Cases23 cases

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1. IL-0154 Line cards on an SFO3 core router rebooted together and halved backbone capacity, and DOKS nodes whose guest networking did not recover stayed NotReady with degraded API servers until all affected nodes in the SFO3 DOKS fleet were recycled

   DigitalOcean2024

   Symptoms

   From 22:25 to 22:50 UTC every DigitalOcean service in the SFO3 region had network connectivity problems, as traffic between the datacenter and the backbone dropped. Traffic through the router was back by 22:30 and SFO3's control plane systems had reconnected by 22:50, and most services recovered then.

   Node NotReadyControl plane unresponsiveIntermittent connection failures

   Trigger

   Most of the line cards on one SFO3 core router rebooted at the same time at 22:21 UTC because of hardware errors on the device.

   Root cause

   DNS or network fault

   Component

   Kubernetes API serverkubelet

   Contributing factor

   –

   Remediation

   • The crashed line cards came back online and traffic on the core router was restored
   • Manually recycled all affected nodes across the SFO3 DOKS fleet

   Action items

   • Work with the router vendor's support team to find the root cause of the line card crash
   • Upgrade software on the core routers in SFO3
   • Raise thresholds for automated remediation so affected nodes are restored without manual action

   Lessons

   A short network fault can leave Kubernetes nodes broken long after the network itself is healthy, when the guest networking on the machines does not recover by itself. Checking node health and the API servers after the network returns, and having automated remediation that is allowed to replace many nodes at once, shortens that tail.

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2. 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

   Symptoms

   At 10:01 UTC on 2024-03-13 a Kubernetes node entered NotReady state, with CPU requests at 78% and memory requests at 82%. An alert fired in Slack at 10:03 and was picked up at 10:05. An attempt to SSH into the node at 10:13 failed because it was unresponsive; it started responding again at 10:19.

   Node NotReadyContainer crash loopOOMKilledMonitoring outage

   Trigger

   Pods of a dev container that used Hangfire to trigger jobs failed with OOM and crash-looped on a node where a Grafana Agent pod was already using a lot of memory.

   Root cause

   Capacity exhaustion

   Component

   Telemetry agentContainer memory limitApplication database

   Contributing factor

   Excessive blast radiusNo resource requests or limitsHarmful manual actionMonitoring blind spot

   Detection

   A Slack alert fired two minutes after the node went NotReady and was picked up two minutes later; the second node's NotReady at 15:03 also raised a Slack alert.

   Remediation

   • marked the EC2 instance unhealthy so a new node started
   • cordoned and force-drained the NotReady node and terminated its EC2 instance
   • removed the new LimitRange from the Grafana Agent namespace and restarted the Grafana Agent pod
   • scaled the dev container to 0 replicas, after which EC2 network traffic returned to normal
   • after the second NotReady, scaled the dev container to 0 replicas again and added a new node
   • emailed the team that owns the dev container, which confirmed it was working on a fix

   Action items

   • Move grafana-agent to the monitoring node group
   • Add alerts for when bandwidth across the cluster reaches a certain threshold
   • Investigate whether memory limits can be set on the grafana-agent Helm chart
   • Investigate grafana-agent memory usage
   • Ask Grafana support whether grafana-agent should use a PVC
   • Consider pushing node logs to Loki with limited retention
   • Create a wiki page with common metrics and log queries to check when investigating issues with Kubernetes nodes

   Lessons

   Dev workloads mixed with production let one crash-looping dev container take down nodes that production also used, and a monitoring agent outside its dedicated node group added to the memory pressure. Scaling the suspect container back up before its owners had fixed it brought the failure back on the replacement node. The team also noted that action items from earlier post-mortems need follow-up, and that knowledge of useful CloudWatch metrics had not been shared, which made the diagnosis harder.

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3. IL-0021 GKE GPU nodes on Container-Optimized OS could not download NVIDIA drivers (403 Forbidden) and came up without working GPUs

   Google Cloud2024

   Symptoms

   From 08:00 US/Pacific on 12 March 2024, GKE GPU nodes running Container-Optimized OS (COS) that were newly created or recreated came up with GPU drivers that did not work, so workloads that used the GPUs could not run. GKE showed elevated errors.

   GPU unavailableNode NotReady

   Root cause

   Dependency failure

   Component

   GPU driverNode operating system imageNode pool

   Contributing factor

   Automation amplification

   Detection

   The report does not say how Google detected the issue. Affected users saw "Failed to download GPU driver installer, status: 403 Forbidden" on the GPU node when installing the driver.

   Remediation

   • Halted automatic node recreations, which attempt GPU driver downloads, until the issue was mitigated
   • Worked with the driver partner to resolve access to the driver download bucket

   Lessons

   The status page report states no lessons or follow-up actions.

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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

   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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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

   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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