Due to increasing popularity and strict performance requirements, online games have become a workload of interest for the performance engineering community. One of the most popular types of online games is the Minecraft-like Game (MLG), in which players can terraform the environment. The most popular MLG, Minecraft, provides not only entertainment, but also educational support and social interaction, to over 130 million people world-wide. MLGs currently support their many players by replicating isolated instances that support each only up to a few hundred players under favorable conditions. In practice, as we show here, the real upper limit of supported players can be much lower. In this work, we posit that performance variability is a key cause for the lack of scalability in MLGs. We propose a novel operational model for MLGs and use it to design the first benchmark that focuses on MLG performance variability, defining specialized workloads, metrics, and processes. We conduct real-world benchmarking of MLGs and find environment-based workloads and cloud deployment to be significant sources of performance variability: peak-latency degrades sharply to 20.7 times the arithmetic mean, and exceeds by a factor of 7.4 the performance requirements. We derive actionable insights for game-developers, game-operators, and other stakeholders to tame performance variability.
翻译:由于受欢迎程度的提高和严格的绩效要求,在线游戏已成为表演工程界感兴趣的工作量。最受欢迎的在线游戏类型之一是“像地雷一样的游戏 ” ( MLG ), 球员可以在游戏中改变环境。最受欢迎的 MLG, Minecraft, 不仅为全世界超过1.3亿人提供娱乐, 而且还提供教育支持和社会互动。 MLG 目前通过复制孤立的例子来支持其众多的球员,这些例子只在有利的条件下支持每个球员达几百个球员。 实际上,正如我们在这里所显示的那样, 得到支持的球员的真正上限可以大大降低。 在这项工作中,我们假设, 性能变异性是MLG 缺乏适应环境的关键原因。 我们为MLG 提出了一个全新的操作模式, 不仅提供娱乐, 而且还提供教育支持和社会互动。 MLG 目前在设计第一个以MLG 表现变异性为重点的基准时, 定义了专门的工作量、 尺度和程序。 我们进行现实世界的MLG 基准, 并发现基于环境的工作量和云的部署是业绩变异性的重要来源: 最慢的温度将急剧降至20.7倍于游戏的视野, 。