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

Cases3 cases

1 to 3 of 3

  1. 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.

  2. Symptoms

    At 2:39 AM PDT (9:39 UTC) on 18 July 2013, services that relied on the redis-master of Twilio's billing system began to fail because the load on its host had become extreme. At 2:42 AM PDT monitoring alerted the on-call engineers to a failure in the Redis cluster.

    Trigger

    At 1:35 AM PDT on 18 July a loss of network connectivity disconnected all billing redis-slaves from the redis-master at once, and all of them requested a full synchronization at the same time. On-call engineers then restarted the overloaded redis-master.

    Root cause
    Component
    Contributing factor
    Detection

    At 2:42 AM PDT monitoring alerted the on-call engineers to a failure in the Redis cluster. At 3:28 AM PDT the billing system monitoring reported the anomalous charges, and at 12:36 PM PDT monitoring detected the recurrence.

    Remediation
    • Restarted the redis-master to relieve the high load, which loaded a wrong configuration
    • Took the billing system offline to stop further credit card charges
    • Restored service to all suspended accounts
    • Restored the lost account balances from the independent double-bookkeeping record in the relational datastore
    • Took billing offline again after the recurrence and reactivated the newly suspended accounts
    • Refunded all erroneous credit card charges
    • Gave all affected accounts a credit of 10% of their last 30 days of spend
    • Replaced the original Redis cluster and corrected the redis-master configuration
    • Activated the billing system progressively for groups of customer accounts
    Action items
    • Disable Redis restarts on the redis-master and recover the master by pivoting a slave instead
    • Add fail-safes so the billing system neither suspends accounts nor charges cards when balances are missing or cannot be written
    • Validate the billing system against the double-bookkeeping databases in real time
    Lessons

    Losing the in-flight balances and the ability to write balances at the same time exposed a flaw in the auto-recharge system: it failed in a dangerous way, charging cards and suspending accounts instead of stopping.

  3. Symptoms

    On Monday, September 10th, 2012, during a schema migration, the health checks on GitHub's MySQL master failed and Percona Replication Manager moved the 'active' role to another node of the new three-node cluster. That node's InnoDB buffer pool was cold and it performed poorly, its health checks failed in turn, and the role failed back to the original server. GitHub.com went down.

    Trigger

    A schema migration on Monday, September 10th put more load on the master database than earlier migrations had, and Percona Replication Manager's health checks on the master failed.

    Root cause
    Component
    Contributing factor
    Detection

    On the morning of September 11th, a developer told the operations team that the 'standby' node was returning incorrect query results.

    Remediation
    • Enabled Pacemaker's maintenance-mode so no health checks or automatic failovers ran, and let the buffer pool warm
    • Powered off the out-of-date node 'c' to end the partition
    • Stopped Pacemaker and Heartbeat on nodes 'a' and 'b' and started them on node 'a' only
    • Started MySQL on node 'a' in the active role
    • Removed the events leaked to wrong dashboards and audited the wrongly routed repositories
    • Contacted the owners of the exposed private repositories
    Action items
    • Change the Pacemaker configuration so the active database role fails over only when an operations engineer starts it
    • Find a way to warm the InnoDB buffer pool of slave databases so failovers do not hurt performance
    • Audit the Pacemaker and Heartbeat stack, focusing on the code path behind the segfault
    • Run hardware tests on the server where the segfault happened
    Lessons

    GitHub concluded that automated failover is not the right strategy for its primary production database: for every failover in this incident, any member of the operations team would have said it should not happen. Failovers that must happen, in an emergency or during maintenance, should not hurt performance.

Check your cluster for this

These 3 cases involve Database replication and Database. 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.

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