Cases2 cases

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1. IL-0170 During a Lunar New Year event, traffic more than three times normal filled the nf_conntrack table on the EKS node running the Istio ingress gateway, dropping packets and taking down Backpackr's web and app services

   Backpackr2025

   Symptoms

   During a Lunar New Year event in January 2024, a developer posted a message in Slack suspecting an outage. While several people were checking it, the problem grew into a full outage of Backpackr's web and app services, and the company decided to stop the event.

   Service outage

   Trigger

   An unexpected traffic surge, more than three times normal, during the Lunar New Year event in January 2024.

   Root cause

   Capacity exhaustion

   Component

   conntrack tableIngress controllerIstio

   Contributing factor

   Single point of failureUnreviewed defaultsMonitoring blind spot

   Detection

   A developer reported a suspected outage in Slack; the outage became total while several people were still confirming it.

   Remediation

   • stopped the Lunar New Year event

   Action items

   • Raise net.netfilter.nf_conntrack_max on all nodes to memory bytes/16384/2, and three times that on Istio nodes, applied by the nodeOptimizer DaemonSet
   • Configure Istio mesh networking so sidecars communicate directly instead of through the ingressGateway
   • Upgrade the Istio nodes from c6.xlarge (12.5 Gbps) to n-type instances with up to 25 Gbps of network bandwidth
   • Strengthen monitoring with ENA network bandwidth and packet drops, detailed Istio ingressGateway and sidecar metrics, and CPU, memory and saturation

   Lessons

   When every request in a cluster goes through one ingress gateway node, that node's connection tracking table and network bandwidth set the limit for the whole service. The default nf_conntrack table size was too small for three times normal traffic, and once it filled, packets were dropped. After the outage Backpackr strengthened its monitoring of network bandwidth, packet drops and the Istio components.

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2. IL-0013 The conntrack table filled up on downsized GKE nodes and a high-traffic aggregation proxy saw climbing connection resets

   loveholidays2020

   Symptoms

   Shortly after a round of changes, loveholidays saw connectivity problems and raised error rates on its aggregation service. The service is a proxy between two other services of more than 100 instances each, handles over 10,000 requests per second continuously and can spike to four times that.

   Connection resetsHigh error rateIntermittent connection failures

   Trigger

   Three changes together: a change in service architecture, halving the RAM of the nodes that run the aggregation service, and sharding a downstream service, which doubled the number of connections to track.

   Root cause

   Capacity exhaustion

   Component

   conntrack tablekube-proxyNode poolHAProxy

   Contributing factor

   Unknown limitNo capacity planningNo alert on limit

   Detection

   Rising error rates and climbing connection reset errors in HAProxy, then node_exporter conntrack metrics compared with their limit.

   Remediation

   • moved the aggregation service to nodes with more RAM
   • limited the number of aggregation service pods per node

   Action items

   • Alert when conntrack table use goes above 75%, with (node_nf_conntrack_entries / on (pod) node_nf_conntrack_entries_limit / on (pod) group_right kube_pod_info) > 0.75

   Lessons

   The conntrack limit is tied to node memory, so resizing a node pool silently resizes the connection table, and on GKE the ratio did not match the commonly cited formula. A high-traffic proxy on small nodes can exhaust it, and the symptoms are connection resets and timeouts, so conntrack use needs its own metric and alert.

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