As part of ongoing efforts to deprecate the legacy SSO integration, a production change related to the older SSO configuration led to service instability for clients still using the legacy authentication mechanism. This resulted in temporary access issues for those clients.

• Affected clients will be advised to migrate from the legacy SSO to the new SSO integration to ensure continued stability and support.

• The legacy SSO will be progressively deprecated in a controlled manner to avoid future disruptions.

• Additional validation and monitoring will be implemented during the deprecation process to minimize client impact.

During the recent release, a configuration issue in the new build resulted in an unintended app service plan change during the swap process.

As a mitigation measure, all pipelines were enhanced to perform app service swaps automatically, reducing the risk of manual configuration errors.

The monolith service in the India region runs on Azure VM Scale Sets (VMSS) with native autoscaling rules already configured to scale based on system metrics. In addition to native autoscaling, an automation layer was implemented to scale capacity proactively based on incoming request volume, providing faster responsiveness during traffic spikes.

As part of a recent infrastructure upgrade, the service was migrated from Azure Cloud Services to VMSS, and the legacy cloud service was subsequently decommissioned. While the native VMSS autoscale continued to function as expected, the request-based scaling automation was still referencing the legacy Cloud Service resource.

During the traffic surge, the request-based automation failed to execute scale-out actions, resulting in delayed capacity expansion until manual intervention was applied. This configuration mismatch between the updated infrastructure and the supplemental automation caused the temporary performance degradation.

The VMSS capacity was manually increased to quickly stabilize the service. The request-based scaling automation was updated to accurately target the VMSS infrastructure. Additionally, scaling behavior was validated under simulated load to ensure that both native autoscaling and request-based scaling work as expected.

The issue has been fully resolved, and additional safeguards are now in place to prevent recurrence. Both native autoscaling and request-based scaling mechanisms are actively monitored to ensure timely capacity adjustments during traffic spikes.

A sudden increase in traffic in the India region caused temporary resource saturation. Autoscaling added capacity, and performance returned to normal. No issues are currently observed in monitoring.

Review traffic patterns and autoscaling settings to ensure faster response