BarTender Cloud incident

AM1 - Printing issues

Notice Resolved View vendor source →

BarTender Cloud experienced a notice incident on July 25, 2026, lasting 7m. The incident has been resolved; the full update timeline is below.

Started
Jul 25, 2026, 01:52 PM UTC
Resolved
Jul 25, 2026, 01:59 PM UTC
Duration
7m
Detected by Pingoru
Jul 25, 2026, 01:52 PM UTC

Update timeline

  1. resolved Jul 27, 2026, 02:20 PM UTC

    This incident has been resolved.

  2. postmortem Jul 27, 2026, 02:21 PM UTC

    ### **Root Cause Analysis \(RCA\)** **Incident:** AM1 – Printing Issues **Date:** July 25, 2026 **Duration:** 6:52 to 6:59 AM PDT **Root cause** An spike in network load and message queue volume caused the platform's messaging service to exhaust its allocated system resources. Under this exceptionally high volume of concurrent data requests, the service exceeded its internal processing limits. This triggered a system exception that caused the message broker to abruptly drop connection requests, preventing dependent application components from communicating successfully. **Containment Actions** Our engineering team updated the messaging service configurations to significantly increase its resource capacity and allow it to handle high-throughput traffic workloads. Since these configuration adjustments were applied and the service was restarted, system connectivity has fully stabilized, and all application components started to communicate normally without any further connection drops. **Preventive Actions** We are updating our standard infrastructure deployment templates to ensure all messaging components are pre-configured with high-capacity resource limits by default. Additionally, we are implementing enhanced monitoring and automated alerts for system resource utilization to proactively flag and address capacity demands before they impact platform performance. **Corrective Actions** A comprehensive review of resource configurations is being conducted across all core platform services to ensure they are optimized for high-throughput scaling. We are also refining application-side connection pooling and retry logic to gracefully manage unexpected traffic spikes, ensuring overall platform resilience during high-volume periods.