Incident Library
Applied filters Root causeConfiguration changeComponentModel inference serverSymptomLoad imbalanceClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases1 case

1 to 1 of 1

  1. IL-0235 Azure OpenAI GPT-5.2 returned HTTP 400 in seven regions after a configuration update the model engine did not support
    Microsoft Azure2026
    Symptoms

    From 23:20 UTC on 9 March 2026 Azure OpenAI Service customers received HTTP 400 and HTTP 429 error responses for the GPT-5.2 model in Australia East, Central US, East US 2, Korea Central, Norway East, Sweden Central and UK South. All other GPT models kept working.

    High error rateLoad imbalance
    Trigger

    An update to the Azure OpenAI GPT-5.2 model enabled feature settings meant to improve service efficiency and resilience. The model engine version running in production did not yet support those settings. The update was rolled out to the whole fleet in stages under Safe Deployment Practices.

    Root cause
    Configuration change
    Component
    Model inference serverModel request routing
    Contributing factor
    Unrepresentative stagingMonitoring blind spotOverlapping failures
    Detection

    Service monitoring detected the issue at 00:19 UTC on 10 March, about an hour after impact began. Detection was late because monitoring was set up for client-side HTTP 400 errors and not for service-side anomalies.

    Remediation
    • Rolled back the GPT-5.2 configuration in all affected regions instead of waiting for a hotfix
    • Completed the routing updates and restored full regional capacity information so traffic was spread normally again
    Action items
    • Train engineers on the operating procedures, including which scenarios can be rolled back quickly
    • Store a cached known-good version of the traffic routing details for when the capacity service cannot provide current data
    • Set thresholds for service-side HTTP 400 errors in monitoring
    • Improve anomaly detection on HTTP 4xx errors to alert on unusual error rates below the usual thresholds
    • Add signals to the deployment systems so problematic rollouts stop automatically
    • Make sure early rollout stages have enough backend model instances to catch such problems
    View case
Check your cluster for this

This case involves Model inference server and Model request routing. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

Open kubegap

By root cause1

Configuration change1 case

Component
Model inference serverModel request routing
Contributing factor
Monitoring blind spotOverlapping failuresUnrepresentative staging
Organisation
Microsoft Azure
  1. IL-0235 Azure OpenAI GPT-5.2 returned HTTP 400 in seven regions after a configuration update the model engine did not support
    Microsoft Azure2026