Realistic, relevant, and reproducible experiments often need input traces collected from real-world environments. In this work, we focus on traces of workflows—common in datacenters, clouds, and HPC infrastructures. We show that the state-of-the-art in using workflow-traces raises important issues: (1) the use of realistic traces is infrequent and (2) the use of realistic, open-access traces even more so. Alleviating these issues, we introduce the Workflow Trace Archive (WTA), an open-access archive of workflow traces from diverse computing infrastructures and tooling to parse, validate, and analyze traces. The WTA includes >48{>}48 million workflows captured from >10{>}10 computing infrastructures, representing a broad diversity of trace domains and characteristics. To emphasize the importance of trace diversity, we characterize the WTA contents and analyze in simulation the impact of trace diversity on experiment results. Our results indicate significant differences in characteristics, properties, and workflow structures between workload sources, domains, and fields.

中文翻译：

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工作流程跟踪档案：来自公共和私人计算基础设施的开放访问数据


真实、相关且可重复的实验通常需要从现实环境中收集的输入轨迹。在这项工作中，我们重点关注数据中心、云和 HPC 基础设施中常见的工作流程痕迹。我们表明，使用工作流跟踪的最新技术提出了重要问题：（1）真实跟踪的使用很少，（2）真实的、开放访问跟踪的使用更常见。为了缓解这些问题，我们引入了工作流跟踪存档 (WTA)，这是一个开放访问的工作流跟踪存档，来自不同的计算基础设施和用于解析、验证和分析跟踪的工具。 WTA 包括从 >10{>}10 计算基础设施捕获的 >48{>}4800 万个工作流，代表了跟踪域和特征的广泛多样性。为了强调痕量多样性的重要性，我们描述了 WTA 内容并在模拟中分析了痕量多样性对实验结果的影响。我们的结果表明工作负载源、域和字段之间的特征、属性和工作流结构存在显着差异。