Incident Library
Applied filters SymptomThroughput degradationDomainKubernetesClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases5 cases

1 to 5 of 5

  1. Symptoms

    Between 06:00 and 07:00 UTC on 8 March 2023, Kubernetes nodes in several Datadog regions lost network connectivity at the same time, on AWS, Google Cloud and Azure. All services across multiple regions were affected, including the regions that host Datadog's CI/CD and automation tools. Datadog's regions are not connected to each other and changes are rolled out one region at a time, so a simultaneous failure on several cloud providers looked implausible at first.

    Trigger

    On 7 March 2023 Ubuntu published a systemd patch for a CVE (249.11-0ubuntu3.7). Ubuntu's default unattended upgrades installed it on the nodes between 06:00 and 07:00 UTC on 8 March, and installing it restarted systemd-networkd.

    Root cause
    Component
    Contributing factor
    Remediation
    • restarted thousands of disconnected instances on Google Cloud and Azure through the cloud APIs, keeping their local disks
    • rebuilt the data lost with terminated AWS instances' local disks through replication, reprocessing and restores from backup
    Lessons

    A change in a base operating system component can stay dormant for months until something restarts that component. Here the trigger was a security patch, and the change reached every region at once because automatic OS updates ran outside the progressive, region-by-region process used for every other change. Cloud providers react differently to an instance that loses its network. Google Cloud and Azure left the instances running, so a restart recovered them with their disks; AWS replaced them quickly, which brought stateless services back fast but destroyed the local-disk data the stateful services needed.

  2. 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.

    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
    Component
    Contributing factor
    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.

  3. Symptoms

    From April 11, 2022 at 13:17 UTC customers and Gitpod staff reported that Gitpod workspaces were intermittently becoming unresponsive. CPU usage of nodes and pods looked normal, with nothing maxed out, and at 13:58 UTC the team found that the workspaces were IO bound rather than CPU bound.

    Trigger

    The ws39 generation of workspace clusters, released to all regional clusters on April 8th at 20:08 UTC and to the XL clusters on April 9th at 17:45 UTC, split the 1TB disk into smaller RAID0 disks, changed CPU limiting and workspace networking, and moved to faster machine types.

    Root cause
    Component
    Contributing factor
    Detection

    Customers and Gitpod staff reported on April 11th at 13:17 UTC that workspaces were intermittently unresponsive, and the team opened an incident in Slack through its incident.io integration. On April 17th the team noticed increased CPU load on the workspace nodes and opened an internal incident.

    Remediation
    • Shifted workspace starts back to the ws38 clusters on April 11th
    • Built ws39a clusters with c2d machines and local SSDs and moved traffic to them
    • Requested a limit increase from Let's Encrypt
    • Routed EU XL traffic to the regional EU cluster and built ws-eu39bxl to replace the crashed ws-eu39xl
    • Cleaned up workspaces stuck in a stopping state so users could start them again
    • Released ws40 with 1TB boot disks to get more IO bandwidth
    • Removed the workspaces that consumed excessive CPU time for crypto-mining
    • Blocked the fraudulent users behind the crypto-mining from using Gitpod
    • Rolled back the ws-daemon change that broke CPU limiting and shipped the fix in the ws34 clusters
    • Blocked ACME HTTP requests to workspace ports so Let's Encrypt rate limits would not be hit again
    • Rolled out IO limiting with the ws41xl and ws41 clusters and moved traffic to them step by step
    Action items
    • Invest in test automation so that test results stop releases like this one
    • Vary the interval between traffic shifts to new clusters, with more time for larger releases
    • Add a risk assessment stage, to be automated, that governs changeset size and rollout speed of workspace cluster rollouts
    • Reduce the impact teams have on each other
    • Add review criteria that find backwards incompatible changes before pull requests are merged, and split such pull requests
    • Recommend rollback as the primary means of mitigation in the incident procedures, and look at automating it
    • Make the status page show the workspace service as down when it is, and update the playbooks
    • Keep incident communication in a single Slack channel and Google Meet
    • Put 10% of the engineering staff on the on-call rotation from May 9th and use that time on observability, alerting and stability
    Lessons

    Gitpod concluded that it should have committed to rolling back on April 11th instead of building and shipping fixes, which kept customers on degraded workspaces longer than necessary. A large release so soon after the previous one needed a risk assessment and slower traffic shifts, and backwards incompatible changes that block a rollback need to be found before pull requests are merged. Failure-free operations require experience with failure.

  4. Symptoms

    A production service at Airbnb showed a high error rate and could not be deployed. The deploy failed with a cryptic Kubernetes error about being unable to access invalid index 5.

    Trigger

    A change to the mutating admission controller, which had been rolled out within the previous month, had gone in seven days before the incident surfaced; when it had to delete two items from an array in a spec, it generated an invalid JSON patch that removed index 2 and then index 3.

    Root cause
    Component
    Contributing factor
    Detection

    The affected service reported a high error rate and its deploy failed; the slow degradation of other services over the previous seven days had gone unnoticed.

    Remediation
    • deleted the mutating admission controller from the affected cluster
    Action items
    • Create alerts from the existing metrics that would have shown the problem earlier
    Lessons

    Keep in mind that a mutating admission controller exists in the cluster; a recently added one is easy to forget during an incident. Search for the exact error message early instead of working on the visible symptoms. Page a teammate when progress stalls.

  5. Symptoms

    On 30 May 2019, in the run-up to the Kubernetes 1.15 code freeze, Prow test jobs in the k8s-prow-build cluster failed in surprising ways or were aborted partway through. Jobs were reported to GitHub as failed while Deck still showed them as running, because pods exited without uploading `finished.json`, the file most Prow tooling uses to tell a job's state.

    Trigger

    A spike in test load before the Kubernetes 1.15 code freeze pushed disk I/O on the build nodes far beyond the IOPS that GCP allows for 250 GB disks.

    Root cause
    Component
    Contributing factor
    Detection

    Several users reported jobs that GitHub showed as failed but Deck showed as still running, and the first report came on Slack at 13:26. Alerting for these failures did not exist or did not work.

    Remediation
    • Requested and received additional disk quota
    • Brought up 55 nodes with 500 GB disks in a new node pool
    • Migrated all nodes from the 250 GB disk pool to the 500 GB disk pool by draining old nodes, finishing at 23:55
    Action items
    • Create or fix monitoring so the oncall is paged when tide stops doing things
    • Set a process and guidelines for adding new members to the oncall rotation, with preparation and extra support
    Lessons

    Prow metrics were not recorded before the incident, which made it hard to understand, and alerting for these failures did not exist or did not work. After the cause was found and a fix devised, nothing happened for another two hours. The team counts it as luck that someone who recognised IOPS as the problem happened to be around to look.

Check your cluster for this

These 5 cases involve Node root disk and Admission webhook. 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.

By root cause5

Breaking change in an upgrade1 case

Organisation
  1. IL-0198 An automatic Ubuntu security update restarted systemd-networkd, which flushed the IP rules Cilium relied on and cut more than 60 percent of Datadog's Kubernetes nodes off the network across regions and cloud providers

Configuration change1 case

Component
Organisation
  1. 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

Faulty deployment1 case

Organisation
  1. IL-0591 Gitpod workspaces in all regions became IO bound and unresponsive for days after the ws39 workspace cluster release
    Gitpod2022

Software defect1 case

Organisation
  1. IL-0032 Mutating admission controller generated broken JSON patches, silently blocking deploys for a week until a production service ran down to two pods
    Airbnb2020

Capacity exhaustion1 case

Organisation
  1. IL-0401 Prow jobs on the k8s-prow-build GKE cluster failed and merges stalled as nodes hit IOPS throttling and kernel panics