Sprig: Low-Latency Startup for Knative Serverless Platforms with Async-Cfork

Le résumé fourni par la source

Serverless computing has emerged as a transformative paradigm in the cloud-native era, widely adopted across major public cloud platforms. However, its pay-as-use model necessitates frequent dynamic instance creation and destruction, making cold start latency a critical system bottleneck. While the industry predominantly employs caching techniques to mitigate cold start overheads, these approaches exhibit inherent limitations. Existing research prototypes often optimize container runtimes manually, resulting in systems incompatible with production environments that cannot leverage automated management capabilities or integrate optimizations effectively. Moreover, runtime optimizations fail to fit system features like asynchronous cold start. This paper presents Sprig, the first serverless system that seamlessly integrates cutting-edge academic research with production-grade platforms. We introduce a novel computational abstraction called Template Pod to bridge the gap between research-oriented flexible designs and minimal computational units in production systems. Sprig further incorporates Asynccfork, a low-latency startup technique optimized for large-scale serverless platforms, significantly reducing function cold start latency. Additionally, we design a multiplexed proxy queue with enhanced scheduling elasticity to resolve request accumulation issues in Knative's asynchronous startup mechanism. Evaluations show Sprig achieves a 70% average reduction in cold start latency compared with Knative, and decreases P99 end-to-end latency from 27s to 0.5s under high load while maintaining only 16.7% of baseline memory footprint for 20 instances.

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