Cases2 cases

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1. IL-0281 PostHog's Logs ClickHouse cluster silently deleted almost all its S3 data, losing US logs older than 3 days

   PostHog2026

   Symptoms

   On 19 February 2026, a node of the ClickHouse cluster behind PostHog's Logs product crashed, restarted and could not start again because it could not find a large amount of its data. Engineers then found that almost all of the Logs data stored on S3 was gone, so logs collected in the US region more than 3 days earlier were lost. Only the Logs product was affected.

   Data loss

   Trigger

   At 10:54 UTC a routine mutation was run to materialise an index. When it finished at 11:02, it set off a bug in ClickHouse's zero-copy replication.

   Root cause

   Software defect

   Component

   DatabaseDatabase replicationObject storageDatabase backups and snapshots

   Contributing factor

   Monitoring blind spotSingle point of failureUntested backup

   Detection

   No automated alarm fired. At 19:40 UTC a node in the cluster crashed, restarted and failed to start because of the missing data, and the engineers who investigated found that most of the S3-backed data was gone.

   Remediation

   • Switched Logs to a new table without zero-copy replication and caught up on recent messages
   • Backfilled the Logs data from the 3 days of Kafka history

   Action items

   • Disable zero-copy replication on all clusters
   • Audit the whole Logs ClickHouse configuration and keep experimental features out of production
   • Enable S3 versioning on the storage buckets so objects deleted by a database bug can be recovered
   • Spot-check configurations and data integrity strategies for single points of failure before a product becomes generally available

   Lessons

   Running Logs in its own cluster kept every other product unaffected, and 3 days of Kafka retention saved the recent data. An experimental setting chosen for an early internal stage was allowed to stay in production. Monitoring covered only incoming and recent data, so petabytes were deleted over 8 hours without an alarm. Relying on database replication alone over shared storage was a single point of failure, and S3 versioning would have let the deleted files be recovered.

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2. IL-0218 GitLab.com's primary PostgreSQL data was wiped by mistake and, with no working backup, the site was down about 18 hours

   GitLab2017

   Symptoms

   From around 19:00 UTC on 31 January 2017, load on GitLab.com's PostgreSQL database rose, which GitLab suspected was spam, and many users could not post comments on issues and merge requests. Around 23:00 UTC the replication of the PostgreSQL secondary fell behind and then failed, because WAL segments it still needed had already been removed from the primary.

   Database overloadReplication lagData lossService outage

   Trigger

   While trying to restore replication to the secondary, an engineer ran the removal of the PostgreSQL data directory on the primary, db1.cluster.gitlab.com, believing it was the secondary.

   Root cause

   Operator error

   Component

   DatabaseDatabase replicationDatabase backups and snapshotsCloud block storage

   Contributing factor

   Untested backupSingle point of failureNo runbookPages not deliveredUnverified assumptionUnreviewed defaults

   Detection

   The engineer who ran the deletion on the primary noticed the mistake and stopped it a second or two later.

   Remediation

   • Raised max_wal_senders from 3 to 32 and lowered max_connections from 8000 to 2000 so PostgreSQL would restart
   • Stopped the deletion on the primary a second or two after noticing it
   • Restored the database from the LVM snapshot taken about 6 hours before the outage by copying the PostgreSQL data directory from staging
   • Restored the webhooks from a separate database built from the snapshot and imported them as a SQL dump
   • Incremented all database sequences by 100,000 so IDs used before the outage could not be reused
   • Re-enabled GitLab.com gradually
   • Rebuilt projects created after 17:20 UTC in basic form from their Git repositories on the NFS cluster

   Action items

   • Change the shell prompt (PS1) on all hosts to show more clearly which host and environment is in use
   • Monitor backups with Prometheus
   • Set PostgreSQL's max_connections to a sane value
   • Investigate point-in-time recovery and continuous archiving for PostgreSQL
   • Take LVM snapshots of the production databases every hour
   • Take Azure disk snapshots of the production databases
   • Move staging to the ARM environment
   • Recover the production replicas
   • Test recovery of PostgreSQL database backups automatically
   • Improve the PostgreSQL replication documentation and runbooks
   • Investigate pgbarman for PostgreSQL backups
   • Investigate WAL-E for database backup and realtime replication
   • Build a streaming database restore
   • Assign an owner for data durability
   • Set up multiple secondaries and balance load among them with pgpool-II
   • Provide a tool for developers to run and revert Rails migrations on staging
   • Build owned recovery procedures for the rest of the GitLab.com infrastructure, not only the database
   • Publish a backup monitoring dashboard and add more backup data to it
   • Improve the abuse reporting and response system so removal for spam does not hard delete
   • Redact engineers' names in future public incident documents

   Lessons

   GitLab split the incident into two problems: GitLab.com went down because the primary's data directory was removed by mistake during a manual, undocumented replication rebuild, and recovery took over 18 hours because the backups had failed silently, disk snapshots were not enabled and the only copy sat on slow staging disks. The backup procedure was never tested because no one owned it. GitLab chose to focus on fast, regularly practised recovery and on making it obvious which host an engineer is on, rather than on blocking commands, since a safer rm only protects against one of many ways to lose data.

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