Userpilot incident

Userpilot services degradation

Minor Resolved View vendor source →
Started
Apr 28, 2026, 03:07 PM UTC
Resolved
Apr 28, 2026, 06:35 PM UTC
Duration
3h 28m
Detected by Pingoru
Apr 28, 2026, 03:07 PM UTC

Affected components

Current status by service (Event Ingestion (US - Standard))

Update timeline

  1. investigating Apr 28, 2026, 03:07 PM UTC

    We are currently experiencing degraded performance affecting data ingestion. Some customers may notice delays in incoming data. Our engineering team is actively investigating and working to restore full performance as quickly as possible. Thank you for your patience.

  2. investigating Apr 28, 2026, 03:07 PM UTC

    We are currently experiencing degraded performance affecting data ingestion. Some customers may notice delays in incoming data. Our engineering team is actively investigating and working to restore full performance as quickly as possible. Thank you for your patience.

  3. resolved Apr 28, 2026, 05:51 PM UTC

    A fix has been implemented and deployed, and we are currently monitoring system performance to ensure stability. We will share the postmortem for this incident as a follow-up message. Thank you for your patience.

  4. resolved Apr 28, 2026, 06:35 PM UTC

    Postmortem The incident was caused by our database background optimization process not running aggressively enough. This allowed data fragments to accumulate across tables used for real-time cache loading. As the number of fragments increased, queries that normally completed in milliseconds were forced to scan across many more fragments than necessary. This significantly increased query latency and led to exhaustion of available database connections, which impacted data ingestion and content publishing performance. To resolve this, we reconfigured our database to optimize these tables more frequently and in smaller batches. This keeps fragment counts low and ensures real-time queries remain fast and stable. Additionally, we have added monitoring and alerting on fragment count and size per table so we can detect abnormal accumulation early and prevent similar incidents in the future.

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