Incident Library
Applied filters ComponentDatabase replicationSymptomDatabase overloadFactorNo headroomClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases2 cases

1 to 2 of 2

  1. Symptoms

    From 17:03 UTC on January 27, 2026, a small subset of Intercom customers, fewer than 1%, saw inconsistent latency and stale data when reading from the platform. At 17:25 UTC an alarm on an excessive message backlog in a worker declared an incident automatically.

    Trigger

    An internal app deletion process, running more concurrent deletion steps per app than usual with no rate limiting, and the ETL data pipeline both put heavy load on the same database shard at the same time.

    Root cause
    Component
    Contributing factor
    Detection

    An alarm on an excessive message backlog in a worker fired at 17:25 UTC and declared an incident automatically.

    Remediation
    • Disabled ETL processing to reduce load on the affected shard
    • Scaled the app deletion workers to zero
    • Re-enabled ETL carefully once monitoring showed stable metrics
    Action items
    • Increase the capacity of shards to leave headroom for unexpected load spikes
    • Add rate limiting and resource controls to the app deletion process so it backs off when database load is high
    • Review how background work such as ETL and maintenance tasks competes with customer-facing operations for database capacity
    • Alert on replication lag earlier and link it to specific workloads
    • Communicate proactively with affected customers in incidents with a limited blast radius
    Lessons

    Because data is spread across many independent shards, the overload stayed on one shard and reached fewer than 1% of customers instead of the whole platform.

  2. Symptoms

    On 2 November 2020 the Cloudflare API and dashboard were degraded for six hours and 33 minutes. The success rate of API queries dropped at times to 75%, and the dashboard was up to 80 times slower than normal, while Cloudflare's edge network kept working.

    Trigger

    At 14:43 UTC a network switch in a control plane data center partly failed: it kept LACP and BGP running but stopped forwarding some packets, and it recovered on its own six minutes later.

    Root cause
    Component
    Contributing factor
    Detection

    At 14:43 UTC alerts fired because the misbehaving switch was unreachable to pings. Engineers then saw that the primary authentication database was overwhelmed.

    Remediation
    • Shed load from the primary authentication database by slowing SSL certificate pushes to the edge, emails and other features
    • Moved API traffic that could use read replicas to the secondary data center by hand
    • Sent authentication calls fully back to the primary data center when the dashboard got worse
    • Rebuilt the first database replica, which put itself back into service at 21:20 UTC and returned performance to normal
    • Ramped the turned-down services back up so asynchronous processing could catch up
    Action items
    • Remove the cluster management limitation that requires rebuilding all replicas after a primary is promoted
    • Redesign the user sessions system so dashboard traffic can be steered between data centers
    • Change the auto-remediation configuration so a database replica is not promoted so quickly
    • Tune each system involved to be more resilient to failures of its dependencies
    Lessons

    Every system in the chain had redundancy and none failed completely; each only degraded, which made the chain of events much harder to model and foresee. Automating replica promotion so that it could trigger on a minute's notice had been a point of pride, but for at least one database a fast promotion can do more harm than the failure it answers. Most general-purpose cluster managers use Raft or Paxos rather than Byzantine fault tolerant protocols, accepting a rare failure mode in exchange for a protocol that is simpler to implement correctly and debug.

Check your cluster for this

These 2 cases involve Database and Database replication. 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 cause2