Incident Library
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Cases2 cases

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  1. IL-0123 A response buffer allocated anew in a loop made OpenAI's routing layer nodes hit their memory limits and fail readiness checks on a morning with more completions than any day before, causing 502 and 503 errors across all models
    OpenAI2023
    Symptoms

    Between 5:42 AM and 7:16 AM PT on 8 November 2023 a large share of requests to OpenAI failed with 502 or 503 errors. Every model and API endpoint saw significant failures.

    High error rateService outageProbe failures
    Trigger

    A morning with dramatically more completions than any previous day pushed the routing layer nodes, which already had a chronic memory problem, past their memory limits.

    Root cause
    Software defect
    Component
    Model request routingContainer memory limit
    Contributing factor
    No alert on limitNo headroom
    Remediation
    • limited incoming traffic
    • redeployed the routing service en masse
    • ramped traffic back up slowly
    Action items
    • Pre-allocate the responseBuffer and reuse it instead of allocating a new one in a loop (3X improvement in memory and CPU usage)
    • Adjust the configured memory limits to an appropriate level so the service has significant headroom
    • Add rate limit controls to shed traffic more gracefully
    • Increase the service's capacity
    • Change alerting to catch the underlying memory behaviour before it escalates into service issues
    • Configure autoscaling for the service, which was not possible before because added capacity could hurt an upstream service
    View case
  2. IL-0132 A faulty resource cleanup process marked Vertex AI prediction endpoints as deleted worldwide, undeploying customers' models and failing predictions for 4 hours 20 minutes
    Google Cloud2022
    Symptoms

    From 10:10 US/Pacific on 2 June 2022, Vertex AI Online Prediction returned errors for 30% up to 100% of requests per region, depending on how each customer used the service.

    High error rateResources deletedService outage
    Trigger

    A faulty resource cleanup process marked Vertex Prediction Endpoints as deleted, globally.

    Root cause
    Software defect
    Component
    Model request routing
    Contributing factor
    Automation amplificationExcessive blast radius
    Detection

    The first public status update was posted at 13:58 US/Pacific and gave the start as 10:20 US/Pacific; the later mini incident report gives 10:10.

    Remediation
    • restored the Vertex Prediction Endpoints that had been marked as deleted
    View case
Check your cluster for this

These 2 cases involve Model request routing and Container memory limit. 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

Software defect2 cases

Component
Model request routing2Container memory limit1
Contributing factor
Automation amplification1Excessive blast radius1No alert on limit1No headroom1
Organisation
Google Cloud1OpenAI1
  1. IL-0123 A response buffer allocated anew in a loop made OpenAI's routing layer nodes hit their memory limits and fail readiness checks on a morning with more completions than any day before, causing 502 and 503 errors across all models
    OpenAI2023
  2. IL-0132 A faulty resource cleanup process marked Vertex AI prediction endpoints as deleted worldwide, undeploying customers' models and failing predictions for 4 hours 20 minutes
    Google Cloud2022