Characterization and Reclamation of Frozen Garbage in Managed FaaS Workloads

FaaS (function-as-a-service) is becoming a popular workload in cloud environments due to its virtues such as auto-scaling and pay-as-you-go. High-level languages like JavaScript and Java are commonly used in FaaS for programmability, but their managed runtimes complicate memory management in the cloud. This paper first observes the issue of frozen garbage, which is caused by freezing cached function instances where their threads have been paused but the unused memory (e.g., garbage) is not reclaimed due to the semantic gap between FaaS and the managed runtime. This paper presents the first characterization of the negative effects induced by frozen garbage with various functions, which uncovers that it can occupy more than half of FaaS instances' memory resources on average. To this end, this paper proposes Desiccant, a freeze-aware memory manager for managed workloads in FaaS, which reclaims idle memory resources consumed by frozen garbage from managed runtime instances and thus notably improves memory efficiency. The evaluation on various FaaS workloads shows that Desiccant can reduce FaaS functions' peak memory consumption by up to 6.72×. Such saved memory consumption allows caching more FaaS instances to reduce the frequency of cold boots (creating instances before function execution) and p99 latency by up to 4.49× and 37.5%, respectively.