Cases6 cases

1 to 5 of 6

1. IL-0246 New pods on Adyen's big data Kubernetes nodes could not start, failing with "Cilium API client timeout exceeded"

   Adyen2026

   Symptoms

   On Adyen's production big data Kubernetes clusters, new pods on some nodes could not start because setting up their network through Cilium timed out. Once one pod had timed out, every other pod trying to start on the same node timed out as well.

   Pods stuck in ContainerCreating

   Trigger

   Heavy data workloads landed on nodes where the interval of Cilium's periodic garbage collection of expired connection tracking entries had grown, during a quiet period, toward its 12-hour maximum.

   Root cause

   Configuration change

   Component

   Cilium

   Contributing factor

   Change with a delayed effectUnreviewed defaultsRetry stormNo alert on limit

   Remediation

   • Set a fixed connection tracking garbage collection interval, conntrackGCInterval: 60s, and rolled it out to the Cilium DaemonSet

   Action items

   • Alert on the connection tracking garbage collection duration and table size metrics

   Lessons

   Scaling parameters can interact with other logic months later as traffic grows: the larger table that solved capacity limits on 512GB nodes interacted with the garbage collection auto-scaling on the 2TB nodes. Logs only showed symptoms, so profiling and tracing across the container runtime, the CNI plugin, the Cilium agent and the kernel were needed, and simple arithmetic with measured numbers pointed at the cause early. Auto-scaling algorithms need bounds, and the 12-hour maximum interval was too long for this workload. A timeout protects the caller but does not cancel the work behind it. Adyen recommends that Cilium deployments with dynamic workloads alert on cilium_datapath_conntrack_gc_duration_seconds and cilium_datapath_conntrack_gc_entries and set conntrackGCInterval: 60s.

   View case
2. IL-0499 Discord voice and video calls hung at Awaiting Endpoint for three hours after 17% of sessions stopped at once

   Discord2026

   Symptoms

   From 12:13 to 15:30 PDT on 25 March 2026, voice and video on Discord were heavily degraded. Users mostly could not start or join calls and saw "Awaiting Endpoint" in their call status.

   Service outage

   Trigger

   A routine change to tune the sessions service cluster on Kubernetes gave each pod more CPU and memory and lowered the pod count in proportion. When it was deployed to the first zone at 12:13 PDT, Kubernetes terminated 50% of that zone's pods, and the termination grace period ran out before the sessions could be handed off.

   Root cause

   Configuration change

   Component

   Pod terminationCoordination and key-value storeDatabase proxy and connection pooler

   Contributing factor

   Retry stormUnknown limit

   Remediation

   • Set low syncer spawn rate limits in the calls, streams and guilds services and restarted the voice syncers cluster
   • Restarted voice syncers instances one at a time, and four of the first five recovered fully
   • Brought 15 new voice syncers instances online, doubling capacity and halving the syncers per instance
   • Restarted the last backed-up voice syncers instance, leaving the doubled cluster fully healthy

   Action items

   • Add a validating admission webhook that rejects a scale-down of Elixir workloads until each pod has handed off its processes
   • Replace the Holster.Pool supervisor with a PartitionSupervisor so outgoing connections are created and checked out concurrently
   • Move gun connection process lifecycle management into Holster.Pool so the gun connection supervisor is no longer used
   • Tune the upstream rate limits that call into voice syncers, with load shedding tooling that can force them
   • Add rate limits on endpoint selection in voice syncers to limit outbound connection creation
   • Monitor the HTTP connection pooling mailboxes
   • Review and expand instrumentation and logging for service discovery announcement and voice syncer RPCs to SFUs
   • Monitor the most critical processes across all services instead of aggregate metrics such as overall mailbox health
   • Bring more workloads into Kubernetes so capacity can be scaled with a single command instead of provisioning VMs by hand
   • Re-architect the A/V system to scale its control plane services horizontally across multiple regions

   Lessons

   Discord says a large enough traffic spike will find a bottleneck somewhere; in earlier large-load incidents its ScyllaDB databases limited recovery, and this time the bottleneck moved to the voice services. Facing a capacity constraint, the team asks whether to increase supply, such as adding services, or reduce demand, such as rate limiting inbound traffic. During an incident it matters to know the toolbox, and Elixir and the BEAM give engineers many introspection options. Any slowdown in the hot loop of a single-threaded process can degrade both the service and the user experience.

   View case
3. IL-0063 VPN outage after recreating a Redis StatefulSet restarted the whole Redis cluster without readiness checks

   AdGuard VPN2025

   Symptoms

   The day began with an alert that several instances of the Redis cluster were running out of disk space. That part was fixed quickly. The outage came an hour later: right after the Redis StatefulSet was deleted and recreated at 8:10 UTC, Kubernetes restarted every Redis pod within about five minutes, and problems started to appear.

   Service outageOOMKilledProbe failuresHigh latency

   Trigger

   To make Git match the volumes that had been resized by hand, the Redis StatefulSet was deleted with orphan (non-cascading) deletion and recreated with the new storage template; Kubernetes reconciled the new spec by restarting the entire Redis cluster.

   Root cause

   Configuration change

   Component

   Persistent volumes and stateful setsIn-memory cacheContainer memory limit

   Contributing factor

   No health probesUnverified assumptionSingle point of failureRetry stormNo headroom

   Detection

   An alert about Redis instances running out of disk space started the work; the outage itself showed up as backend errors about Redis connections right after the StatefulSet was recreated.

   Remediation

   • made the Redis masters forget obsolete node identities, reset the affected replicas and rejoined them, then waited for replication to catch up
   • identified the component that was actually running out of memory, scaled the backend service and raised memory limits for that component
   • temporarily relaxed probes so backend instances took traffic immediately instead of flapping between ready and not ready
   • reverted the temporary workarounds at 10:00 UTC

   Action items

   • Add startup probes so a Redis pod is not marked ready until its dataset is loaded
   • Build an own control plane for Redis that handles restarted pods stuck to an old master address
   • Reduce dependence on the single Redis cluster: move some important data to other stores, such as a separate Redis cluster per server, and use Kafka for some backend components

   Lessons

   The disk resize was not the problem; the cleanup afterwards was. An immutable field pushes operators toward deleting and recreating the controller, and that can set off a full reconcile. Startup and readiness probes are what slow a rolling restart down to a safe pace; without them a distributed store restarts in the most fragile way. Recovery plans must expect a cluster to heal slowly, and dependent services need to degrade gracefully while it does.

   View case
4. 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 Plus2022

   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.

   View case
5. 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.

   View case

By root cause1