Cases3 cases

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1. IL-0071 Worker node running out of inodes while disk space looked fine, because containerd kept a full node_modules tree in each of several image layer snapshots

   Onkar Raghunath Shelke2026

   Symptoms

   A Kubernetes worker node paged with NodeFilesystemFilesFillingUp, the node_exporter mixin alert that predicts a filesystem will run out of inodes. The engineer checked disk space first: df -h showed the root filesystem 83% used, 103G used and 22G available. df -i showed inodes 67% used, 11M used and 5.3M free.

   Node disk full

   Trigger

   Several versions of a single-stage Node.js image, each shipping more than 40,000 files, were held on the node; containerd unpacked every layer with a distinct digest into its own snapshot, each with a full copy of node_modules.

   Root cause

   Capacity exhaustion

   Component

   Node root diskkubeletContainer runtime

   Contributing factor

   Unreviewed defaultsMonitoring blind spotUnknown limit

   Detection

   The NodeFilesystemFilesFillingUp alert from the node_exporter mixin fired on the predicted inode trend while inode use was at 67%.

   Action items

   • Build the image in multiple stages so the final image contains only the compiled assets
   • Add a flat alert on root filesystem inode use above 80% for 30 minutes alongside the predictive alert
   • Put a Prometheus query on a dashboard that shows, per node, inode usage minus disk usage, sorted from the highest
   • Remove unused images from nodes with crictl rmi --prune to free old snapshots

   Lessons

   kubelet's background cleanup works on bytes only. A workload heavy in small files gets no early intervention for inodes, and the first thing kubelet does at 5% free inodes is evict pods. Watch inode use on nodes separately from disk use, and keep dependency trees out of runtime images.

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

   Kubernetes project2019

   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.

   Node NotReadyNode kernel panicPods stuck in TerminatingThroughput degradation

   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

   Capacity exhaustion

   Component

   Cloud block storageNode root diskkubeletCI system

   Contributing factor

   Monitoring blind spotIgnored early signal

   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.

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3. 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

   Saltside2017

   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.

   Pods PendingImage pull failuresNode NotReadyService outage

   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

   Capacity exhaustion

   Component

   Node root diskkubeletContainer runtimeHelm

   Contributing factor

   Unreviewed defaultsMonitoring blind spotIgnored early signalSingle point of failure

   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.

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