Cases4 cases
1 to 4 of 4
IL-0169The 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 NotReadyScaleway2024- 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.
- Trigger
Simultaneous deployments in the FR-PAR region pushed the Scaleway Kubernetes API out of memory.
- Root cause
- Component
- Contributing factor
- 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.
IL-0144A systemd security update installed by unattended-upgrades lost the DNS configuration of Ubuntu 18.04 VMs, so AKS kubelets could not resolve registry names and pods failed with ImagePullBackOffMicrosoft Azure2022- Symptoms
From 06:00 UTC on 30 August 2022, Azure VMs running Ubuntu 18.04 (bionic) with unattended-upgrades enabled began failing DNS resolution and losing network connectivity. Several Azure teams, among them the AKS and Azure Container Apps teams, were alerted by production alerts shortly after the update packages were published.
- Trigger
Unattended-upgrades on Ubuntu 18.04 VMs installed a Canonical security update published at 06:00 UTC on 30 August 2022, including systemd version 237-3ubuntu10.54.
- Root cause
- Component
- Contributing factor
- Detection
Several Azure teams, including AKS and Azure Container Apps, were alerted by production alerts shortly after the packages were published; incoming support cases then confirmed which Ubuntu versions were affected.
- Remediation
- pointed customers to Canonical's description of the systemd bug and its fix
- recommended rebooting affected VMs or running a template script that repairs DNS resolution
- built automatic detection and remediation for AKS nodes and rolled it out across all regions
- mitigated the remaining AKS customers manually through support
- Action items
- Review the process that lets critical security updates bypass Safe Deployment Practices
- Improve monitoring of the AKS data plane to alert on an uptick of errors
- Review AKS monitoring algorithms so that similar VM errors are detected and alerted on
- Establish an improved escalation path to Canonical during outages and add it to internal Technical Service Guides
- AKS takes full control of the node security patch mechanism, with additional testing and controlled release of patches (estimated December 2022)
- Work with Canonical to run dedicated tests on proposed packages before they are published for Azure IaaS VMs
- Establish a process with Canonical to close the testing gap for the upgrade scenario (estimated March 2023)
- Give AKS customers maintenance window control and environment staging for these patches (estimated December 2023)
- Lessons
Security patches applied automatically by unattended-upgrades, once a day by default, and outside Azure's Safe Deployment Practices reached Ubuntu 18.04 VMs in every Azure region, so one systemd regression became a DNS outage across Azure. On AKS, lost node DNS showed up as image pull failures such as ImagePullBackoff, because kubelet could not resolve the registry. Azure plans to put node security patching under AKS's control with testing and controlled release; customers can use automatic node image upgrade for AKS, or automatic VM guest patching for VMs, instead of unattended-upgrades.
IL-0176Prometheus in a 235-node Kubernetes cluster crash-looped because over two million series exhausted host memory and the kernel OOM killer chose it first, as Burstable QoS gave it oom_score_adj 999LINE2020- Symptoms
One Monday morning the author opened the Prometheus dashboard to check a Kubernetes cluster for alerts and could not reach it. The Prometheus pod was in CrashLoopBackOff: kubectl get pods showed it 1/2 ready with 950 restarts over 3d20h on worker3.
- Trigger
After start, the Prometheus time series count rose to 2,162,256 within five minutes and its memory use filled the 8GB host.
- Root cause
- Component
- Contributing factor
- Detection
The author found it on a Monday morning when the Prometheus dashboard, opened to check the cluster for alerts, could not be reached.
- Remediation
- removed most of the unnecessary settings from the Prometheus ConfigMap, after which the container stopped crashing
- Action items
- Set appropriate resource requests and limits on the Prometheus pod
- Reduce unneeded metrics by adjusting scrape targets or scrape interval
- Estimate Prometheus memory needs, provide dedicated hosts with a node label such as deploy-topology: Prometheus, and pin the Prometheus pod to them with a nodeSelector
- Lessons
Exit code 137 together with an OOM event in the kubelet log means the kernel killed the container, not kubelet. Under node memory pressure the kernel kills the process with the highest score, and kubelet derives each container's oom_score_adj from the pod's QoS class: a container without a memory request in a pod where another container has one ends up Burstable with a score near 1000, so it is killed first. In a large cluster, Prometheus memory needs to be estimated from the expected series count and requested explicitly.
IL-0035Worker nodes went NotReady after a new ElastAlert rule without memory limits used up node memoryNU.nl2019- Symptoms
The NU.nl development team got reports that several services on one of its Kubernetes clusters behaved erratically: occasional error pages, slow responses and timeouts. The affected services were mostly internal tools and dashboards.
- Trigger
A new ElastAlert rule, deployed shortly before from the command line, that fired if the Cloudfront-* Elasticsearch indexes stopped receiving documents; those indexes take a few million requests per hour, and the rule made ElastAlert's memory grow without bound.
- Root cause
- Component
- Contributing factor
- Detection
Users reported error pages, slow responses and timeouts from several services; no alert fired.
- Remediation
- terminated the NotReady nodes one by one so the auto-scaling group replaced them (the new nodes also went NotReady, but Prometheus and Grafana landed on a stable node)
- found the ElastAlert pods' memory growth on the Grafana pod memory dashboard
- fixed the ElastAlert problem that caused the memory growth
- Action items
- Define alerts on resource usage such as CPU, memory and disk space
- Keep researching an alerting strategy that combines Elasticsearch, Prometheus Alertmanager and New Relic
- Consider exporting metrics out of the cluster and running Grafana outside it, on EC2 or a separate Kubernetes cluster
- Either visualise the important metrics in the ELK stack or make Prometheus and Grafana more available, and improve the metrics strategy
- Set resource limits for ElastAlert through the Helm values
- Configure namespaces with default memory requests and limits
- Isolate customer-facing workloads from build, logging and monitoring workloads (a dedicated node group, or later a separate tools cluster)
- Deploy everything through automation such as Jenkins pipelines, and consider a GitOps approach
- Deploy through a pipeline that includes a smoke test step
- Make Kubernetes and cloud infrastructure work part of the team's sprints, picked up by all team members while pairing with more experienced members, and hold workshops that go deep into specific topics
- Lessons
Fixing the root cause covers only a small part of what an incident can teach; the chain of smaller failures around it is where most of the learning is. A pod without a memory limit can take whole nodes down, so limits need defaults at the namespace level. Monitoring that runs inside the cluster it watches goes blind with it. Changes installed by hand from the command line leave the rest of the team without a record of what changed.
These 4 cases involve kubelet and Container memory limit. 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 cause3
Capacity exhaustion2 cases
- Contributing factor
IL-0169The 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 NotReadyScaleway2024IL-0176Prometheus in a 235-node Kubernetes cluster crash-looped because over two million series exhausted host memory and the kernel OOM killer chose it first, as Burstable QoS gave it oom_score_adj 999LINE2020
Breaking change in an upgrade1 case
- Component
- Contributing factor
- Organisation
Configuration change1 case
- Contributing factor
- Organisation