BarTender Cloud experienced a major incident on July 23, 2025 affecting EU1 - Integration Services, lasting 5h 18m. The incident has been resolved; the full update timeline is below.
Affected components
Update timeline
- investigating Jul 23, 2025, 09:54 PM UTC
We are currently investigating an issue causing increased latency on API requests in the EU1 region. Our team is working to identify the root cause and restore optimal performance as quickly as possible. We will provide updates as soon as more information is available.
- investigating Jul 23, 2025, 10:45 PM UTC
We are continuing to investigate this issue.
- investigating Jul 23, 2025, 11:54 PM UTC
We are continuing to investigate this issue.
- investigating Jul 24, 2025, 12:52 AM UTC
We are continuing to investigate this issue.
- identified Jul 24, 2025, 01:45 AM UTC
The issue has been identified and a fix is being implemented.
- monitoring Jul 24, 2025, 02:05 AM UTC
A fix has been implemented and we are monitoring the results.
- resolved Jul 24, 2025, 03:03 AM UTC
The issue affecting API performance in the EU1 region has been fully resolved. All systems are now operating normally. Thank you for your patience.
- postmortem Jul 30, 2025, 12:29 AM UTC
**Incident:** EU1 - Slowness in API Requests **Region:** EU1 **Time:** Wed, July 23 – 14:45 to 20:03 PDT **Summary** On July 23 and July 24, the EU1 region experienced slowness in API requests due to an edge-case scenario involving a combination of specific customer-side configuration and insufficient handling of that edge case within our platform. This led to suboptimal distribution of print jobs within the rendering cluster. After addressing the situation, system performance returned to normal. **What Happened** A particular combination of parameters in a customer’s configuration triggered a scenario where print jobs were not evenly distributed across the rendering cluster. Although the platform remained functional, the affected rendering logic did not optimally balance the load, resulting in slowness during periods of high demand. The behavior exposed an opportunity to improve how the platform handles unusual or edge-case job distribution patterns. **Resolution** The engineering team diagnosed the problem and implemented an adjustment that improved the handling of such edge-case scenarios. This update ensured more efficient job distribution across the rendering cluster. After the fix was applied, performance normalized and the issue did not reoccur. **Next Steps** To prevent similar issues in the future, we will: * Enhance exception and edge-case handling in job distribution logic * Improve monitoring and alerting for resource underutilization in the rendering cluster * Expand detection logic to proactively identify unusual job distribution patterns