Serverless Function-as-a-Service (FaaS) is a popular cloud paradigm to quickly and cheaply implement complex applications. Because the function instances cloud providers start to execute user code run on shared infrastructure, their performance can vary. From a user perspective, slower instances not only take longer to complete, but also increase cost due to the pay-per-use model of FaaS services where execution duration is billed with microsecond accuracy. In this paper, we present Minos, a system to take advantage of this performance variation by intentionally terminating instances that are slow. Fast instances are not terminated, so that they can be re-used for subsequent invocations. One use case for this are data processing and machine learning workflows, which often download files as a first step, during which Minos can run a short benchmark. Only if the benchmark passes, the main part of the function is actually executed. Otherwise, the request is re-queued and the instance crashes itself, so that the platform has to assign the request to another (potentially faster) instance. In our experiments, this leads to a speedup of up to 13% in the resource intensive part of a data processing workflow, resulting in up to 4% faster overall performance (and consequently 4% cheaper prices). Longer and complex workflows lead to increased savings, as the pool of fast instances is re-used more often. For platforms exhibiting this behavior, users get better performance and save money by wasting more of the platforms resources.

翻译：无服务器函数即服务（FaaS）是一种流行的云范式，能够以低成本快速实现复杂应用。由于云提供商启动执行用户代码的函数实例运行在共享基础设施上，其性能可能存在波动。从用户视角看，运行缓慢的实例不仅延长完成时间，还会因FaaS服务按使用时长精确到微秒计费的特性增加成本。本文提出Minos系统，该系统通过主动终止运行缓慢的实例来利用这种性能波动。快速实例将得以保留，以便在后续调用中重复使用。该系统的典型应用场景包括数据处理和机器学习工作流，这类流程通常以下载文件作为初始步骤，Minos可在此期间运行简短基准测试。仅当基准测试通过时，函数主体才会实际执行；否则请求将重新排队，实例自行崩溃，迫使平台将请求分配至其他（可能更快的）实例。实验表明，在数据处理工作流的资源密集型环节中，该方法可实现高达13%的加速，整体性能提升最高达4%（相应降低4%成本）。更长更复杂的工作流能带来更高收益，因为快速实例池会被更频繁地复用。对于存在此类性能波动的平台，用户可通过消耗更多平台资源获得更优性能并节省成本。