Degraded Performance in Webhooks API and UI, Pull Requests

Final update

On February 9, 2026, between 07:05 UTC and 11:26 UTC, GitHub experienced intermittent degradation across Issues, Pull Requests, Webhooks, Actions, and Git operations. Approximately every 30 minutes, users encountered brief periods of elevated errors and timeouts lasting roughly 15 seconds each. During the incident window, approximately 1–2% of requests were impacted across these services, with Git operations experiencing up to 7% error rates during individual spikes. GitHub Actions saw up to 2% of workflow runs delayed by a median of approximately 7 minutes due to backups created during these periods. This was due to multiple resource-intensive workloads running simultaneously, which caused intermittent processing delays on the data storage layer. We mitigated the incident by scaling storage to a larger compute capacity, which resolved the processing delays. We are working to improve detection of resource-intensive queries, identify changes in load patterns, and enhance our monitoring to reduce our time to detection and mitigation of issues like this one in the future.

1. Resolved · Feb 9, 11:26 UTC
   On February 9, 2026, between 07:05 UTC and 11:26 UTC, GitHub experienced intermittent degradation across Issues, Pull Requests, Webhooks, Actions, and Git operations. Approximately every 30 minutes, users encountered brief periods of elevated errors and timeouts lasting roughly 15 seconds each. During the incident window, approximately 1–2% of requests were impacted across these services, with Git operations experiencing up to 7% error rates during individual spikes. GitHub Actions saw up to 2% of workflow runs delayed by a median of approximately 7 minutes due to backups created during these periods. This was due to multiple resource-intensive workloads running simultaneously, which caused intermittent processing delays on the data storage layer. We mitigated the incident by scaling storage to a larger compute capacity, which resolved the processing delays. We are working to improve detection of resource-intensive queries, identify changes in load patterns, and enhance our monitoring to reduce our time to detection and mitigation of issues like this one in the future.