Cases2 cases
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IL-0553CircleCI's orchestration database filled its transaction log volume, and no workflows or jobs started for 50 minutesCircleCI2026- Symptoms
On 6 October 2026 CircleCI pipelines were slow to be created and workflows and jobs were slow to start, in short bursts from 13:30 UTC and continuously from 15:30 UTC. From 15:48 to 16:38 UTC no workflows or jobs started at all, and pipelines triggered from 16:02 UTC failed.
- Trigger
Around 12:40 UTC, on top of the regular workload, anti-wraparound autovacuum runs on several of the largest tables of the orchestration service's database began writing transaction logs faster than the database could archive them.
- Root cause
- Component
- Contributing factor
- Detection
Monitoring raised short alerts about errors in the orchestration service from 10:02 UTC, each clearing on its own. At 13:35 the alerts came back together with related alerts from several other services, and after they returned around 14:30 and engineers investigated further, an incident was declared at 14:54 UTC.
- Remediation
- Changed the anti-wraparound autovacuum settings to help it finish faster
- Moved the transaction logs onto the database's main storage volume, which took the database offline from 15:47 to 16:38 UTC
- Changed database parameters to stop further maintenance runs from starting
- Changed a database setting at 18:19 UTC to cut the time each write spent waiting on storage
- Added database and server capacity to the systems that hand jobs to the execution fleet to clear the backlog faster
- Action items
- Alert on how full the transaction log volume is and on how far archiving has fallen behind
- Alert on the database maintenance that drives transaction log growth
- Review all alerts so that noisy or sensitive alerts do not hide real issues
- Tune how often and how aggressively autovacuum runs on the database
- Track the size of the largest tables over time so they stay within safe limits
- Remove the single transaction log bottleneck by splitting the service across several database instances or moving it to a distributed database
- Make CircleCI's systems wait for the orchestration service to recover instead of failing jobs after retrying
- Include specific impact and timing sooner in status page updates during long incidents
- Lessons
CircleCI says the combination of alerts should have been recognised sooner: brief error alerts that cleared on their own were treated as routine, and nothing alerted on the transaction log volume or on archiving lag. Because every write of the orchestration service went through one database and one transaction log, a backlog in that log slowed every pipeline, workflow and job.
- Symptoms
On 30 May 2019, in the run-up to the Kubernetes 1.15 code freeze, Prow test jobs in the k8s-prow-build cluster failed in surprising ways or were aborted partway through. Jobs were reported to GitHub as failed while Deck still showed them as running, because pods exited without uploading `finished.json`, the file most Prow tooling uses to tell a job's state.
- Trigger
A spike in test load before the Kubernetes 1.15 code freeze pushed disk I/O on the build nodes far beyond the IOPS that GCP allows for 250 GB disks.
- Root cause
- Component
- Contributing factor
- Detection
Several users reported jobs that GitHub showed as failed but Deck showed as still running, and the first report came on Slack at 13:26. Alerting for these failures did not exist or did not work.
- Remediation
- Requested and received additional disk quota
- Brought up 55 nodes with 500 GB disks in a new node pool
- Migrated all nodes from the 250 GB disk pool to the 500 GB disk pool by draining old nodes, finishing at 23:55
- Action items
- Create or fix monitoring so the oncall is paged when tide stops doing things
- Set a process and guidelines for adding new members to the oncall rotation, with preparation and extra support
- Lessons
Prow metrics were not recorded before the incident, which made it hard to understand, and alerting for these failures did not exist or did not work. After the cause was found and a fix devised, nothing happened for another two hours. The team counts it as luck that someone who recognised IOPS as the problem happened to be around to look.
These 2 cases involve CI system and PostgreSQL vacuum. 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 cause1
Capacity exhaustion2 cases
- Contributing factor
- Organisation