Incident Library
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  • Root cause
  • Component
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Cases7 cases

6 to 7 of 7

  1. 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.

    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
    Component
    Contributing factor
    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.

  2. Symptoms

    On 2022-04-25 the Sidekiq Apdex (the share of background jobs that finish within a target time) dropped, and an engineer declared an incident in Slack at 15:13 UTC. Users saw intermittent slowness across GitLab.com, and asynchronous work such as pipeline creation and import and export took unusually long.

    Trigger

    The Consul agent in GitLab.com's GKE pods had memory demand spikes that did not fit in the pods' 500MB memory limit, and the agent was killed again and again.

    Root cause
    Component
    Contributing factor
    –
    Detection

    An engineer declared the incident in Slack at 15:13 UTC after the Sidekiq Apdex dropped; the second event was found when monitoring detected an elevated error rate at 01:21 UTC on 2022-04-26.

    Remediation
    • planned at 16:13 to raise the per-user connection limit for the gitlab database user and the pgbouncer backend pools for the main database; changes were applied at 17:26 and confirmed at 17:47
    • raised the pod memory limits from 500MB to 1GB so the Consul agents survive memory spikes
    Action items
    • Monitor the Consul agents on GKE pods to see whether the 1GB memory limit keeps them healthy
    • Investigate the Consul memory demand spikes and what can be done beyond raising the hard memory limit
    Lessons

    When the local Consul agent that Rails uses for database service discovery keeps dying, Rails does not fail; it sends every query to the last known primary. What engineers saw was database saturation and slow background jobs, which pointed the investigation first at a recent pgbouncer pool change. The memory limit of the Consul agent in every pod therefore decided the load on the primary database.

Check your cluster for this

These 7 cases involve Application database and In-memory cache. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause4

Capacity exhaustion4 cases

  1. IL-0100 PostHog's feature flags pods were packed onto Kubernetes nodes that were too small for their CPU requests, and CPU saturation above 90% caused three outages in ten days through Redis overload, connection pool exhaustion and slow queries
  2. IL-0202 A burst of queries and database writes exhausted connection pools and memory on Honeycomb's ingest hosts, and Kubernetes crash-loop back-off kept failed hosts offline so ingest capacity stayed too low to recover
  3. IL-0194 After a kube-apiserver restart, pod LIST requests from every pod of a Vector DaemonSet nearly tripled etcd memory and restarted all master nodes
    Palark2023
  4. IL-0206 Consul agents in GitLab.com's GKE pods were repeatedly OOM-killed, so the Rails pods lost database replica discovery and sent every query to the primary
    GitLab2022

Breaking change in an upgrade1 case

Organisation
  1. IL-0117 A scheduled maintenance and an ingress upgrade on OpenAI's user-facing clusters caused a networking control plane regression that briefly broke the data plane, and the services that restarted then overwhelmed a backend persistence store with a heavy first-start query
    OpenAI2024

Software defect1 case

Organisation
  1. IL-0024 Expensive cache-backed API calls and uncancelled database requests overloaded MongoDB and took the Hugging Face Hub down three times

Configuration change1 case

Organisation
  1. 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