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

Cases9 cases

7 to 9 of 9

  1. Symptoms

    On Friday, January 18, Moonlight's API began returning occasional errors that looked like connection problems with its Redis database. The API checks Redis on every authenticated request to validate the session. At the same time the Kubernetes monitoring reported some nodes and pods as unresponsive.

    Trigger

    The Kubernetes scheduler put several CPU-heavy pods on the same node, including all three replicas of the website and the server-side rendering pods.

    Root cause
    Component
    Contributing factor
    Detection

    API errors that looked like Redis connectivity problems, and Kubernetes monitoring that showed nodes and pods as unresponsive. Google Cloud Support later found the link between sustained 100% CPU and kernel panics.

    Remediation
    • added anti-affinity rules to all major deployments so their pods spread across nodes
    Action items
    • Keep working with Google Cloud support to find and fix the cause of the node kernel panics
    Lessons

    Three replicas give no fault tolerance if the scheduler places them all on one node; anti-affinity rules make the spread explicit. A node failure that comes from the workload itself moves with the workload when the scheduler reschedules it.

  2. Symptoms

    Shortly after a search reindex job was started, problems with the Kubernetes cluster hit Universe's reporting and search APIs and the Kubernetes cluster UI itself. The status page opened an investigation into reports of search and reporting being unavailable at 14:37 EDT on 2017-07-21.

    Trigger

    A change to the search index definition, which removed some fields from full-text indexing, was shipped, and a reindex job was started as a Kubernetes Job to apply it.

    Root cause
    Component
    Contributing factor
    Detection

    The team saw problems with the Kubernetes cluster shortly after starting the job, and the status page cites reports of search and reporting being unavailable.

    Remediation
    • removed the reindex Job from the scheduler
    • let the nodes auto-heal back to healthy
    Lessons

    restartPolicy: Never on the pod template does not stop a Kubernetes Job from retrying: a Job replaces failed pods and may run more than once, so a job that can exhaust a node will keep moving to new nodes.

  3. Symptoms

    While running the CI process on a local machine to test an application Helm chart, the SRE lead watched the pods with watch kubectl get pods. All pods reached Running, and then some went back to Pending. Two hours later the problem had grown and some pods showed the phase Unknown.

    Trigger

    A CI run installed the application's Helm charts for all four markets (Efritin.com, Tonaton.com, Ikman.lk and Bikroy.com) on the nonproduction cluster at the same time.

    Root cause
    Component
    Contributing factor
    Detection

    The SRE lead saw pods go from Running back to Pending while watching kubectl get pods during the CI run; no monitoring raised an alert, even when all three workers were not ready.

    Remediation
    • terminated the three worker nodes and let the auto scaling group replace them
    Action items
    • Fix the Datadog integration for the nonproduction AWS account and repeat the installs with telemetry
    • Increase the worker root EBS volumes from 20GB to 120GB
    • Keep common base images pulled on every node with a DaemonSet until kops supports user hooks
    • Configure different allocation limits for the different layers in Kubernetes
    • Discuss a highly available Tiller with the Helm team
    • Find a way to throttle the number of newly created pods
    Lessons

    An ordinary deploy of the application could collapse the cluster, because the default 20GB gp2 root volumes could not keep up with parallel image pulls and container starts. Without node metrics and pod phase metrics, three NotReady workers raised no alert. A single Tiller replica can block the deploy that would fix an outage.

Check your cluster for this

These 9 cases involve Container memory limit and Application database. 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 cause1

Capacity exhaustion9 cases

  1. IL-0155 Some DOKS clusters in NYC1 saw intermittent DNS timeouts and NodeNotReady events because CoreDNS ran on shared-CPU Droplet worker nodes
  2. IL-0085 A control plane node of Magic Pages' Kubernetes cluster on Hetzner Cloud ran out of memory, the cluster's own calls then used up the Hetzner API rate limit, and all customer websites were down for about 7.5 hours
  3. IL-0110 A Grafana Agent pod's high memory use and crash-looping Hangfire pods drove a Kubernetes node into system OOM and NotReady, twice in one day
    DFDS2024
  4. IL-0168 Simultaneous cluster auto-upgrades overloaded Scaleway's Kubernetes API, and a node authentication retry loop kept Kapsule and Kosmos nodes NotReady in FR-PAR
  5. IL-0169 The Scaleway Kubernetes API in FR-PAR ran out of memory under simultaneous deployments, and because it also handled node authentication, Kapsule and Kosmos nodes went NotReady
  6. IL-0016 Prometheus on the live cluster ran out of memory and was OOMKilled, and the monitoring node it ran on went NotReady
  7. IL-0064 CPU-heavy pods packed onto one Google Cloud node drove it to kernel panics, and the crash moved from node to node until the site was down
  8. IL-0036 A reindex Job that kept failing exhausted one node after another until the whole cluster was down
  9. IL-0040 Parallel Helm installs saturated small gp2 root volumes on a kops cluster and left all three workers NotReady with the kubelet or Docker down