使用ACME监控、分析和控制Internet规模的系统
Monitoring, Analyzing, and Controlling Internet-scale Systems with ACME
摘要：
在各种条件下分析和控制大型分布式服务是困难的。然而，这些能力对于许多重要的开发和操作任务（如基准测试、测试和系统管理）来说是必不可少的。为了促进这些任务，我们已经建立了应用程序控制和监控环境（ACME），一个可扩展的，灵活的基础设施，用于监测，分析和控制互联网规模的系统。ACME由两部分组成。ISING（Internet Sensor In-Network agGregator）查询传感器并在通过覆盖网络路由时汇总结果。ENTRIE是触发Internet事件的引擎，它使用ISING提供的数据流，结合用户的XML配置文件，来触发执行器，例如在鲁棒性基准测试期间终止进程或在观察到预定义的异常条件时寻呼系统管理员。在本文中，我们描述的设计，实施和评估ACME及其组成部分。我们发现，对于一个512节点的系统上运行一个模拟的互联网拓扑结构，ISING的使用网络聚合可以减少端到端的查询响应延迟超过50%相比，使用直接的网络连接或相同的覆盖网络没有聚合。我们还发现，ACME的未调优实现可以调用一个或所有节点上的执行器响应于一个离散或聚合事件在不到4秒，我们说明ACME的适用性，具体的基准测试和监控方案。
英文摘要：
Analyzing and controlling large distributed services under a wide range of conditions is difficult. Yet these capabilities are essential to a number of important development and operational tasks such as benchmarking, testing, and system management. To facilitate these tasks, we have built the Application Control and Monitoring Environment (ACME), a scalable, flexible infrastructure for monitoring, analyzing, and controlling Internet-scale systems. ACME consists of two parts. ISING, the Internet Sensor In-Network agGregator, queries sensors and aggregates the results as they are routed through an overlay network. ENTRIE, the ENgine for TRiggering Internet Events, uses the data streams supplied by ISING, in combination with a user's XML configuration file, to trigger actuators such as killing processes during a robustness benchmark or paging a system administrator when predefined anomalous conditions are observed. In this paper we describe the design, implementation, and evaluation of ACME and its constituent parts. We find that for a 512-node system running atop an emulated Internet topology, ISING's use of in-network aggregation can reduce end-to-end query-response latency by more than 50% compared to using either direct network connections or the same overlay network without aggregation. We also find that an untuned implementation of ACME can invoke an actuator on one or all nodes in response to a discrete or aggregate event in less than four seconds, and we illustrate ACME's applicability to concrete benchmarking and monitoring scenarios.
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。
