

With this app, you can:

• Visualize exactly where SLA logic failed
• Pinpoint and reset timers on specific issues
• Detect SLA misfires across your queue
• And ultimately, regain control over your performance metrics

🔎 If your SLAs are misfiring or your team is just tired of guessing why a ticket breached, try SLA Time and Report today. It’s your shortcut to clarity, confidence, and SLA sanity.

🙋‍♀️ Over to you

Have you run into this problem in your Jira project? What’s the strangest SLA behavior you’ve had to debug?

Share your story in the comments, we’d love to hear how you solved it (or how we can help).

[Maria Rusnakova]

That's a comprehensive article :)

[Alina Kurinna _SaaSJet_]

@Maria Rusnakova thank you so much!