Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Monitoring, Analyzing, and Controlling Internet-Scale Systems with ACME

David Oppenheimer, Vitaliy Vatkovskiy, Hakim Weatherspoon, Jason Lee, David A. Patterson and John Kubiatowicz

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-03-1276
October 2003

http://www.eecs.berkeley.edu/Pubs/TechRpts/2003/CSD-03-1276.pdf

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.


BibTeX citation:

@techreport{Oppenheimer:CSD-03-1276,
    Author = {Oppenheimer, David and Vatkovskiy, Vitaliy and Weatherspoon, Hakim and Lee, Jason and Patterson, David A. and Kubiatowicz, John},
    Title = {Monitoring, Analyzing, and Controlling Internet-Scale Systems with ACME},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2003},
    Month = {Oct},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2003/5770.html},
    Number = {UCB/CSD-03-1276},
    Abstract = {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.}
}

EndNote citation:

%0 Report
%A Oppenheimer, David
%A Vatkovskiy, Vitaliy
%A Weatherspoon, Hakim
%A Lee, Jason
%A Patterson, David A.
%A Kubiatowicz, John
%T Monitoring, Analyzing, and Controlling Internet-Scale Systems with ACME
%I EECS Department, University of California, Berkeley
%D 2003
%@ UCB/CSD-03-1276
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2003/5770.html
%F Oppenheimer:CSD-03-1276