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Cloud resilience is crucial for cloud operators and the myriad ofapplications that rely on the cloud. Today, we lack a mechanism that allowscloud operators to gracefully degrade application performance in public clouds.In this paper, we put forward a vision for automated feature degradation with athree-pronged approach. First, we introduce the idea of diagonal scaling --pruning an application's dependency graphs during capacity crunch scenarios --to maximize the availability of critical services. Second, we propose the useof simple and expressive Criticality Tags on microservices to convey anapplication developer's resilience intent to the cloud provider without anyapplication modifications. Third, we design Gecko, an automated cloudresilience management system that maximizes critical service availability ofapplications while also taking into account operator objectives, therebyimproving the overall resilience of the infrastructure during failures. Usingextensive experiments, we show that the Gecko controller running atopKubernetes can maximize the overall resilience of applications andinfrastructure under a broad range of failure scenarios. We also demonstratethat diagonal scaling with Gecko aligns well with microservice architectureusing experiments with a real-world application.

Gecko: Automated Feature Degradation for Cloud Resilience