容器分析器：分析容器化大数据管道的资源利用率
Container Profiler: Profiling Resource Utilization of Containerized Big Data Pipelines
摘要：
本文介绍了容器分析器，一个软件工具，测量和记录任何容器化任务的资源使用情况。我们的工具分析了容器化任务的CPU、内存、磁盘和网络利用率，在虚拟机、容器和进程级别收集了50多个Linux操作系统指标。Container Profiler支持以可配置的采样间隔执行时间序列分析，以持续监控容器化任务和管道消耗的资源。为了研究Container Profiler的实用性，我们分析了多阶段生物信息学分析管道（使用独特分子标识符的RNA测序）的资源利用要求。我们检查分析指标，以评估跨管道的不同阶段的CPU、磁盘和网络资源利用率的模式。我们还量化了我们的容器分析器工具的分析开销，以评估分析具有不同级别的分析粒度的运行管道的影响，验证影响可以忽略不计。Container Profiler提供了一个有用的工具，可用于持续监控本地或云上运行的长时间复杂容器化应用程序的资源消耗。这可以帮助识别需要更多资源来提高性能的瓶颈。
英文摘要：
This paper presents the Container Profiler, a software tool that measures and records the resource usage of any containerized task. Our tool profiles the CPU, memory, disk, and network utilization of containerized tasks collecting over fifty Linux operating system metrics at the virtual machine, container, and process levels. The Container Profiler supports performing time series profiling at a configurable sampling interval to enable continuous monitoring of the resources consumed by containerized tasks and pipelines. To investigate the utility of the Container Profiler, we profile the resource utilization requirements of a multi-stage bioinformatics analytical pipeline (RNA sequencing using unique molecular identifiers). We examine profiling metrics to assess patterns of CPU, disk, and network resource utilization across the different stages of the pipeline. We also quantify the profiling overhead of our Container Profiler tool to assess the impact of profiling a running pipeline with different levels of profiling granularity verifying that impacts are negligible. The Container Profiler provides a useful tool that can be used to continuously monitor the resource consumption of long and complex containerized applications that run locally or on the cloud. This can help identify bottlenecks where more resources are needed to improve performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
