Incident Library
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  • Root cause
  • Component
  • Symptom
  • Contributing factor
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  1. Symptoms

    From 16:18 UTC on 28 May 2026 the Lucidworks AI hosted LLMs in the us-southcarolina region were unavailable: queries to llama-3-8b-instruct, llama-3v2-3b-instruct and phi-4-multimodal-instruct returned 500 or 429 errors. Search, embedding models, the Lucidworks Platform UI and passthrough LLM calls kept working.

    Trigger

    A routine Kubernetes patch upgrade on a cluster in us-southcarolina cycled its node pools one after another in quick succession.

    Root cause
    Component
    Contributing factor
    Remediation
    • Deleted the degraded replacement head node that could not pull container images
    • Waited for the LLM image pulls to finish on the replacement nodes
    • Launched new nodes with the required LLM images and redirected Lucidworks AI traffic to them
    Action items
    • Upgrade clusters that host LLM workloads in sequence, with each node pool fully healthy before the next one is upgraded
    • Investigate image pre-loading, such as pre-baked disks or image streaming, for large ML model images
    • Open a support ticket with the cloud provider about the abnormal Docker pull times
    • Coordinate Kubernetes maintenance windows with LLM service owners so they do not clash with ongoing deployments
    • Build tooling to force a Ray cluster failover to the blue or green state instead of waiting for Ray to settle it
Check your cluster for this

This case involves Model inference server and Node pool. 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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