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Cases2 cases

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  1. IL-0124 Capacity changes queued while a circuit breaker was engaged ran all at once when it was released, taking multiple OpenAI inference engines out of service and raising API error rates
    OpenAI2026
    Symptoms

    Between about 4:26 PM and 4:56 PM PST on 4 March 2026, some OpenAI API requests to several models failed or took longer than usual, and some Codex traffic was affected too. The overall API success rate dropped temporarily.

    High error rateHigh latency
    Trigger

    A protective circuit breaker that had paused some scheduling operations was released, and the infrastructure actions queued during the pause were executed at the same time.

    Root cause
    Software defect
    Component
    Automated capacity manager
    Contributing factor
    Automation amplificationChange with a delayed effectNo safeguard on destructive changeMonitoring blind spot
    Remediation
    • manually reassigned infrastructure resources to the affected models
    • brought the removed inference engines back online and reassigned them until error rates returned to normal
    Action items
    • Improve safeguards in the automated capacity management systems so they detect and respond to state drift
    • Improve observability of circuit breakers and scheduling systems so their status and effects are easier to identify
    • Add safeguards so queued actions cannot run in large batches after long pauses
    • Improve monitoring and alerting around capacity reconciliation problems
    Lessons

    Pausing one automated system does not stop the systems that feed it. Changes queued during the pause reflect the state at the time they were queued, and releasing the queue all at once applies those stale decisions together. The fixes OpenAI names are detecting state drift, making circuit breaker status visible, and preventing large batches from executing after a long pause.

    View case
  2. 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
Check your cluster for this

These 2 cases involve Automated capacity manager 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
Automated capacity manager1Container memory limit1Model request routing1
Contributing factor
Automation amplification1Change with a delayed effect1Monitoring blind spot1No alert on limit1No safeguard on destructive change1No headroom1
Organisation
OpenAI2
  1. IL-0124 Capacity changes queued while a circuit breaker was engaged ran all at once when it was released, taking multiple OpenAI inference engines out of service and raising API error rates
    OpenAI2026
  2. 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