Incident Library
Applied filters SymptomWrites rejectedFactorRetry stormClear 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 05:35 UTC on 4 February 2019 Mandrill, Mailchimp's transactional email service, sent only 80% of queued emails, because one of its PostgreSQL shards, shard4, stopped accepting writes. When Mandrill engineers opened an investigation at 11:58 UTC, they saw a sharply elevated load on shard4.

    Trigger

    At 05:35 UTC on 4 February the transaction ID counter of shard4, the busiest Mandrill PostgreSQL shard, reached its upper limit and PostgreSQL shut the database down to protect against wraparound.

    Root cause
    Component
    Contributing factor
    Detection

    The first exception was logged overnight but was buried by unrelated exceptions in the centralized error reporting. Mandrill engineers opened an investigation at 11:58 UTC and, while looking for the source of the rising load on shard4, found the wraparound at 12:56 UTC.

    Remediation
    • Put shard4 into standalone mode and started VACUUM at 14:16 UTC on 4 February
    • Stopped and restarted the vacuum with settings that made it run faster
    • Started a dump and restore of the database without the Search and Url tables while the vacuum ran
    • Replaced storage volumes on the Mandrill app servers whose disks were filling with queued jobs and logs
    • Moved the job-queue tables from shard4 to other live shards
    • Truncated the Search and Url tables on the locked database at 19:12 UTC on 5 February, after which the vacuum finished in about an hour
    • Started sending from the backlog at 21:36 UTC
    • Added alerting for XID wraparound by 22:40 UTC
    Lessons

    Mailchimp named the factors that slowed its response: knowledge of and access to Mandrill systems and monitoring rested with a few people, Mandrill logging needed a locally writable disk, logs of malformed API requests were hard to separate from real application errors, job health was hard to see, and the disk space problem made partial deployments for triage risky. What helped was trained incident commanders with clear roles (incident commanders in 3-hour rotations, scribes, technical liaisons and points of contact between teams), periodic summaries with a list of recent and open decisions, and taking time in a video meeting to reassess, which led to the truncation. Running in the cloud let the team expand storage quickly, and the team was lucky that the largest table holding up the vacuum held data it could delete.

  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.

Check your cluster for this

These 2 cases involve PostgreSQL vacuum 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 cause2