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When a Jira automation fails, start with its audit log: it shows whether the rule ran, which component failed, and the error reported. Then trace the failure through the trigger, rule actor, target project or space, smart values, and—if the rule makes a REST or web request—the request’s status, credentials, and permissions. Jira Cloud and Data Center differ, so confirm your deployment before applying an authentication or limits fix.
Start with the automation audit log
Atlassian recommends the audit log as the first diagnostic step. Find the relevant rule and execution, then check its status, the component that failed, and the message attached to that component. This narrows the investigation to the point where the rule stopped rather than treating every failure as an API problem. See Atlassian’s Jira automation troubleshooting guide.
- No execution entry when expected: inspect whether the trigger should have fired and whether trigger filters excluded the event.
- An execution entry exists: follow its component results and error message to the failed action or request.
Check the rule actor’s access
Automation actions run with an actor identity. Verify that the actor can see the issue and has the permissions needed for the action in the target project or space. Issue security can also hide an issue from an otherwise authorized actor. A rule may be able to start but fail when it reaches an action that requires access the actor does not have. Atlassian’s guidance on the actor-permission error is at this support page.
When a permission error is caused by rule ordering
The Cloud message “Actor does not have permission to view the event that triggered this execution” can also occur when another queued rule deletes the issue before the current rule processes it. In that case, changing permissions alone may not solve the problem. Review other rules that share the trigger and can delete the same issue. Atlassian describes this race condition and possible mitigations in its troubleshooting article.
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- Consider whether deletion can be replaced by a terminal status transition.
- Where rules overlap, consider consolidating or sequencing them so one does not remove the issue before another can process it.
- Add an early issue-exists condition if the rule should stop when the issue is gone.
Fix create, clone, and link action failures
For an action that creates, clones, or links work items, check the destination before editing the rule. Confirm that the target project or space key is correct and accessible, that the requested work-item type is available in its scheme, and that the actor has permission to create work items there. If the rule performs later edits, comments, or transitions, check the corresponding permissions as well.
After correcting the identified access or target configuration, retry the specific failed execution from the audit log to verify the same path. For the “Error retrieving work type fields” message and related create/clone troubleshooting, see Atlassian’s support article.
Diagnose missing or incorrect smart values
If an action receives blank or unexpected data, test the value rather than guessing what the rule passed along. Atlassian’s recommended approach is to use a manual trigger and a Log action, then inspect the emitted value in the audit log. This can reveal whether the problem is an empty source field, an incorrect smart-value expression, or a value that differs from the rule author’s expectation. See Atlassian’s smart-value troubleshooting guidance.
For a less specific field-related error, check whether the action omits a required value or refers to a custom field that has been deleted. Repair the field configuration or supply the required data, then run the rule again. Atlassian discusses the “Error retrieving work type fields” failure here.
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Troubleshoot REST and web request errors by deployment
For a failed REST or web request, use the audit entry and response details to check four things: HTTP status, authentication scheme, target endpoint or resource, and the access of the user whose credentials are used. The cited HTTP troubleshooting guidance is for Jira Data Center; its authentication examples should not be copied to Cloud without checking the relevant Cloud documentation. The endpoint and response body matter, so a status code alone does not identify every cause.
| Response or setup | What to check |
|---|---|
| 4xx response | Atlassian’s Data Center guidance classifies 4xx responses as client-side request errors. Inspect the request, endpoint, credentials, and resource access. |
| 401 response | Check that credentials are present and valid for the deployment and authentication scheme being used. |
| 403 response | The guidance describes 403 as an identified user lacking the required permission. Check access to the specific target resource. |
| 5xx response | The Data Center guidance classifies 5xx responses as server-side processing errors. Review the response details and whether the request can be retried safely. |
| Authentication mismatch | The cited Data Center examples distinguish Cloud API-token Basic authentication from Data Center personal-access-token Bearer authentication. Confirm deployment-specific requirements before changing the header or token type. |
See Atlassian’s Data Center automation troubleshooting guide for its status-code and authentication examples.
Separate Cloud usage caps from service throttling
Jira Cloud has both a monthly automation usage cap and per-execution service limits. They are different conditions, so do not assume that a throttled execution means the monthly allowance has been exhausted. Atlassian says a per-execution service-limit breach can mark a rule THROTTLED and may disable it. Use the execution’s audit details and current plan documentation to determine which limit applies; the cited material does not establish exact quotas. See Atlassian’s automation service limits documentation.
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