Cases2 cases

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1. IL-0316 Railway's control plane slowed and deployments stopped after a PgBouncer version jump used abnormal CPU and memory

   Railway2025

   Symptoms

   At 11:48 UTC on 22 September 2025, minutes after Railway had resolved a dashboard outage, its control plane showed abnormal resource consumption and elevated API latency. A large backlog of deployments queued during the first outage had started all at once, and the control plane began returning elevated database errors.

   High latencyIntermittent timeoutsDeploys failing

   Trigger

   After a dashboard outage caused by a schema change was fixed, a large backlog of queued deployments started at the same time and put the control plane and its database, behind a newly upgraded PgBouncer, under heavy load.

   Root cause

   Breaking change in an upgrade

   Component

   DatabaseDatabase proxy and connection pooler

   Contributing factor

   Unpinned versionNo staged rolloutMonitoring blind spotUnreviewed defaults

   Detection

   Users reported at 11:05 UTC that the project canvas failed to load; the control plane's abnormal resource consumption and elevated API latency were seen at 11:48 UTC and opened as a new incident.

   Remediation

   • Deployed a fix for the API failure caused by the schema change within 15 minutes
   • Suspended deployments for non-Pro users so Pro users could deploy and the queue could drain
   • Suspended all deployments, Pro included, for up to 20 minutes during peak instability
   • Scaled up the control plane database's CPU, memory, connection limits and IOPS
   • Rolled PgBouncer back to the previous stable version, which brought all metrics back to nominal
   • Re-enabled deployments for all non-Pro users
   • Fixed the edge case in which private networks and their endpoints were missing from the dashboard

   Action items

   • Re-engineer parts of the control plane to be more resilient, moving large parts of its storage layer away from Postgres
   • Add CI validation that keeps disruptive schema changes out of production and automated schema compatibility checks before backend deployments
   • Monitor and alert on PgBouncer node CPU, memory and connection pool utilization
   • Upgrade PgBouncer in phases, instance by instance, instead of everywhere at once

   Lessons

   Railway believes that without the breaking schema change reaching production the cascade would not have happened, that monitoring PgBouncer's own CPU, memory and pool metrics would have shown the performance regression earlier and shortened recovery, and that upgrading PgBouncer instances one at a time would have exposed the version-specific problem before it reached every instance.

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2. IL-0498 Clerk's Postgres database had load spikes every 15 minutes and requests failed and slowed intermittently for four days

   Clerk2025

   Symptoms

   At 13:08 UTC on 15 September 2025, Clerk's internal monitoring alerted on significant request failures and increased latency. Over the following days the request failures and latency spikes kept coming back while the Postgres database stayed unhealthy, with repeated spikes in database load.

   High error rateHigh latencyDatabase overloadConnection pool exhaustion

   Trigger

   At 05:30 UTC on 14 September 2025 the cloud provider automatically upgraded Clerk's Postgres database to a new minor version, which changed how Postgres handled connection locks.

   Root cause

   Breaking change in an upgrade

   Component

   DatabaseDatabase proxy and connection pooler

   Contributing factor

   Unpinned versionRetry stormMonitoring blind spotOverlapping failuresHarmful manual action

   Detection

   Internal monitoring alerted on significant request failures and increased latency at 13:08 UTC on 15 September. Shortly after the upgrade on 14 September it had already shown an increased but still acceptable database load.

   Remediation

   • Optimised several expensive queries, refined critical indexes and re-indexed the database
   • Blocked abusive traffic more aggressively for a time
   • Performed a manual minor version upgrade and increased database capacity
   • Added jitter to the connection pooling configuration so connections no longer recycled in step

   Action items

   • Evaluate other database providers that give more control over upgrades and downgrades
   • Isolate more services from each other, for example Sign Up and Sign In infrastructure from the rest of the system
   • Keep optimising the most costly database queries
   • Evaluate sharding and multi-tenant infrastructure to isolate one application from others

   Lessons

   Clerk's review found that connection metrics sampled every 60 seconds could not show a recycling pattern that lasted seconds and repeated every 15 minutes, that an attack and background jobs with similar periods pulled attention away from the database layer, that the Backend API looked healthy only because it manages far fewer connections, and that the release freeze removed the staggering of connection creation that normal deploys provide.

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