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Start with the rule’s audit log entry: it shows whether Jira Automation triggered and, if it did, which component failed. Then check the rule actor’s access, the target project or space, field values, and—if the rule makes a web request—the HTTP status and authentication method. Troubleshooting differs between Jira Cloud and Data Center, so confirm your deployment before applying a fix.
First confirm whether the rule ran
Open the rule’s audit log and find the expected execution. Atlassian recommends the audit log as the first debugging step in its automation troubleshooting guidance.
- No execution entry: Check whether the trigger should have fired, then inspect trigger conditions and filters. The failure may be before the rule begins its actions.
- An execution entry exists: Review its status, failed component, and message. Use those details to narrow the problem to a condition, action, or request rather than changing unrelated rule settings.
After making a targeted correction, retry the specific failed execution from the audit log when that option is available. This helps establish whether the fix addresses the same failure path.
Check the rule actor and the target’s access
Automation actions run with an actor identity. That actor needs the permissions required for the action and access to the relevant issue or work item. Atlassian’s Cloud guidance on the rule actor explains the actor’s role; verify its access in the target project or space, including issue security where it applies.
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A missing permission or visibility restriction can prevent an action from viewing or changing an issue. For create, clone, or link failures, check the destination as well as the source:
- Confirm the target project or space key is correct and accessible to the actor.
- Check that the requested work-item type is available in the target’s scheme.
- Confirm the actor has permission to create work items there.
- If later actions edit fields, comment, or transition the item, check the corresponding permissions too.
Atlassian’s guidance for create, clone, and link failures covers these target-side checks. Once corrected, retry the failed execution rather than relying only on a new test run.
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When a permission error may be a deletion race
In Jira Cloud, the message “Actor does not have permission to view the event that triggered this execution” may indicate a timing problem rather than a static permission gap. One queued rule can delete an issue before another rule for the same trigger runs. The second rule then cannot view the triggering issue.
Review other rules that share the trigger and can delete the same issue. Atlassian describes this scenario in its Cloud troubleshooting article. Depending on the workflow, possible changes include consolidating or sequencing the rules, adding an early condition that checks whether the issue still exists, or replacing deletion with a terminal workflow transition. Choose a change that preserves the intended process; do not treat this particular message as proof that permissions are definitely correct or definitely wrong.
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Diagnose missing fields and incorrect smart values
If an action runs with blank or unexpected data, test the smart value itself before rewriting the whole rule. Atlassian recommends using a manual trigger and a Log action, then checking the emitted value in the audit log. See its Log action instructions and smart values reference.
- Run the rule with a manual trigger using a representative issue or work item.
- Add a Log action that outputs the smart value you expect to use.
- Inspect the logged output in the audit log and compare it with the value the next action needs.
- Correct the field reference, context, or rule configuration, then test again.
For a field-related message such as “Error retrieving work type fields,” check whether a required value is missing or a custom field referenced by the rule has been deleted. Repair the rule’s field configuration if it points to an unavailable field; Atlassian’s field-error guidance discusses these causes.
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For REST and web requests, diagnose the deployment and response
Do not troubleshoot a failed request by status code alone. First establish whether the Jira instance is Cloud or Data Center, then inspect the endpoint, response body, credentials, and permissions for the account making the request. The cited REST API troubleshooting guidance is for Jira Data Center, not a universal recipe for every deployment.
| Response or symptom | What to check |
|---|---|
| 4xx response | In the cited Data Center guidance, 4xx indicates a client-side request error. Check the endpoint, request format, credentials, and whether the account can access the target resource. |
| 403 response | The cited guidance describes 403 as an identified user lacking the required permission. Verify that user’s access to the specific project, issue, or resource. |
| 5xx response | The cited guidance associates 5xx with server-side processing errors. Review the response details and server-side context; changing the rule actor’s project permission alone may not resolve a server error. |
| Authentication failure | Confirm the authentication scheme appropriate to the deployment and endpoint. The cited page distinguishes Cloud API-token Basic authentication from Data Center personal-access-token Bearer authentication; do not copy one deployment’s example into another without checking its documentation. |
These status-code descriptions are a starting point, not a diagnosis of a particular endpoint. The exact response body and resource still matter. For Cloud API requests, use the relevant Jira Cloud REST authentication documentation rather than assuming Data Center instructions apply.
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Separate Jira Cloud usage limits from service throttling
Jira Cloud automation has distinct kinds of limits. A monthly usage cap and a per-execution service limit are not the same failure. Atlassian documents these separately in its automation service-limits guidance and automation usage-limits guidance.
If an execution shows THROTTLED, investigate the per-execution service limit; Atlassian notes that a service-limit breach may also disable a rule. If the concern is the monthly allowance, check the current plan documentation and usage information instead. The exact applicable limits depend on the current Cloud plan and documented service conditions, so do not infer a quota from a throttling status alone.
Keep Cloud and Data Center fixes in their context
Cloud and Data Center share useful troubleshooting habits—read the execution evidence, confirm the identity used, and verify access to the target—but the details are not interchangeable. The Cloud actor, smart-value, and automation-limit guidance cited above applies to Cloud. The HTTP troubleshooting page cited above is Data Center-specific, and its authentication examples should not be treated as universal. Confirm the deployment, endpoint, and current product documentation before changing credentials or permissions.
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