GitHub, autoscaling, and the component substitution fallacy
This article discusses the technical challenges of autoscaling services, specifically focusing on the 'component substitution fallacy' during a GitHub outage. It explains how relying solely on CPU metrics can lead to service saturation when I/O-bound threads are blocked.
Why it matters
Understanding proper autoscaling metrics is critical for maintaining high availability in complex, distributed cloud architectures.
In yesterday’s post about the recent GitHub outage , there was a detail in the writeup that I didn’t say anything about: the autoscaling policy on the service with the saturated Istio sidecar.
Originally this was caused by an Istio sidecar pod reaching its concurrency limits and failing to auto scale correctly because of a misconfigured policy that watched host service but not sidecar limits.
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