Quilt: Resource-aware Merging of Serverless Workflows
Yuxuan Zhang, Sebastian Angel
摘要
This paper describes Quilt, a serverless optimizer that automatically merges workflows that consist of many functions (possibly in different languages) into one process thereby avoiding high invocation latency, communication overhead, and long chains of cold starts. Instead of merging all functions, Quilt takes into account the provider's resource constraints to decide which functions to merge. Quilt is compatible with existing platforms without modification (Fission, OpenWhisk, and OpenFaaS), can merge functions in different languages (C, C++, Swift, Go, Rust) by acting at the level of LLVM IR, and requires no input or help from developers. Our evaluation shows that Quilt improves median workflow completion time by 45.63%–70.95% and throughput by 2.05×–12.87×.
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