Incident Library
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Cases2 cases

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  1. IL-0130 Deployments of large models from Vertex Model Garden failed with "Model server never became ready" in most regions for 13 days after a storage provisioning configuration change
    Google Cloud2024
    Symptoms

    From 22 October 2024 at 14:08 US/Pacific, customers deploying large models, those that need more than 100 GB of disk, through Vertex AI Online Prediction (Vertex Model Garden deployments) had their deployments fail with the error "Model server never became ready".

    Deploys failing
    Trigger

    A recent change introduced an internal storage provisioning configuration error.

    Root cause
    Configuration change
    Component
    –
    Contributing factor
    –
    Detection

    The incident began on 22 October 2024 at 14:08 but was first posted on the status page on 4 November 2024 at 13:17 US/Pacific, about 13 days later. The first post said large Vertex Model Garden deployments (greater than 100GB) on a GKE Autopilot cluster might fail.

    Remediation
    • rolled back the configuration change that introduced the storage provisioning error
    Lessons

    A configuration error that affects only one class of deployments, here models needing more than 100 GB of disk, can stay in place across most regions for almost two weeks. The visible symptom, a model server that never becomes ready, does not point at storage provisioning, and the fix was to roll the configuration back. The report lists no follow-up actions.

    View case
  2. IL-0108 An Alcide admission controller applied to the production cluster during a workshop made create and update requests on Deployments time out
    DFDS2020
    Symptoms

    At 14:41 CET on 4 November 2020 users reported timeouts when deploying to Hellman, the production Kubernetes cluster. The timeouts were confirmed at 15:04.

    Deploys failingControl plane lag
    Trigger

    During an Alcide workshop that began at 13:00 CET, an Alcide admission controller was applied to the production cluster at 13:13 in the belief that it would not disrupt anything.

    Root cause
    Configuration change
    Component
    Admission webhookKubernetes API server
    Contributing factor
    No configuration testsUnverified assumptionMonitoring blind spot
    Detection

    Users reported timeouts when deploying to the Hellman cluster at 14:41 CET; the timeouts were verified at 15:04.

    Remediation
    • toggled the Alcide admission controller to verify that it caused the timeouts
    • permanently deleted the Alcide admission controller
    Action items
    • Monitor Kubernetes deployments for timeouts
    • Monitor 5xx status codes from the Kubernetes API server
    Lessons

    New components are applied in sandbox clusters, not in production. The team needs enough Alcide knowledge to maintain the component until it is fully deprecated.

    View case
Check your cluster for this

These 2 cases involve Admission webhook and Kubernetes API server. 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.

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By root cause1

Configuration change2 cases

Component
Admission webhook1Kubernetes API server1
Contributing factor
Unverified assumption1Monitoring blind spot1No configuration tests1
Organisation
DFDS1Google Cloud1
  1. IL-0130 Deployments of large models from Vertex Model Garden failed with "Model server never became ready" in most regions for 13 days after a storage provisioning configuration change
    Google Cloud2024
  2. IL-0108 An Alcide admission controller applied to the production cluster during a workshop made create and update requests on Deployments time out
    DFDS2020