Disruption with some GitHub services

Final update

On April 13, 2026, between 14:41 UTC and 17:29 UTC, the Copilot service experienced degraded performance. All Copilot users were impacted by increased latency, and approximately 20% experienced request failures when interacting with Copilot Cloud Agent (CCA). On average, request latency increased to approximately 950ms. The GitHub User Dashboard also displayed intermittent errors loading Copilot quota information. CCA and the User Dashboard were impacted for approximately 2 hours and 56 minutes. This was due to an infrastructure change that reduced the available compute capacity for a backend service responsible for Copilot rate limiting and quota management. The reduced capacity caused resource exhaustion under normal traffic load, leading to cascading failures in downstream request processing. We mitigated the incident by increasing compute resources allocated to the affected service and scaling out the number of service instances to distribute load more effectively. We are working to improve proactive capacity monitoring to detect resource degradation before it impacts users, reviewing retry and timeout configurations across dependent services to reduce amplification during d

1. Resolved · Apr 13, 17:40 UTC
   On April 13, 2026, between 14:41 UTC and 17:29 UTC, the Copilot service experienced degraded performance. All Copilot users were impacted by increased latency, and approximately 20% experienced request failures when interacting with Copilot Cloud Agent (CCA). On average, request latency increased to approximately 950ms. The GitHub User Dashboard also displayed intermittent errors loading Copilot quota information. CCA and the User Dashboard were impacted for approximately 2 hours and 56 minutes. This was due to an infrastructure change that reduced the available compute capacity for a backend service responsible for Copilot rate limiting and quota management. The reduced capacity caused resource exhaustion under normal traffic load, leading to cascading failures in downstream request processing. We mitigated the incident by increasing compute resources allocated to the affected service and scaling out the number of service instances to distribute load more effectively. We are working to improve proactive capacity monitoring to detect resource degradation before it impacts users, reviewing retry and timeout configurations across dependent services to reduce amplification during degraded states, and evaluating connection management strategies to improve resilience under constrained resources.