FaaSNet: Scalable and Fast Provisioning of Custom Serverless Container Runtimes at Alibaba Cloud Function Compute
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Abstract (arXiv)
Serverless computing, or Function-as-a-Service (FaaS), enables a new way of building and scaling applications by allowing users to deploy fine-grained functions while providing fully-managed resource provisioning and auto-scaling. Custom FaaS container support is gaining traction as it enables better control over OSes, versioning, and tooling for modernizing FaaS applications. However, providing rapid container provisioning introduces non-trivial challenges for FaaS providers, since container provisioning is costly, and real-world FaaS workloads exhibit highly dynamic patterns. In this paper, we design FaaSNet, a highly-scalable middleware system for accelerating FaaS container provisioning. FaaSNet is driven by the workload and infrastructure requirements of the FaaS platform at one of the world's largest cloud providers, Alibaba Cloud Function Compute. FaaSNet enables scalable container provisioning via a lightweight, adaptive function tree (FT) structure. FaaSNet uses an I/O efficient, on-demand fetching mechanism to further reduce provisioning costs at scale. We implement and integrate FaaSNet in Alibaba Cloud Function Compute. Evaluation results show that FaaSNet: (1) finishes provisioning 2500 function containers on 1000 virtual machines in 8.3 seconds, (2) scales 13.4x and 16.3x faster than Alibaba Cloud's current FaaS platform and a state-of-the-art P2P container registry (Kraken), respectively, and (3) sustains a bursty workload using 75.2% less time than an optimized baseline.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 May 2021.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 3.
7 papers.
- 2024ServerlessLLM: Low-Latency Serverless Inference for Large Language Modelscited by 78
- 2023How Does It Function? Characterizing Long-term Trends in Production Serverless Workloadscited by 10
- 2025FlexPipe: Adapting Dynamic LLM Serving Through Inflight Pipeline Refactoring in Fragmented Serverless Clusterscited by 9
- 2024LIFL: A Lightweight, Event-driven Serverless Platform for Federated Learningcited by 2
- 2025PipeBoost: Resilient Pipelined Architecture for Fast Serverless LLM Scalingcited by 2
- 2024Shabari: Delayed Decision-Making for Faster and Efficient Serverless Functionscited by 0
- 2025SageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scalingcited by 0
- 2025FlexPipe: Adapting Dynamic LLM Serving Through Inflight Pipeline Refactoring in Fragmented Serverless Clusters13 Oct 2025
- 2025PipeBoost: Resilient Pipelined Architecture for Fast Serverless LLM Scaling22 Mar 2025
- 2025SageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scaling20 Feb 2025
- 2024LIFL: A Lightweight, Event-driven Serverless Platform for Federated Learning5 May 2024
- 2024ServerlessLLM: Low-Latency Serverless Inference for Large Language Models25 Jan 2024
- 2024Shabari: Delayed Decision-Making for Faster and Efficient Serverless Functions16 Jan 2024
- 2023How Does It Function? Characterizing Long-term Trends in Production Serverless Workloads15 Dec 2023