Catalyzer: Sub-millisecond Startup for Serverless Computing with Initialization-less Booting

By Dong Du, Tianyi Yu, Yubin Xia, Binyu Zang, Guanglu Yan, Chenggang Qin, Qixuan Wu, Haibo Chen. International Conference on Architectural Support for Programming Languages and Operating Systems, 2020

385 citations recorded by the source corpus.

Serverless computing promises cost-efficiency and elasticity for high-productive software development. To achieve this, the serverless sandbox system must address two challenges: strong isolation between function instances, and low startup latency to ensure user experience. While strong isolation can be provided by virtualization-based sandboxes, the initialization of sandbox and application causes non-negligible startup overhead. Conventional sandbox systems fall short in low-latency startup due to their application-agnostic nature: they can only reduce the latency of sandbox initialization through hypervisor and guest kernel customization, which is inadequate and does not mitigate the majority of startup overhead. This paper proposes Catalyzer, a serverless sandbox system design providing both strong isolation and extremely fast function startup. Instead of booting from scratch, Catalyzer restores a virtualization-based function instance from a well-formed checkpoint image and thereby skips the initialization on the critical path (init-less). Catalyzer boosts the restore performance by on-demand recovering both user-level memory state and system state. We also propose a new OS primitive, sfork (sandbox fork), to further reduce the startup latency by directly reusing the state of a running sandbox instance. Fundamentally, Catalyzer removes the initialization cost by reusing state, which enables general optimizations for diverse serverless functions. The evaluation shows that Catalyzer reduces startup latency by orders of magnitude, achieves < 1ms latency in the best case, and significantly reduces the end-to-end latency for real-world workloads. Catalyzer has been adopted by Ant Financial, and we also present lessons learned from industrial development.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/f14446970a5ed7145a6d350e1aff07ca203cece8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Simon Shillaker
2. Peter R. Pietzuch

In Computer Networks and Communications

1. Alexander Fuerst
2. Simon Shillaker
3. Peter R. Pietzuch
4. Prateek Sharma

In Information Systems

1. Alexander Fuerst
2. Simon Shillaker
3. Peter R. Pietzuch
4. Prateek Sharma

Citations in the corpus

• Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing (2020, background): “Table 1: Isolation approaches for serverless (Initialisation times include ahead-of-time snapshot restore where applicable [16,25,61].”
• FaasCache: keeping serverless computing alive with greedy-dual caching (2021, background): “Catalyzer [29] implements new mechanisms for checkpointing and restoring application and sandbox state, which significantly reduce the initialization cost of functions deployed in their gvisorbased sandbox environment.”