Cases3 cases

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1. IL-0552 CircleCI's archival database ran out of storage, slowing workflow and job starts and the display of workflows in the UI

   CircleCI2025

   Symptoms

   At about 23:00 UTC on 21 January 2025, an automated alert reported that the CircleCI database instance holding archived data was almost out of free storage space. From 23:50 UTC customers saw slow starts and cancellations of workflows and jobs, and delays and difficulty viewing workflows in the CircleCI UI, although pipelines for a specific project could still be viewed.

   High latencyIntermittent timeoutsLog floodNode disk fullCloud API rate limit exhausted

   Trigger

   A code change to a function in the archival database on 16 January 2025 unintentionally made it write an excessive number of log messages, and the database filled its storage.

   Root cause

   Faulty deployment

   Component

   DatabaseCI system

   Contributing factor

   Change with a delayed effectExcessive blast radiusOverlapping failures

   Detection

   An automated alert at about 23:00 UTC warned that the archival database was almost out of free storage, before customers were affected. The growing workflows queue was not linked to it at first because a separate alert about request volume fired at about the same time.

   Remediation

   • Scaled up the event consumer that processes the workflows queue at 23:44 UTC
   • Promoted a read replica of the archival database to a standalone primary at 23:55 UTC

   Action items

   • Fix the database function so it no longer writes an excessive number of log messages
   • Add a max duration to the workflows retry policy for archiving so it fails earlier than the default timeout
   • Move workflow archival to an event-based model that decouples it from the workflows service
   • Add forecast and anomaly monitoring for databases that alerts on unusual activity before it reaches critical levels

   Lessons

   The storage alert on the archival database did fire, but the database filled much faster than forecast, so there was little time to act before customers were affected. Because the workflows service called the archival service synchronously, a problem in the archival database slowed the whole workflows service.

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2. IL-0571 STORES reservation returned bursts of 504 errors when a smart-list query held a database process for over 20 minutes

   STORES2024

   Symptoms

   About 20 minutes into a batch that rewrote the preset smart-list data of STORES 予約 (STORES reservation), an alert fired for a sudden rise in 504 errors (Gateway Timeout). The work had started a little after 03:00 UTC, and the metrics watched during it, such as web server response latency and the load of the writer database, had shown no large change.

   High error rateDatabase overload

   Trigger

   The preset smart lists 初回予約の顧客 (first-reservation customers) and 要フォロー顧客 (customers needing follow-up), created more than a month earlier, were rewritten with new search parameters after the search specification changed, which switched them onto the new search query.

   Root cause

   Faulty deployment

   Component

   Database

   Contributing factor

   Inefficient queryChange with a delayed effectUnrepresentative stagingMonitoring blind spotUnverified assumption

   Detection

   An alert on a sudden increase in 504 errors (Gateway Timeout), about 20 minutes after the preset rewrite batch started.

   Action items

   • Rework the database design so the inline-view search logic is no longer used
   • Add a test that checks this API's EXPLAIN output for scans larger than expected
   • Provide an environment where the timing of this logic can be measured easily

   Lessons

   Rushing to meet the schedule led to both a failure that affected users and a later release. In a multi-tenant database an EXPLAIN that shows index use can still hide large scans, tests need the case where one query is fast and the next is slow, the metrics to watch during a data change are those of the instance that serves the affected queries, and metrics sent at the end of a request are lost for requests that never finish.

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3. IL-0483 Replicate's website and API returned slow responses and HTTP 500s for two hours as PostgreSQL connections ran out

   Replicate2023

   Symptoms

   From 05:45 UTC on 11 May 2023, for about two hours, many Replicate customers got slow responses or HTTP 500 errors from the API and the replicate.com website and had trouble running predictions. Monitoring paged an engineer at 05:46 UTC, a minute after the database connection pool became fully saturated.

   High error rateHigh latencyLock contention or deadlock

   Trigger

   A little after 05:00 UTC on 11 May, normal variations in traffic pushed the stacking INSERT queries past their tipping point.

   Root cause

   Faulty deployment

   Component

   Database

   Contributing factor

   Change with a delayed effect

   Detection

   Monitoring detected the saturated database connection pool almost immediately and paged an engineer at 05:46 UTC.

   Remediation

   • Switched off all asynchronous prediction update features with a feature flag at 07:31 UTC, after which the database recovered

   Action items

   • Keep the asynchronous prediction update feature disabled and redesign it so it no longer sends stacked INSERTs
   • Review lock contention and other database hotspots that could cause similar problems
   • Publish detailed reports after major incidents

   Lessons

   The system ran in a degraded state that looked successful until it tipped into a full failure. The same asynchronous update work that triggered the outage also partly protected customers who used webhooks, and the stacked INSERTs came directly from a latency improvement: removing 100-150ms brought two updates of one prediction to the database almost together.

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