Incident Library
  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases3 cases

1 to 3 of 3

  1. Symptoms

    On 23 February 2023 Stytch's EKS worker nodes went Ready:Unknown one after another, Karpenter failed to launch replacement nodes, and with fewer and fewer pods scheduled the Live Stytch API went down for 14 minutes, returning 5XX on every call.

    Trigger

    At 14:21 UTC Stytch landed a change to remove unused EKS managed node groups, because it had decided to run its data plane applications fully on nodes provisioned by Karpenter. Because Crossplane resources use an orphan deletion policy, engineers deleted the node groups in the AWS console, first in staging and then in production.

    Root cause
    Component
    Contributing factor
    Detection

    Low-urgency alerts that Karpenter could not find the instance profile fired in staging at 16:06 UTC and in production at 17:48 UTC but were not treated as an incident. The incident process started at 20:26 UTC when node launch failures spiked the Karpenter error rate, and Kubernetes monitoring alerts in production followed at 20:44 UTC. The support team flagged the outage at 21:14 UTC.

    Remediation
    • Reverted the node group deletion, which recreated the managed node groups
    • Manually scaled up one of the Live API node groups with more and much larger nodes and removed its taints
    • Removed node selectors from the applications one after another so their pods could be scheduled
    Action items
    • Treat Karpenter errors as high-urgency alerts that page the on-call engineer
    • Tune cluster alerting thresholds to send a high-urgency page earlier
    • Add alerts for nodes that stay NotReady or Unknown for long periods
    • Raise the thresholds of other deployment alerts, such as unschedulable pods and replicas not available
    • Give Karpenter its own IAM instance profile, separate from the one used by the node groups
    • Separate other AWS resources that were shared between uses, specifically IAM and security groups
    • Rework the EKS and Karpenter configuration so system instance profiles are unique, static per cluster and generated by Karpenter
    • Introduce a cloud visualization tool for engineers making infrastructure changes
    • Add live system and product metrics to the status page
    • Ask AWS to confirm the undocumented actions and side effects of deleting a node group
    • Correct the shared use of IAM roles and security groups across the infrastructure
    Lessons

    The IAM role for Karpenter's self-managed nodes should never have been the same as the one for the managed node groups; sharing it is what let the node group deletion break Karpenter, and the roles had been left combined for speed and simplicity when Karpenter was first set up. The hours-long delay between the configuration change and its effect made the incident hard to assess, and AWS confirmed that this delay is expected, so Stytch will allow for it in future IAM instance profile changes.

  2. Symptoms

    During a rollout of the Grafana Loki distributor Deployment in one Grafana Cloud Logs environment, the write path went down for about 25 minutes. The newly started distributor pods were OOM-killed over and over, never passed their health and readiness checks, and the rollout stopped making progress.

    Trigger

    Step 1 of moving the Loki ring off a separately deployed key-value store onto embedded memberlist added a new label, gossip_ring_member: 'true', to the distributor pods and Service, together with a small config change, and the change required a rollout of the distributors.

    Root cause
    Component
    Contributing factor
    Detection

    The first clue was kubectl get pods and the kube_deployment_status_replicas_updated metric showing that only 16 of 140 distributor pods had been updated.

    Remediation
    • scaled the distributor Deployment out horizontally so the load spread over more pods with the new label and the rollout could continue
    • reverted the migration step to end the outage
    • set service_ignored_labels:: [$._config.gossip_member_label] and passed it to k.util.serviceFor so the label is no longer copied into the Service selector
    Action items
    • Update the function that generates a Service from a Deployment or StatefulSet to handle edge cases, including this one
    Lessons

    A Service whose selector is built by copying every label of a workload changes which pods it matches as soon as a new label is added. During a rollout it then matches only the new pods, which receive all the traffic before there are enough of them. A few errors during a rollout in other environments hid the problem, because those environments gave distributors more memory and could absorb the shift. Manifest diffs kept for every pull request made it possible to see that the Service selector had changed.

  3. Symptoms

    Datadog alerted the DevOps team to a high normalised load average, first on the staging cluster (Day 0, 21:06 EST) and the next day on the development cluster (Day 1, 16:53 EST). The load was first put down to a legitimate service that kept scaling up and down in both environments, and because of the volume of identical alerts they were muted until things settled.

    Trigger

    An automated crawler found the Weave Scope dashboard on a public load balancer that required no authentication. Weave Scope can open a shell in running containers, and its scope-agent containers ran privileged, as root and with the host's root filesystem mounted, so a command started there could run on the host.

    Root cause
    Component
    Contributing factor
    Detection

    Datadog alerts on high normalised load average, muted at first as noise from a legitimate service; on Day 3 an engineer ran top on a node and found the gcc process at 100% CPU.

    Remediation
    • stopped Weave Scope and removed its deployment from all Kubernetes clusters
    • checked access logs for unauthorised access to the instances
    • confirmed the miner's outbound connections went only to a mining pool
    • isolated one affected node for later investigation
    • rotated out every node in each cluster so all affected hosts were destroyed and rebuilt
    Action items
    • Audit all Kubernetes and deployment YAML files and security groups for services that are unintentionally public or misconfigured
    • Replace load-average alerts with more meaningful monitors and tune them to signal a real anomaly
    • Research tools such as falcon or sysdig for behavioural monitoring and anomaly and intrusion detection
    • Evaluate Istio and Linkerd for observing and controlling end-to-end network traffic
    • Analyse the cost of scanning Docker images and containers for known vulnerabilities
    • Set aside time in architecture discussions to revisit older choices such as running containers as root
    • Share knowledge of large projects, such as Kubernetes version migrations, across the whole team
    Lessons

    Load average was not a useful signal for spotting a problem in the clusters, and muted noisy alerts nearly hid the miner. A load balancer that Kubernetes creates belongs to Kubernetes: a manual security group edit in the AWS console is reverted, so internal exposure must be declared in the Kubernetes YAML. A dashboard that can open shells, in front of privileged agents that mount the host's root filesystem, gives whoever reaches it root on every node.

Check your cluster for this

These 3 cases involve Configuration templating and Cloud load balancer. 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.

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