Cases9 cases

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1. 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

   Scaleway2024

   Symptoms

   At 01:04 CET on 13 February 2024, the Kubernetes API behind Scaleway's managed Kubernetes services Kapsule and Kosmos in the Paris region (FR-PAR) spiked in RAM and CPU use and ran out of memory. Nodes in FR-PAR could no longer authenticate to their control plane, and some of them went "Not Ready". Customers on both shared (mutualized) and dedicated environments were affected.

   Node NotReadyControl plane lagOOMKilled

   Trigger

   A new Kubernetes release was made available to all users on 12 February 2024, and during the night of 12 to 13 February many clusters triggered their auto-upgrade at the same time.

   Root cause

   Capacity exhaustion

   Component

   Kubernetes API server

   Contributing factor

   Retry stormAutomation amplificationNo staged rollout

   Detection

   The timeline's first entry, at 01:04 CET, records the Kubernetes API's RAM and CPU spikes and out-of-memory state, with nodes unable to authenticate to their control plane and some becoming "Not Ready". The first recorded action, 42 minutes later at 01:46, was to increase the resources allocated to the API.

   Remediation

   • increased the resources allocated to the Kubernetes API at 01:46 and again at 02:20
   • applied API traffic restrictions at 02:30 to smooth the incoming traffic
   • removed the traffic restrictions progressively in 50-100 batches from 03:20
   • ran a script at 03:40 to replace the failing nodes created during the congestion
   • rolled back to the former node authentication mechanism, first on a subset of clusters from 15:45 and on all clusters by 19:41 on 19 February
   • disabled cluster upgrade and configuration update features until 10:30 on 20 February

   Action items

   • Increase the resources allocated to the Kubernetes API
   • Roll back to the former node authentication mechanism
   • Implement a local authentication cache on nodes
   • Rework the resource allocation strategy to behave better under load spikes
   • Add new request queuing mechanisms for Kubernetes
   • Separate the different components to reduce side effects under high load or failure
   • Monitor selected metrics closely to identify anomalous patterns earlier
   • Refund customers who deployed nodes during the incident but could not use them normally

   Lessons

   Letting many clusters auto-upgrade at the same moment after a release turns routine upgrades into one coordinated load spike on the shared Kubernetes API. A node authentication mechanism that retries without letting up turns a slow API into an unavailable one, and auto-healing that replaces NotReady nodes amplifies the problem. The congestion pattern had already appeared three weeks earlier, and short-term mitigations did not stop it from recurring, so Scaleway rolled back the new authentication mechanism. Scaleway notes that as the number of customer clusters and nodes grows sharply, traffic control mechanisms have to improve to prevent congestion.

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2. 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

   Scaleway2024

   Symptoms

   At 23:48 CET on 24 January 2024 the Scaleway Kubernetes API for the FR-PAR region ran out of memory. At the same minute Scaleway saw requests to its API Gateway spike.

   Node NotReadyOOMKilledIntermittent timeoutsMonitoring outage

   Trigger

   Simultaneous deployments in the FR-PAR region pushed the Scaleway Kubernetes API out of memory.

   Root cause

   Capacity exhaustion

   Component

   Container memory limitkubelet

   Contributing factor

   Single point of failureRetry storm

   Detection

   Increased load on the API Gateway was detected at 23:48, the minute the incident began, and the incident was escalated to on-call engineers at 00:00:10.

   Remediation

   • raised the memory limit and garbage collection thresholds of the Kubernetes managed services
   • deployed additional replicas of key services
   • purged the registry cache and monitored the clusters as they stabilised
   • adjusted service configurations after the incident to keep the platform stable

   Action items

   • Implement a local authentication cache
   • Further develop node authentication
   • Enhance monitoring, adjust rate limiting strategies and improve incident response protocols

   Lessons

   Because the Kubernetes API also handled node authentication, its memory exhaustion made some nodes NotReady, and the endless retries of those nodes added load on the API Gateway. Scaleway plans a local authentication cache and further work on node authentication.

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3. IL-0016 Prometheus on the live cluster ran out of memory and was OOMKilled, and the monitoring node it ran on went NotReady

   UK Ministry of Justice2023

   Symptoms

   At 14:05 on 25 July 2023, a high-priority PagerDuty alert from Pingdom reported that the "Prometheus - live healthcheck" was DOWN. Prometheus on the live cluster was unavailable, and the Cloud Platform lost its monitoring for a while.

   Monitoring outageOOMKilledNode NotReady

   Trigger

   The growing number of namespaces and Prometheus rules raised Prometheus' memory needs beyond what its node instance size could hold.

   Root cause

   Capacity exhaustion

   Component

   PrometheusNode poolContainer memory limit

   Contributing factor

   No alert on limit

   Detection

   A Pingdom health check on Prometheus failed and raised a high-priority PagerDuty alert.

   Remediation

   • drained the monitoring node, moving Prometheus to another monitoring node
   • changed the node instance size to r6i.4xlarge
   • raised the Prometheus memory limit to 100Gi
   • set the Prometheus container limits to 12 CPU cores and 110Gi of memory

   Action items

   • Add an alert on node memory usage and on a pod using up most of a node's memory (issue #4538)

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4. 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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5. 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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