Sidecar autoscaling failure cascades across GitHub
During a worldwide disruption of GitHub's collaboration, automation, and authentication services, roughly one in five web or API requests failed at peak, along with about half of archive and raw-file downloads.
Autoscaling and capacity monitoring must cover service-mesh sidecars and other infrastructure limits, while every retry path needs a bounded budget and backoff so recovery traffic cannot become a second outage.
A new traffic peak saturated Central US load balancers after an Istio sidecar hit its concurrency limit and an autoscaling policy failed to react to the sidecar's capacity.
Sidecar saturation spread until four HAProxy nodes exhausted their flow limits, slowing the shared authentication path and disrupting many GitHub services; optimistic gateway retries increased load, while a latent VS Code retry loop amplified Copilot token traffic by roughly tenfold and prolonged recovery.
Scale on every constrained layer, not just the application process. Cap retries with budgets and backoff so partial failures do not multiply load.
