Cases11 cases

6 to 10 of 11

1. IL-0091 Changing the worker node instance type through Terraform recycled all nodes at once and deleted users' production pods together

   UK Ministry of Justice2023

   Symptoms

   At 10:23 on 6 June 2023 a user of the Cloud Platform reported that all of their production pods had been deleted at the same moment. Several users received Pingdom alerts that their applications were down for a few minutes.

   Service outage

   Trigger

   The team changed the instance type of the cluster's worker nodes through Terraform.

   Root cause

   Configuration change

   Component

   Node poolTerraform

   Contributing factor

   Excessive blast radiusNo runbook

   Detection

   Users reported that their production pods had been deleted at once and that Pingdom alerts showed their applications down; the incident was declared at 11:00.

   Action items

   • Ask AWS, through a support ticket, for the steps to change the node instance type without an outage
   • Plan how to make instance type changes through Terraform without downtime and add a runbook with the steps for changing the node instance type

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2. IL-0177 WebSocket connections to LINE's messaging-hub on Kubernetes dropped all at once whenever another service's change reloaded a shared HAProxy L7 load balancer, and the reconnect wave overloaded a token API and filled nf_conntrack on Nginx

   LINE+2022

   Symptoms

   The graph of WebSocket connections to messaging-hub, the messaging platform used by the Japanese food delivery service Demaecan, showed sudden deep drops even outside peak traffic. The drops kept coming back at irregular intervals. Messages still reached clients, because messaging-hub switches to Firebase Cloud Messaging when a WebSocket is gone.

   Connection resetsDatabase overloadIntermittent connection failuresHigh latency

   Trigger

   Another service that shared the same L7 load balancer deployed its own load balancer configuration in the Verda dashboard, which reloaded HAProxy; 30 minutes later, at the hard-stop-after limit, the old HAProxy process exited and closed every WebSocket connection it still held.

   Root cause

   Configuration change

   Component

   HAProxyCloud load balancerconntrack tableIngress controller

   Contributing factor

   Change with a delayed effectExcessive blast radiusRetry stormUnverified assumption

   Detection

   The developer noticed deep, sudden drops in the WebSocket connection graph that were not tied to peak traffic and kept recurring irregularly. The Nginx packet drops were found through network monitoring.

   Remediation

   • separated the Merchant system's token issuance API into its own deployment so reconnect traffic did not delay other Merchant APIs
   • scaled out Nginx with pod anti-affinity and a label selector so each pod ran on a different node, which stopped the nf_conntrack packet drops
   • raised Ingress Nginx proxy-read-timeout and proxy-send-timeout and the load balancer timeout to 3600s, which did not stop the drops
   • moved messaging-hub from the shared L7 load balancer to an L4 load balancer, which ended the WebSocket drops

   Lessons

   A reload of a shared load balancer by a different team can cut long-lived connections, and with hard-stop-after the cut comes 30 minutes later, far from the change that caused it. The author's lesson is not to narrow the scope of the search too early: trusting that the infrastructure was fine kept the investigation inside the team's own systems for days. A reconnect wave from many WebSocket clients can overload the systems that issue connection tokens and fill nf_conntrack on proxy nodes. Scaling Nginx out only helps for conntrack if the pods land on different nodes, and anti-affinity leaves extra replicas Pending once they outnumber the nodes. That messaging-hub problems can still load the connected systems remains an open problem.

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3. IL-0010 A templating change that dropped its {{ }} delimiters made Argo CD delete all 478 Skyscanner services in every region

   Skyscanner2021

   Symptoms

   On 25 August 2021, skyscanner.net was unavailable and the Skyscanner mobile apps could not work, for travellers and business partners everywhere at the same time. The full global outage lasted four and a half hours.

   Service outageResources deleted

   Trigger

   A peer-reviewed change to a rarely changed root-level file of the cells templating configuration, intended as a no-op, that left out the {{ }} delimiters; it was submitted around 15:30 GMT, merged to master and rolled out automatically to every region at once.

   Root cause

   Configuration change

   Component

   Argo CDConfiguration templating

   Contributing factor

   Missed in reviewNo staged rolloutNo configuration testsUntested backupAutomation amplificationExcessive blast radius

   Remediation

   • restored the correct configuration for each cluster and let Argo CD reconcile the cluster back to it
   • restored services through the backup and restoration process
   • brought one region back first with the critical services and served all traffic from it from around 20:30 GMT
   • restored and verified the remaining regions and non-critical services over Thursday and Friday

   Action items

   • Avoid global configuration deploys, including rare change paths like this one
   • Treat templated configuration as code and add testing and linting
   • Plan and wargame more drastic failure scenarios in runbooks
   • Verify backup and restore processes, including access to the backups and the loss of a region
   • Refactor runbooks so they are clear and, where appropriate, idempotent for a stressed engineer in the early morning
   • Reconsider how much configuration is templated across regions, weighing configuration drift against automated global rollout

   Lessons

   Global configuration changes had been prevented in many cases, but not in this rarely used path. Configuration that gains templating and logic has become code and needs tests and at least linting. The failure scenarios and runbooks were not pessimistic enough, a backup only counts once it has been restored, and runbooks need care so they work for a stressed engineer at night. Automation that templates configuration across regions trades drift for the risk of rolling one mistake out everywhere. An experienced incident commander who kept the response calm and blameless made a large difference.

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4. IL-0008 An unresponsive OPA validating webhook crash-looped the API server during a GKE master upgrade, and node auto-repair then recreated every node

   Jetstack2019

   Symptoms

   Jetstack was upgrading the master of a development cluster that many teams use to test their apps during the working day, a regional Google Kubernetes Engine (GKE) cluster in europe-west1. The upgrade ran through Jetstack's GKE Terraform pipeline and did not finish before the 20-minute Terraform timeout, while the GKE console still showed the cluster as upgrading.

   Upgrade stallControl plane unresponsiveNode recreation loopService outage

   Trigger

   A planned master upgrade of the shared development cluster. The same upgrade had been done on another pre-production environment earlier that day, and no API downtime was expected.

   Root cause

   Configuration change

   Component

   Admission webhookGKE control planeKubernetes API serverkubelet

   Contributing factor

   Excessive blast radiusNo health probesMonitoring blind spotAutomation amplification

   Detection

   The first sign was the master upgrade missing the 20-minute Terraform timeout; re-running the pipeline returned the kube-apiserver unhealthy error. The cause was identified with the help of Google Support.

   Remediation

   • Deleted the OPA ValidatingAdmissionWebhook resource during a window of API server access

   Action items

   • Limit the OPA webhook to the namespaces where the policy applies and development teams have access
   • Enable the webhook only for Ingress and Service resources, the only resources the policy validates
   • Add a liveness probe so OPA is restarted when it stops responding, and update the OPA documentation
   • Follow the open upstream Kubernetes issue about this behaviour

   Lessons

   With alerting on API server response times, the team might have seen CREATE and UPDATE requests slow down across the board as soon as the OPA-backed webhook was first deployed. Every workload needs probes: OPA looked so simple to deploy that the team skipped the Helm chart, which adds a livenessProbe for the admission controller containers among other adjustments to the tutorial configuration. Others had hit the same problem, and an upstream issue to improve it was still open.

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5. IL-0052 A cryptocurrency miner ran on every node of the development and staging clusters through a public, unauthenticated Weave Scope dashboard

   JW Player2019

   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.

   Sustained high node CPUUnauthorised access or a foreign workload

   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

   Configuration change

   Component

   Cluster dashboardCloud load balancer

   Contributing factor

   Ignored early signalUnreviewed defaultsExcessive blast radiusMonitoring blind spot

   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.

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