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GitHub · Developer toolsMay 19, 2026, 05:30 UTC 5 months ago

Incident with Copilot

InformationalCapacityUpdated 46d ago
May 19, 05:30 UTCMay 19, 05:30 UTC
Duration
0m
Impact
Informational
Root cause
Capacity
GitHub, 90 days
69 incidents
Affected
Not listed by the vendor.
Status page

Final update

On May 19, 2026, between 05:30 UTC and 14:50 UTC, some Copilot users experienced failures when using code completions, chat sessions, and cloud agent sessions. At peak impact, approximately 13% of Copilot API requests failed, and approximately 24% of remote sessions failed to initialize. A partial mitigation at 08:16 UTC reduced the Copilot API error rate to approximately 0.3%, but intermittent failures persisted until a full fix was deployed at 14:15 UTC and recovery was verified by 14:50 UTC. The incident was caused by rate limits being exceeded on a shared infrastructure component. A recently enabled feature increased call volume to this component, and the combined load exceeded capacity limits as traffic increased during business hours. We mitigated the incident by deploying a caching layer to reduce load on shared infrastructure. To prevent recurrence, we are separating rate limit scopes between services, adding monitoring for internal dependency rate limiting, and reducing redundant calls.

Timeline

  1. Resolved · May 19, 05:30 UTC
    On May 19, 2026, between 05:30 UTC and 14:50 UTC, some Copilot users experienced failures when using code completions, chat sessions, and cloud agent sessions. At peak impact, approximately 13% of Copilot API requests failed, and approximately 24% of remote sessions failed to initialize. A partial mitigation at 08:16 UTC reduced the Copilot API error rate to approximately 0.3%, but intermittent failures persisted until a full fix was deployed at 14:15 UTC and recovery was verified by 14:50 UTC. The incident was caused by rate limits being exceeded on a shared infrastructure component. A recently enabled feature increased call volume to this component, and the combined load exceeded capacity limits as traffic increased during business hours. We mitigated the incident by deploying a caching layer to reduce load on shared infrastructure. To prevent recurrence, we are separating rate limit scopes between services, adding monitoring for internal dependency rate limiting, and reducing redundant calls.

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