DocumentCode
18873
Title
Integrated Monitoring Software for Application Service Managers
Author
Yoshizawa, Masamitsu ; Sato, Takao ; Naono, Ken
Author_Institution
Platform Syst. Res. Dept., Hitachi Ltd., Tokyo, Japan
Volume
11
Issue
3
fYear
2014
fDate
Sept. 2014
Firstpage
321
Lastpage
332
Abstract
In today´s data centers, many application services share the same physical/virtual devices and affect each other. Therefore, application service managers need to spend a lot of time monitoring the application services by investigating a wide range of historical data about the shared devices. In this paper, integrated monitoring software for a wide range of historical data, which shortens the transition time (i.e., the time to switch from one historical data to another) by collecting and processing the historical data, is proposed and evaluated. Five basic historical data formats for automatically creating both well-organized historical data and relation data for the historical data are also proposed. The formats help application service managers by eliminating the need for the additional software development, which was otherwise required for each application service. Surveys on application service managers in a SaaS provider for over 50 000 companies show that about 98.6% of monitoring tasks can be covered by the five basic data formats and that the integrated monitoring software reduces the transition times for switching between historical data by about 54.7% compared to those with conventional monitoring software. These results suggest that the proposed integrated monitoring software is effective not only for reducing the time required for monitoring application services, but also for enhancing the overall service availability of SaaS providers´ systems.
Keywords
cloud computing; computer centres; integrated software; software development management; system monitoring; SaaS; application service manager; data center; data format; historical data; integrated monitoring software; physical-virtual device; service availability; software development; time monitoring; transition time reduction; Batch production systems; Databases; Monitoring; Servers; Software as a service; Switches; SaaS; Service monitoring; anomaly detection; impact analysis; monitoring software; performance prediction; root cause analysis;
fLanguage
English
Journal_Title
Network and Service Management, IEEE Transactions on
Publisher
ieee
ISSN
1932-4537
Type
jour
DOI
10.1109/TNSM.2014.2346073
Filename
6873567
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