Incident with Copilot AI Model Providers
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
On July 29, 2026, from 14:51 UTC to 15:28 UTC, GitHub Actions experienced elevated REST API request timeouts and errors, failures registering runners, and delayed workflow run starts for customers whose traffic was served by a single infrastructure site. This was caused by an under-provisioned internal Actions service in that site: under increased load its instances ran out of memory and became unresponsive, and because Actions API requests wait synchronously on that service, requests routed through the affected site stalled and timed out. During the incident, approximately 2% of workflows were delayed. Requests served by other sites remained unaffected. Both standard and larger hosted runners routed through the affected site could see delayed job starts. The issue was mitigated by scaling out the runner-administration service in the affected site and increasing the replica count, which restored API availability and returned workflow run starts to normal. We are working to add horizontal autoscaling, memory-saturation alerting, and scaling-forecast monitoring for this service, along with responder playbooks, to reduce the likelihood of similar issues in the future.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
This incident has been resolved. Thank you for your patience and understanding as we addressed this issue. A detailed root cause analysis will be shared as soon as it is available.
Please refer to the combined summary in this related incident: https://www.githubstatus.com/incidents/s65j9gslmfm8
On July 25, 2026, between 09:07 and 10:04 UTC, the GPT-5.2, GPT-5.3-Codex, GPT-5.4, GPT-5.4 Mini, GPT-5.6 Sol, GPT-5.6 Terra and GPT-5.6 Luna models experienced degraded availability in GitHub Copilot products and IDE surfaces. Requests to these models had an average failure rate of 5.6%. Other Copilot models remained available as alternatives.The degradation was caused by an issue with an upstream model provider. Success rates returned to normal after the upstream issue was mitigated, and we continued monitoring before resolving the incident. We are working on improving the automated failover for the affected models to prevent similar incidents in the future.
On July 25, 2026, GitHub Actions experienced two related periods of degradation that caused some workflow runs to be delayed by more than 5 minutes or end with infrastructure failures. First period (08:45 – 09:13 UTC): During planned maintenance on a critical-path Redis cluster for Actions, one participating region was left in a degraded state. Separately, an independent capacity operation temporarily removed another region from the cluster and redirected its traffic to the degraded region. This created cross-region inconsistencies in job-assignment state, causing workflow runs to be delayed, exhaust retries, or fail outright. At peak, about 7% of runs were delayed by more than 5 minutes, and 25% of runs failed with an infrastructure error during the course of the incident. We mitigated the incident at 09:13 UTC by returning traffic to its normal distribution. Second period (12:08 – 12:48 UTC): As part of mitigating the first incident, traffic was returned to the regional instance that was still undergoing its capacity increase. Multiple Redis nodes in the scaling region experienced failures, increasing traffic to healthy nodes and causing connection limits to be reached on many nodes. At peak, 30% of runs were delayed by more than 5 minutes, and 60% of runs failed with an infrastructure error during the course of the incident. We mitigated the incident at 12:48 UTC by redirecting workflow traffic away from the scaling region. We are adding stronger regional health and capacity checks before maintenance and requiring a stable observation period before restoring traffic. We are also improving automated connection resiliency, and partnering with our platform dependency to automatically detect and remediate unhealthy cluster members and shard imbalance. More generally, we already had work underway to improve the resiliency and scale of this piece of Actions infrastructure.