DocumentCode
717099
Title
Automated business application discovery
Author
Nidd, Michael ; Kun Bai ; Jinho Hwang ; Vukovic, Maja ; Tacci, Michael
Author_Institution
Zurich Lab., IBM Res., Zurich, Switzerland
fYear
2015
fDate
11-15 May 2015
Firstpage
794
Lastpage
797
Abstract
When planning a data center migration it is critical to discover the client´s business applications and on which devices (server, storage and appliances) those applications are deployed in the infrastructure. It is also important to understand the dependencies the applications have on the infrastructure, on other applications, and in some cases on systems external to the client. Clients can only rarely provide that information in a complete and accurate manner. The usual approach then has been to obtain the information by asking the client´s application and platform owners a series of questions but in most cases clients do not have the tools or skills to acquire the requested information. The lack of accurate information leads to project delays, increased cost and higher levels of risk. In this paper we present an algorithm and tools for programmatically identifying and locating business application instances in an infrastructure, based on weighted similarity metric. We discuss results from our preliminary evaluation and the correctness of the algorithm. Such automated approach to application discovery significantly helps clients to achieve their project objectives and timeline without imposing additional work on the application and platform owners.
Keywords
cloud computing; commerce; computer centres; planning; automated business application discovery; data center migration; planning; project delays; Business; Clustering algorithms; Interviews; Measurement; Planning; Servers; XML;
fLanguage
English
Publisher
ieee
Conference_Titel
Integrated Network Management (IM), 2015 IFIP/IEEE International Symposium on
Conference_Location
Ottawa, ON
Type
conf
DOI
10.1109/INM.2015.7140378
Filename
7140378
Link To Document