Cases2 cases
1 to 2 of 2
IL-0110A Grafana Agent pod's high memory use and crash-looping Hangfire pods drove a Kubernetes node into system OOM and NotReady, twice in one dayDFDS2024- 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.
- 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
- Component
- Contributing factor
- 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.
IL-0112The daily node rollover put DFDS's EKS nodes on an AMI later recalled for a kernel issue, causing "PLEG is not healthy" NodeNotReady flaps and pod network timeoutsDFDS2022- Symptoms
On 2022-10-31 a planned upgrade of the vpc-cni EKS add-on, started from the deployment pipeline at 13:45 UTC, timed out at 14:10. Only about 10 of the 45 aws-node pods had upgraded, 5 were stuck in Terminating and the other 30 had not been attempted.
- Trigger
At 07:30 UTC on 2022-10-31 the daily node rollover replaced the existing nodes with nodes built from AMI v20221027, the latest AWS EKS node AMI, released on 2022-10-29 and later recalled because of a kernel issue.
- Root cause
- Component
- Contributing factor
- Detection
The team noticed nodes flapping between NodeNotReady and NodeReady ("KubeletNotReady PLEG is not healthy") at 14:30 UTC while watching the stalled vpc-cni upgrade, about seven hours after the rollover. Time to detection was 7 hours. Alerting did not catch the NodeNotReady events or the socket growth.
- Remediation
- cordoned, drained and deleted 15 stuck nodes one at a time to complete the vpc-cni upgrade
- changed the Terraform infrastructure-modules so a specific AMI could be set
- rolled the EC2 Auto Scaling group launch configuration back to the previous known good AMI through the pipeline
- Action items
- Reach out to teams with suggestions about readiness and liveness probes
- Create a dashboard for readiness and liveness probe coverage
- Write a wiki article on readiness and liveness probes and their usefulness
- Modify infrastructure-modules to allow specifying a particular AMI
- Schedule a discussion on whether to take the latest AMI immediately and how to test new AMIs before they are deployed
- Implement alerting on abnormal NodeNotReady events and on increased socket use
- Create a learning path for Kubernetes within the team
- Collect logs from nodes centrally
- Create a Prometheus exporter that retrieves the latest available AMI, with a dashboard and alerts
- Lessons
When a new node AMI has just been rolled out, upgrading other cluster components on the same day makes it hard to tell which change is causing trouble; here the vpc-cni upgrade on the same day confused matters. Taking the latest AMI automatically with no way to pin one meant a rollback first needed a Terraform change. The team also concluded that it needs better communication paths with application teams during incidents.
These 2 cases involve Application database and kubelet. 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 cause2
Capacity exhaustion1 case
- Contributing factor
- Organisation
Software defect1 case
- Contributing factor
- Organisation