Autodesk experienced a minor incident on May 27, 2026 affecting Revit Cloud Worksharing / Cloud Models, lasting 55m. The incident has been resolved; the full update timeline is below.
Affected components
Update timeline
- investigating May 27, 2026, 04:46 AM UTC
We are investigating an issue where customers are unable to publish models in the Revit Cloud Worksharing / Cloud Models in the US region. We are actively looking into this and we will provide an update within 60 minutes or sooner if we have more information to share.
- resolved May 27, 2026, 05:42 AM UTC
The issue has been resolved. Thank you for your patience and understanding as we worked to resolve this issue.
- postmortem Jun 02, 2026, 09:23 PM UTC
**AUTODESK EVENT ANALYSIS** **Incident Number:** #COE-INC144048 **Incident Date:** May 26, 2026 **Summary** On May 26, 2026, between 9:20 PM PDT and 10:30 PM PDT, Autodesk customers in the US region were unable to publish Revit Cloud Models to Forma Data Management. **Impacted Services** * Revit Cloud Models in the US region **Root Cause** * A recently enabled configuration change caused the service to perform more internal processing than expected during certain publish-related requests. * This additional processing created a surge of internal requests that exceeded service capacity limits, causing the service to become unavailable. * Because the affected component supports the Revit publish workflow, customers in the US region were unable to publish Revit Cloud Models. * We restored the service by disabling the recently enabled configuration change and reverting the service to a previously stable version. **Autodesk Actions** Autodesk has completed a post-incident analysis of the event and identified actions to be taken. These include the following: * Modifying the service to avoid performing repetitive internal configuration checks during high-volume operations, reducing unnecessary processing and improving overall service stability. * Improving the service’s ability to handle periods of increased demand by optimizing resource allocation and capacity management. Thank you for your patience and understanding.