Cases14 cases

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1. 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

   Moonlight2019

   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.

   High error rateIntermittent connection failuresNode NotReadyService outageSustained high node CPU

   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

   Capacity exhaustion

   Component

   Pod scheduling and placementLinux kernelApplication database

   Contributing factor

   Single point of failureUnverified assumptionAutomation amplification

   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.

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2. IL-0055 A failing CronJob with the default concurrency policy piled up thousands of restarting pods and took down a cluster

   Target2018

   Symptoms

   A Kubernetes cluster went down after one CronJob kept failing and its pods piled up. Because each failed run kept restarting instead of being replaced by the next one, the pods accumulated into the thousands. The speaker's arithmetic for a job scheduled every minute that fails for three days is 4,320 restarting pods.

   Service outage

   Trigger

   A CronJob kept failing.

   Root cause

   Configuration change

   Component

   Jobs and CronJobsNode pool

   Contributing factor

   Unreviewed defaultsAutomation amplification

   Lessons

   When deploying a CronJob, set its concurrency policy to Replace or Forbid; with the default, failing runs accumulate and restart together. An application should handle a missing dependency with probes and bounded back-off rather than crash in a loop, which also keeps it from hammering a dependency that is already struggling.

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3. IL-0036 A reindex Job that kept failing exhausted one node after another until the whole cluster was down

   Universe2017

   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.

   Service outageNode NotReadyNode recreation loop

   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

   Capacity exhaustion

   Component

   Jobs and CronJobsPod scheduling and placement

   Contributing factor

   Unverified assumptionAutomation amplificationExcessive blast radius

   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.

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