Cases4 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.

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2. IL-0068 Anonymous access to the Kubernetes API server used to plant a ClusterRoleBinding backdoor and a cryptominer DaemonSet

   Aqua Security2023

   Symptoms

   Aqua's research team Nautilus recorded the attack on one of its Kubernetes honeypots. What appeared in the cluster was a DaemonSet running the image kuberntesio/kube-controller:1.0.1 from Docker Hub on every node, using the nodes' CPU to mine Monero.

   Unauthorised access or a foreign workloadResources deleted

   Trigger

   An API server misconfigured to accept unauthenticated requests from anonymous users with privileges.

   Root cause

   Configuration change

   Component

   Kubernetes API serverRBAC and service accountsContainer registry and its credentials

   Contributing factor

   Monitoring blind spot

   Detection

   Aqua recorded the attacker's API requests on its honeypot; planted AWS access keys raised a beacon when the attacker tried to use them.

   Lessons

   Fixing an exposed API server is not enough once an attacker has been in: a ClusterRoleBinding to an attacker-created ServiceAccount keeps working after anonymous access is closed. Attackers name these objects and images after real Kubernetes components so they blend into the API audit logs and pass for legitimate deployments. Aqua recommends scanning clusters for vulnerabilities, exposed secrets and misconfigurations with a tool such as Trivy.

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3. IL-0108 An Alcide admission controller applied to the production cluster during a workshop made create and update requests on Deployments time out

   DFDS2020

   Symptoms

   At 14:41 CET on 4 November 2020 users reported timeouts when deploying to Hellman, the production Kubernetes cluster. The timeouts were confirmed at 15:04.

   Deploys failingControl plane lag

   Trigger

   During an Alcide workshop that began at 13:00 CET, an Alcide admission controller was applied to the production cluster at 13:13 in the belief that it would not disrupt anything.

   Root cause

   Configuration change

   Component

   Admission webhookKubernetes API server

   Contributing factor

   No configuration testsUnverified assumptionMonitoring blind spot

   Detection

   Users reported timeouts when deploying to the Hellman cluster at 14:41 CET; the timeouts were verified at 15:04.

   Remediation

   • toggled the Alcide admission controller to verify that it caused the timeouts
   • permanently deleted the Alcide admission controller

   Action items

   • Monitor Kubernetes deployments for timeouts
   • Monitor 5xx status codes from the Kubernetes API server

   Lessons

   New components are applied in sandbox clusters, not in production. The team needs enough Alcide knowledge to maintain the component until it is fully deprecated.

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4. IL-0008 An unresponsive OPA validating webhook crash-looped the API server during a GKE master upgrade, and node auto-repair then recreated every node

   Jetstack2019

   Symptoms

   Jetstack was upgrading the master of a development cluster that many teams use to test their apps during the working day, a regional Google Kubernetes Engine (GKE) cluster in europe-west1. The upgrade ran through Jetstack's GKE Terraform pipeline and did not finish before the 20-minute Terraform timeout, while the GKE console still showed the cluster as upgrading.

   Upgrade stallControl plane unresponsiveNode recreation loopService outage

   Trigger

   A planned master upgrade of the shared development cluster. The same upgrade had been done on another pre-production environment earlier that day, and no API downtime was expected.

   Root cause

   Configuration change

   Component

   Admission webhookGKE control planeKubernetes API serverkubelet

   Contributing factor

   Excessive blast radiusNo health probesMonitoring blind spotAutomation amplification

   Detection

   The first sign was the master upgrade missing the 20-minute Terraform timeout; re-running the pipeline returned the kube-apiserver unhealthy error. The cause was identified with the help of Google Support.

   Remediation

   • Deleted the OPA ValidatingAdmissionWebhook resource during a window of API server access

   Action items

   • Limit the OPA webhook to the namespaces where the policy applies and development teams have access
   • Enable the webhook only for Ingress and Service resources, the only resources the policy validates
   • Add a liveness probe so OPA is restarted when it stops responding, and update the OPA documentation
   • Follow the open upstream Kubernetes issue about this behaviour

   Lessons

   With alerting on API server response times, the team might have seen CREATE and UPDATE requests slow down across the board as soon as the OPA-backed webhook was first deployed. Every workload needs probes: OPA looked so simple to deploy that the team skipped the Helm chart, which adds a livenessProbe for the admission controller containers among other adjustments to the tutorial configuration. Others had hit the same problem, and an upstream issue to improve it was still open.

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