Incident Library
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Cases2 cases

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  1. Symptoms

    At 11:36 PM PDT on 9 June, alerts fired across multiple OpenAI services as a large number of cloud-hosted GPU nodes lost network connectivity, and the engineering team was escalated to immediately. Losing those nodes cut the capacity available to serve ChatGPT and the API.

    Trigger

    A routine daily scheduled update of the host operating system on the cloud-hosted GPU servers restarted systemd-networkd on the affected nodes.

    Root cause
    Component
    Contributing factor
    Detection

    Alerts fired immediately across multiple services when the infrastructure began losing network connectivity at 11:36 PM PDT, and the engineering team was escalated to at once.

    Remediation
    • re-imaged the affected GPU virtual machines
    • deployed recovery automation to restart the remaining impacted nodes
    • halted the background update mechanisms on the GPU VMs
    Action items
    • Disable automatic daily updates on GPU VMs so updates run in a controlled, scheduled way
    • Update system configurations to prevent conflicts between systemd-networkd and the networking service
    • Audit VM configurations across the fleet to find and reduce similar risks
    • Improve recovery speed for critical infrastructure such as GPU VMs and clusters
    • Run regular disaster recovery drills
    Lessons

    An unattended operating system update that restarts systemd-networkd can wipe the routes another networking agent manages, and it hits every node that takes the update at about the same time. Without break-glass tooling to restore connectivity, nodes that lost their network had to be re-imaged, which stretched recovery over many hours.

  2. Symptoms

    On August 16, 2024 from 11:38 AM to 1:16 PM PT, the OpenAI primary API was unreliable: ChatGPT conversations succeeded less often, and logging in and creating accounts were affected. The status page called it elevated error rates for ChatGPT and the Platform API. The incident came in two waves, of 44 and 15 minutes.

    Trigger

    A scheduled maintenance combined with an upgrade to the ingress of OpenAI's user-facing clusters.

    Root cause
    Component
    Contributing factor
    Action items
    • Mitigate the networking control plane regression and validate that control plane restarts do not interfere with the clusters' data plane
    • Change service software to start faster and remove the first-start query, relieving the persistence layer
    • Deploy configuration changes that optimise the networking control plane's effect on the clusters' ability to handle traffic
    • Remove the expensive database query from critical startup paths
    • Add monitoring and alerting for networking control plane issues
    • Introduce staged rollouts with longer soak time for infrastructure changes
    • Audit systems for other slow queries that may affect service start time
    Lessons

    A brief connectivity loss turned into a long outage because recovery itself was expensive: the services that restarted overwhelmed one backend persistence store with a heavy first-start query. Keeping costly queries off startup paths shortens recovery, and staged rollouts with longer soak time limit how many systems an infrastructure regression reaches before it is caught.

Check your cluster for this

These 2 cases involve Application database and Ingress controller. 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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