Cases2 cases

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1. IL-0035 Worker nodes went NotReady after a new ElastAlert rule without memory limits used up node memory

   NU.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.

   Node NotReadyHigh error rateHigh latencyIntermittent timeoutsMonitoring outageOOMKilled

   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

   Configuration change

   Component

   Container memory limitkubeletPrometheus

   Contributing factor

   No resource requests or limitsUnreviewed defaultsNo alert on limitMonitoring blind spotExcessive blast radius

   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.

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2. IL-0038 kubelet rollout hit a Kubernetes bug and left every node in a cluster NotReady, triggering mass pod eviction

   Oath2018

   Symptoms

   During a rolling update of a kubelet change in one of Oath's on-premises production clusters, nodes started going NotReady, and soon all nodes in the cluster were NotReady.

   Node NotReadyPod evictionPods Pending

   Trigger

   A change to kubelet was rolled out across the nodes of one cluster; on restart, kubelet cleans up transient cgroup files, and a Kubernetes bug in that step left kubelet stuck instead of starting.

   Root cause

   Software defect

   Component

   kubeletKubernetes controller manager

   Contributing factor

   No health probesExcessive blast radius

   Detection

   Nodes reported NotReady and the eviction graphs climbed while the kubelet rollout was in progress.

   Remediation

   • failed the affected data center over so users were routed to the next available data center

   Action items

   • Run a functional test of kubelet after each upgrade batch and certify it before the next 30% of nodes are updated

   Lessons

   Check kubelet after upgrading it before moving to the next batch; a simple curl against the kubelet API would have caught this. The node controller's eviction throttling and full disruption mode, which the speakers note is not well documented, kept a cluster-wide kubelet failure from evicting every pod.

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