Cases11 cases

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1. IL-0530 Virtual router controllers in us-central1 ran out of memory in a loop, cutting networking for new and migrated VMs

   Google Cloud2023

   Symptoms

   On 5 October 2023 in us-central1, newly created VMs waited a long time before their networking worked, and VMs that had been live migrated lost connectivity for a long time after the migration. Networking telemetry showed cross-region packet loss to and from us-central1 from 03:08 US/Pacific. Health check state of VMs reached load balancers late.

   Packet lossNetwork unreachableOOMKilledStale endpoint routingCluster or node provisioning stall

   Trigger

   A management plane behaviour change, meant to decouple the processing of API updates to Instance Groups and Network Endpoint Groups used as load balancer backends, was deployed in us-central1 after rolling out to several other regions without incident.

   Root cause

   Faulty deployment

   Component

   Network control plane (SDN)Cloud load balancer

   Contributing factor

   Excessive blast radiusNo alert on limit

   Detection

   Engineers were alerted to slowness in the virtual network control plane in us-central1 at 21:45 US/Pacific on 4 October, before the packet loss started, and to controller failures from memory exhaustion at 02:11 on 5 October. Networking telemetry showed cross-region packet loss from 03:08.

   Remediation

   • Increased the memory allocated to the virtual network router controllers
   • Rolled back the management plane change in us-central1
   • Restarted by hand the routers that were still not accepting updates

   Action items

   • Alert proactively on memory risks and unexpected memory increases
   • Refactor the deployment configuration so engineers can reallocate memory much faster
   • Re-evaluate existing practices and add safety mechanisms for API reconciliation
   • Make management plane changes more visible across teams so the changes can be correlated faster
   • Adjust the deployment footprint so a regional API change is less likely to exhaust memory across the region at once
   • Optimise memory use in the traffic routers and their controllers

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2. IL-0178 On EKS, HPA scale-in returned 502 errors because containers stopped before their pod IPs left the Service endpoints, and after blue/green switches conntrack kept sending established connections to deleted pods behind an instance-mode ALB

   Lotte E-commerce2022

   Symptoms

   LOTTE ON, Lotte E-commerce's online shopping mall of about 40 microservices on Amazon EKS, returned errors for a period of time whenever the Horizontal Pod Autoscaler (HPA) scaled pods in after load dropped. Requests reached containers that had already been deleted and failed with 502 errors.

   High error rateIntermittent timeoutsStale endpoint routing

   Trigger

   HPA scale-in deleting pods, and the deletion of Blue pods after a blue/green switch of the Service label selector.

   Root cause

   DNS or network fault

   Component

   Horizontal pod autoscalerPod terminationkube-proxyconntrack tableCloud load balancerIngress controller

   Contributing factor

   Unreviewed defaults

   Remediation

   • delayed container shutdown on pod deletion (a wait in the SIGTERM handler or a preStop sleep, capped by terminationGracePeriodSeconds) so containers stop only after the pod has left the Service endpoints
   • switched some workloads' Ingress-created ALBs from instance mode to IP mode so traffic goes straight to pod IPs without iptables and conntrack

   Action items

   • Move all workloads to ALB IP mode gradually

   Lessons

   Removing a pod from Service endpoints and stopping its containers happen at the same time in Kubernetes, so a pod can stop while traffic is still routed to it unless shutdown is delayed with a preStop hook or in the application. With an instance-mode ALB, traffic passes through node iptables and conntrack, and established connections can keep going to a pod IP after its iptables rules are gone. IP mode avoids that path, within the limit of 1000 targets per target group.

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3. IL-0461 Every rollout of Datadog's metrics query service on Kubernetes raised errors that the logs blamed on DNS

   Datadog2022

   Symptoms

   From September 2021, each rollout of an update to Datadog's metrics query service, which serves real-time and historical metric data to the web frontend and to monitor evaluation, came with a rise in errors. Clients retried failed queries, so few errors reached users, but the retries slowed dashboards and monitors. The service's logs showed DNS errors stopping it from connecting to the data stores it depends on.

   High error rateDNS resolution failuresHigh latencyOOMKilledPacket lossStale endpoint routing

   Trigger

   Rollouts of the metrics query service, which delete the old pods. The client behaviour behind the failures came from an August 2021 rollout of the metrics query clients that applied round_robin as the new default gRPC load balancing policy.

   Root cause

   Configuration change

   Component

   conntrack tableCiliumLinux kernelCoreDNSClient-side DNS resolver and cacheexternal-dnsHTTP and RPC client library

   Contributing factor

   Change with a delayed effectRetry stormUnknown limitMonitoring blind spot

   Detection

   Errors rose during rollouts of the metrics query service, and the service's logs showed DNS errors when connecting to its data stores.

   Remediation

   • Raised the memory of the node-local-dns pods from 64 MB to 256 MB, which stopped the OOM kills but not the DNS errors
   • Tested larger instance types and confirmed that scaling up the service's infrastructure resolved the errors
   • Removed the custom gRPC reconnect parameters from the clients to restore the defaults

   Action items

   • Contribute a change to Cilium that adds an unreachable route for a deleted pod's IP so clients get an ICMP error

   Lessons

   The errors looked like DNS but were not. ENA metrics and VPC Flow Logs gave the visibility into VPC connection tracking that host metrics did not, and Cilium, Kubernetes and AWS networking interact in ways that can make reverse path filtering drop packets it should allow. DNS propagation time depends on many settings. The causes were changes Datadog had made itself, to work around a dependency bug, to resolve earlier incidents and to override default reconnect parameters, which looked safe at the time and showed their effects much later, when the link was hard to see.

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4. IL-0089 A test cluster deletion script run with the kube context pointing at the live-1 production cluster deleted its ingress controller, monitoring, logging, cert-manager, kiam and external-dns

   UK Ministry of Justice2020

   Symptoms

   At 18:27 on 21 September 2020 the Cloud Platform team detected that some services running on the live-1 production cluster had gone down, and some users could not reach them. The incident was declared at 18:40.

   Service outageResources deletedMonitoring outageStale endpoint routing

   Trigger

   A script for deleting a test cluster was triggered while the kube context was pointing at the live-1 production cluster instead of the test cluster.

   Root cause

   Operator error

   Component

   Ingress controllerCredential broker for podsexternal-dnsCloud load balancerPrometheus

   Contributing factor

   No safeguard on destructive change

   Detection

   The first detection was at 18:27, and the incident was declared 13 minutes later, at 18:40.

   Remediation

   • restored the default ingress controller together with external-dns and kiam, which it depends on
   • corrected the owner field in the Formbuilder Route 53 TXT records so external-dns pointed their A records at the new NLB
   • restored the remaining components with a targeted apply
   • ran the apply pipeline to restore all certificates, ServiceMonitors and Prometheus rules from the environment repository

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5. IL-0049 Partial DNS outage after CoreDNS scaled down and kube-proxy failed to delete stale conntrack entries

   Preply2020

   Symptoms

   Prometheus detected a high rate of 5xx responses on three services, called A, B and C in the write-up, and paged the on-call engineers through VictorOps at 22:18 EET. The 5xx rate was also visible in Kibana.

   DNS resolution failuresHigh error rateStale endpoint routing

   Trigger

   Because load in the cluster was low, the CoreDNS autoscaler reduced the number of CoreDNS pods from 3 to 2.

   Root cause

   DNS or network fault

   Component

   CoreDNSkube-proxyconntrack table

   Contributing factor

   Automation amplificationIgnored early signalNo caching

   Detection

   Prometheus alerted on a high 5xx rate on services A, B and C and paged on-call through VictorOps.

   Remediation

   • reverted the latest release of the affected service
   • a regular deploy created new nodes, the CoreDNS autoscaler added CoreDNS pods, and the conntrack table was rewritten

   Action items

   • Disable the autoscaler for CoreDNS
   • Run a DNS cache server in production
   • Monitor conntrack usage

   Lessons

   Scaling CoreDNS down is not free: if kube-proxy fails to clear conntrack entries for the removed pod, clients keep sending DNS queries to it. Known DNS weaknesses in a cluster should be prioritised before they cause an outage, and fixes that only treat consequences leave the underlying conntrack problem in place.

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