On August 1st, 2026, the GPT-5.6 Luna model in GitHub Copilot experienced degraded availability in intermittent time intervals between ~08:05 UTC and ~16:30 UTC. Specifically the timeframes observed were 10:00-10:20 UTC, 10:45-11:50 UTC, 13:00-14:25 UTC, and 16:00-16:30 UTC. During this time, requests to GPT-5.6 Luna in Copilot chat and IDE surfaces frequently failed or timed out. This was caused by an issue with an upstream model provider. Other Copilot models were not affected, and users could continue working by selecting another model or 'Auto'. Availability for GPT-5.6 Luna fully recovered once the provider resolved their outage at 16:30 UTC.
On July 30, 2026, the Claude Fable 5 model in GitHub Copilot experienced degraded availability for approximately 73 minutes, from 08:33 to 09:46 UTC. During this time, requests to Claude Fable 5 in Copilot chat and IDE surfaces frequently failed or timed out. This was caused by an issue with an upstream model provider. Other Copilot models were not affected, and users could continue working by selecting another model or 'Auto'. Availability for Claude Fable 5 fully recovered once the provider resolved their outage at 09:46 UTC, and we confirmed resolution at 10:12 UTC.
On July 29, 2026, between 19:45 UTC and 21:51 UTC, users of the Fable 5 model in GitHub Copilot experienced increased request failures and latency. The average failure rate across all Copilot requests was 0.006%, while failures for Fable 5 peaked at 21%. Other models remained available. This was caused by degradation of an upstream model provider.The affected endpoint recovered, and we monitored the service until error rates and latency returned to normal levels. We are working to add endpoint redundancy to mitigate similar provider issues in the future.
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.
On July 26, 2026 at 21:34 UTC we began seeing intermittent errors on the GitHub GraphQL API. A subset of GraphQL API requests returned HTTP 502 errors in short bursts. During the impact window an average of 0.09% of GraphQL API requests in the affected region failed, with a peak of 0.50% of requests failing during the worst two-minute period at 03:02 UTC on July 27. Requests that failed generally succeeded when retried, and no data was lost or altered. Other GitHub services were not affected.The errors were traced to a single group of servers handling a share of GraphQL API traffic. Application processes on that group intermittently closed connections before completing responses. Impact ended at 03:52 UTC on July 27 when those processes were replaced, and we resolved the incident at 04:09 UTC on July 27 after confirming error rates had returned to normal.We are still investigating why those processes closed connections, and that work is being carried out by the team that owns the underlying compute platform. In the meantime we are adding detection and automated mitigation for when a single group of servers behaves differently from its peers.
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.
Between July 24, 19:17 UTC and July 24, 20:02 UTC, users were unable to create pull requests due to a database schema change. In total, 113,930 pull request creation attempts were impacted across 50,904 users, with an average error rate of 1.75% and a maximum error rate of 2.25% for all requests to Pull Requests service. Existing pull requests and other GitHub functionality were not affected. The issue was resolved by reverting the change to the affected database, upon which pull request creation immediately resumed.The root cause was related to a backfill workflow into the Vitess keyspace hosting Pull Request data. The backfill Vitess command encountered errors and increased VReplication lag, and the workflow was canceled at 19:17 UTC. The cancellation executed a misunderstood Vitess codepath that dropped the backing table to the target keyspace, leaving a non-existent reference that resulted in errors creating Pull Requests. The mitigation was executing a command to drop the vschema reference to the dropped table, allowing Pull Request creation to resume.We are adding stronger pre-flight validation to our tooling to prevent similar issues and expanding lower-environment support to provide better test coverage end-to-end before promoting them to production. We're also fixing our backfill migration tooling to protect from this specific codepath.