Incident Library
Applied filters SymptomIntermittent timeoutsOrganisationMicrosoft AzureClear 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

Cases2 cases

1 to 2 of 2

  1. Symptoms

    From 10:03 UTC on 29 September 2026, requests to Azure OpenAI Service, Foundry Agent Service, Foundry Models and Azure AI services in Sweden Central failed intermittently, took longer, or returned HTTP 500 and 503 errors. At 10:17 UTC service monitoring raised an alert on elevated failure rates for Azure OpenAI Service requests in the region.

    Trigger

    At about 09:38 UTC a planned deployment of an internal service in Sweden Central cleared that service's caches during the region's peak traffic hours.

    Root cause
    Component
    Contributing factor
    Detection

    Service monitoring detected elevated failure rates for Azure OpenAI Service requests in the region at 10:17 UTC and alerted the engineering teams; engineers were engaged at 10:28 UTC.

    Remediation
    • reconfigured the backend service's automated health check so it no longer depended on remote connectivity, which stopped the restart loop
    Action items
    • Reconfigure the backend service's automated health check so it no longer depends on connectivity to its database layer
    • Add monitoring and alerting on the load and latency of the caching layer used by the backend service
    • Update troubleshooting and procedural guidance for connection exhaustion scenarios for on-call engineers
    • Add throttling and rate limiting to protect the backend service from sudden traffic increases (estimated October 2026)
    • Increase the resource capacity of the caching layer used by the backend service across regions (estimated October 2026)
    • Improve diagnostic metrics and automated detection to identify such issues more quickly (estimated October 2026)
    • Partition the caching layer used by the backend service to increase its throughput (estimated December 2026)
    Lessons

    A health check that depends on a remote dependency turns a dependency problem into a restart loop: instances that cannot reach the database are killed, the remaining ones take more load and retries, and adding instances or resources does not help until the check itself is changed. Clearing a cache during peak traffic can multiply load on the backend behind it, especially when cache-read defects let lookups bypass the cache. Connection exhaustion was hard to see because the existing network and diagnostic metrics did not show it.

  2. Symptoms

    In newly created AKS clusters using Azure CNI in Central India, kubectl exec and kubectl logs could time out, and pod-to-pod or pod-to-node traffic could time out. The cluster diagnostics page showed tunnel exec issues. Clusters using kubenet were not affected.

    Trigger

    VMs in Central India started being assigned MAC addresses in a much higher range than before (06 prefix rather than the usual 00).

    Root cause
    Component
    Contributing factor
    –
    Remediation
    • told owners of affected scale-set clusters to run a node image upgrade, or any Kubernetes upgrade such as a patch version, to get the Azure CNI that does not use a bridge
    • told owners of availability-set clusters to scale out and delete the VMs with a high-range MAC address in bridge mode
    • advised recreating affected clusters that were brand new
    Action items
    • Roll out a hotfix that makes transparent mode the default in all regions
    Lessons

    A change in how the platform assigns MAC addresses can wake a long-dormant bug in the network plugin. Knowing which CNI mode the nodes run (bridge or transparent) and keeping node images current decides whether such a bug reaches you.

Check your cluster for this

These 2 cases involve Azure CNI and In-memory cache. 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.

By root cause2