Cases46 cases

1 to 5 of 46

1. IL-0179 With DEBUG logging and synchronous log output, a high-traffic service filled the 64 KB stdout pipe, so request threads blocked in write() while holding database connections and HikariCP ran dry, failing requests in 30-second bursts

   MUSINSA2026

   Symptoms

   The on-call engineer for a high-traffic service was alerted that requests were failing in large batches every 30 seconds.

   High error rateIntermittent timeoutsConnection pool exhaustion

   Trigger

   DEBUG level logging was on in production when traffic surged, raising log volume to about 100 times normal while the service logged synchronously.

   Root cause

   Configuration change

   Component

   Application logging libraryContainer runtimeTelemetry agentDatabase

   Contributing factor

   Unverified assumptionExcessive blast radius

   Detection

   The on-call engineer was alerted that requests were failing in large batches every 30 seconds.

   Action items

   • Replace synchronous logging with TraceAwareAsyncAppender, which captures trace_id and span_id on the calling thread and drops logs instead of blocking when the queue is full (neverBlock=true)
   • Keep the amount of log output at a sustainable level, since an asynchronous queue still fills under sustained overload

   Lessons

   Removing AsyncAppender to keep trace IDs also removed the protection that kept request threads away from stdout back-pressure. A company-wide standard applies the same side effect to dozens of services, so check what a standard rests on and what working behaviour it takes away. ThreadLocal context does not cross into an asynchronous worker, but capturing it on the calling thread before handing the event off keeps both the IDs and the asynchronous output. Under extreme load, dropping log lines is preferable to stopping request handling.

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2. 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.

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3. IL-0512 xpro.mit.edu returned 503 for an hour when its Kubernetes/APISIX origin certificate expired after renewal failed

   MIT Open Learning2026sev1

   Symptoms

   At 3:38 PM EDT on 3 June 2026, alerts fired because both the xPRO production CMS and the main xPRO site at https://xpro.mit.edu were returning 503 errors. Fastly, in front of the site, could not connect to the Kubernetes/APISIX origin, because the origin certificate for xpro-web.odl.mit.edu had expired at 3:29 PM EDT.

   Service outageTLS certificate errors

   Trigger

   The origin certificate xpro-cert for xpro-web.odl.mit.edu, issued on 2026-03-05 with a 90-day validity period, expired at 3:29 PM EDT on 3 June 2026.

   Root cause

   Configuration change

   Component

   cert-managerCDN and edge networkAuthoritative DNS servers and records

   Contributing factor

   No configuration testsMonitoring blind spotChange with a delayed effect

   Detection

   Alerts for the xPRO production CMS and the main xPRO site fired at 3:38 PM EDT on the 503 errors, and a Rootly incident was created at 4:08 PM EDT.

   Remediation

   • Deleted and recreated the stale cert-manager certificate resources so that cert-manager issued a fresh origin certificate

   Action items

   • Remove the backend origin domain from the non-OpenEdX xPRO Fastly TLS subscription, so Fastly manages only xpro.mit.edu
   • Deploy the Pulumi update for the xPRO application in Production
   • Trigger cert-manager renewal of the xPRO certificate after the conflicting Fastly validation CNAME is removed
   • Consider tests or policy checks that keep cert-manager-managed origin domains out of Fastly TLS subscriptions
   • Consider alerting earlier on failed cert-manager CertificateRequests and Orders, so stale ACME failures are found before the certificate expires

   Lessons

   Reading the outage as a failed cert-manager ACME renewal was true but incomplete; the missing part was that Fastly had been set to manage validation for a backend origin domain that belonged to cert-manager. The team concluded that TLS certificates and DNS validation records need guardrails around ownership, and that public Fastly frontend domains and Kubernetes/APISIX origin domains must not be treated as interchangeable service domains in TLS automation.

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4. 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.

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5. IL-0200 Newly provisioned Kubernetes nodes ran an incompatible etcd version and broke cluster consensus in several GitHub production clusters, causing 5XX errors on Git operations and page loads

   GitHub2026

   Symptoms

   From 01:36 UTC on 12 March 2026, GitHub.com returned elevated error rates for Git operations, web requests and related services. At 01:54 UTC the GitHub status page said it was investigating reports of impacted performance for some services.

   High error rate

   Trigger

   During a planned infrastructure upgrade, a configuration issue made newly provisioned Kubernetes nodes run an incompatible version of etcd.

   Root cause

   Configuration change

   Component

   etcd

   Contributing factor

   Monitoring blind spot

   Detection

   The status page opened the incident at 01:54 UTC, 18 minutes after errors began, citing reports of impacted performance.

   Remediation

   • paused deployments for the duration of the incident
   • identified the newly provisioned nodes running the incompatible etcd version and removed them, which restored cluster consensus
   • ran a validation deploy that confirmed all systems were healthy before resuming normal operations

   Action items

   • Enforce version compatibility programmatically during node replacements
   • Add monitoring that detects split-brain conditions earlier
   • Update the recovery tooling to reduce restoration time

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