Incident Library
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Cases2 cases

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  1. IL-0005 A new telemetry service overloaded the Kubernetes API servers of large clusters and broke DNS-based service discovery for all OpenAI services
    OpenAI2024
    Symptoms

    Alerts fired at 3:13 PM PST on 11 December 2024, and from 3:16 PM every OpenAI service was significantly degraded or completely unavailable, including ChatGPT, the API and Sora. The status page reported API calls returning errors and difficulties logging in to platform.openai.com and ChatGPT. Customer impact peaked at 3:40 PM.

    Service outageHigh error rateControl plane unresponsiveDNS resolution failures
    Trigger

    At 2:23 PM PST a change introducing a new telemetry service, which collects detailed Kubernetes control plane metrics, was merged and the deployment pipeline started. Between 2:51 PM and 3:20 PM the change was applied to all clusters.

    Root cause
    Configuration change
    Component
    Kubernetes API serverClient-side DNS resolver and cacheTelemetry agent
    Contributing factor
    Unrepresentative stagingNo staged rolloutCache-masked failureMonitoring blind spotLimited debug access
    Detection

    OpenAI's detection tools worked: alerts fired at 3:13 PM PST, a few minutes before customer impact began at 3:16 PM, and the root cause was identified at 3:16 PM.

    Remediation
    • Scaled clusters down to reduce the total Kubernetes API load
    • Blocked network access to the Kubernetes admin APIs so no new expensive requests arrived
    • Scaled up the Kubernetes API servers
    • Removed the telemetry service once enough control was back
    • Moved traffic from impacted clusters to healthy ones
    • Intervened manually in clusters where simultaneous resource downloads saturated resource limits
    Action items
    • Put every infrastructure configuration change through a phased rollout with continuous monitoring of both the service workloads and the clusters, including the Kubernetes control plane
    • Run fault injection tests in which the data plane runs without the control plane for longer, and tests that roll out bad changes on purpose to check detection and rollback
    • Build break-glass mechanisms so engineers can reach the Kubernetes API servers in any circumstances
    • Decouple the Kubernetes data plane from the control plane so that service discovery for critical workloads does not depend on the control plane
    • Speed up recovery with better caching and dynamic rate limiters for resources needed at cluster startup, and regular drills that rapidly replace an entire cluster
    Lessons

    Several systems and processes failed at once and interacted in unexpected ways: tests did not catch the change's effect on the Kubernetes control plane, DNS caching put a delay between the change and the failures, and being locked out of the control plane made remediation very slow. Because service discovery used Kubernetes DNS, the control plane was carrying load for product traffic even though the data plane was meant to be independent of it.

    View case
  2. IL-0116 A CNI configuration change incompatible with a hardware variant that exists only in production cut network connectivity in an OpenAI GPU cluster and took text-davinci-003 fully down
    OpenAI2023
    Symptoms

    At 4:53 pm Pacific on 25 January 2023 one of OpenAI's GPU clusters had a major outage, and the text-davinci-003 model went fully down.

    Service outageThroughput degradation
    Trigger

    A configuration change to the CNI (Container Network Interface) plugins, which provide network connectivity to containers, was deployed to a GPU cluster that contained a hardware variant the staging environment did not have.

    Root cause
    Configuration change
    Component
    CNI plugin
    Contributing factor
    Unrepresentative stagingMonitoring blind spot
    Detection

    Engineers immediately identified the problem as network connectivity, but it took nearly an hour to identify CNI as the cause.

    Remediation
    • put a fix for the CNI configuration change in place, which restored 80% of traffic immediately
    • deployed models back onto GPUs over about three more hours until capacity was fully stable
    Action items
    • Make staging environments contain every type of hardware configuration so they better represent production
    • Monitor and alert on the health of the CNI system directly
    • Fix the network and storage bottlenecks that limit how quickly many replicas of a model can be deployed
    Lessons

    A change that had been deployed to other clusters over 24 hours and deemed safe still broke a cluster with different hardware, so staging needs every hardware configuration that production has.

    View case
Check your cluster for this

These 2 cases involve CNI plugin and Client-side DNS resolver and 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.

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By root cause1

Configuration change2 cases

Component
CNI plugin1Client-side DNS resolver and cache1Kubernetes API server1Telemetry agent1
Contributing factor
Monitoring blind spot2Unrepresentative staging2Cache-masked failure1Limited debug access1No staged rollout1
Organisation
OpenAI2
  1. IL-0005 A new telemetry service overloaded the Kubernetes API servers of large clusters and broke DNS-based service discovery for all OpenAI services
    OpenAI2024
  2. IL-0116 A CNI configuration change incompatible with a hardware variant that exists only in production cut network connectivity in an OpenAI GPU cluster and took text-davinci-003 fully down
    OpenAI2023