A Reactive Performance Monitoring Framework Katherine ChengLi Directed By: Prof. Liam Peyton Thesis Submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the degree of Master of Computer Science University of Ottawa Ottawa, Ontario, Canada June 2016 © Katherine ChengLi, Ottawa, Canada, 2016 Abstract With the ascendency of data and the rise of interest in analytics, organizations are becoming more interested in the use of data to make their business processes more intelligent and reactive. BI applications are a common way that organizations integrate analytics in their processes. However, it can be days, weeks or even months before a manual response is undertaken based on a human interpreting a report. Even when information technology supports automatic responses within an organization, it is often implemented in an ad hoc manner without following a systematic framework. In this thesis, we present a reactive performance monitoring (RPM) framework which aims at automating the link from the analytical (how well is the operational achieving the strategic) to the operational (the particular process steps implemented within an organization that determine its behavior) aspects of businesses to bypass the strategic (the high level and long term goals an organization is trying to achieve) as needed and reduce the latency between knowledge and action. Our RPM framework is composed of an architecture, a methodology, and a rule environment which permits the redaction of rules possessing relevant conditions and actions. In addition, we present an OLAP rule engine which is demonstrated to be effective in our framework where events are streamed in, reacted upon in real-time, and stored in an OLAP database. To develop and evaluate our framework, two case studies were undertaken. The first was done using IBM technologies implementing an application made to identify patients at high risk of cancer recurrence. The second was done using open source technologies. With this second implementation, we created an application that has the ii goal of informing women from at risk populations of the different stages of pregnancy on a weekly basis. iii Acknowledgements Although the accomplishment of a thesis is a personal achievement, I would certainly not have been able to finish it without the help, support, and patience of my supervisor Prof. Liam Peyton. Thank you for your continued help and encouragement. Thank you to my family for encouraging me throughout this process and for believing that I would be able to successfully accomplish this. A special thank you to Mathieu Jobin for his never ending support. In addition, I would like to thank the organizations that helped fund my master’s degree. This includes MITACS, NSERC, and OGS. Finally, thank you to IBM and CENGN for providing me the opportunity to intern with them. In particular, thank you to Randy Giffen from IBM and my Extreme Blue team. It has been a great source of knowledge and experience. iv Table of Contents Abstract ............................................................................................................................................ ii Acknowledgements ......................................................................................................................... iv Table of Contents ............................................................................................................................. v List of Figures ................................................................................................................................. viii List of Tables .................................................................................................................................... ix List of Acronyms ............................................................................................................................... x 1 Introduction ..............................................................................................................................1 1.1 Problem Statement ..........................................................................................................1 1.2 Thesis Motivation and Contributions ...............................................................................3 1.3 Thesis Methodology and Organization .............................................................................5 2 Background ...............................................................................................................................9 2.1 Performance Monitoring ..................................................................................................9 2.1.1 Performance Management ......................................................................................9 2.1.2 Real-time Analytics ................................................................................................ 10 2.1.3 Predictive Analytics ............................................................................................... 11 2.1.4 Event ...................................................................................................................... 11 2.2 Business Process Management ..................................................................................... 11 2.2.1 Business Process .................................................................................................... 11 2.2.2 Web Service ........................................................................................................... 12 2.2.3 Business Process Management (BPM) .................................................................. 12 2.3 Event Processing Technologies ...................................................................................... 14 2.3.1 Message Broker ..................................................................................................... 15 2.3.2 Event-Driven Architecture ..................................................................................... 15 2.3.3 Complex Event Processing (CEP) ........................................................................... 15 2.3.4 Notification ............................................................................................................ 16 2.4 On-Line Analytical Processing (OLAP) ............................................................................ 16 2.4.1 Data Access Object ................................................................................................ 16 2.4.2 Business Intelligence (BI) ....................................................................................... 17 2.4.3 Data Warehouse .................................................................................................... 17 v 2.4.4 Star Schema ........................................................................................................... 18 2.4.5 Online Analytical Processing (OLAP) ...................................................................... 18 2.5 Rule Engine .................................................................................................................... 19 2.5.1 State Monitoring Engine (SME) ............................................................................. 19 2.5.2 IBM SPSS Analytical Decision Management (IBM SPSS ADM) and IBM SPSS Modeler 20 2.5.3 Drools and IBM Operational Decision Manager .................................................... 20 2.6 Related Works ............................................................................................................... 21 2.6.1 Application Framework for Monitoring Care Processes (AFMCP) ........................ 21 2.6.2 Big data Analysis Infrastructure Testbed (BAIT) .................................................... 22 2.6.3 IBM Predictive Maintenance and Quality (IBM PMQ) ........................................... 25 3 A Reactive Performance Monitoring Framework .................................................................. 26 3.1 Problem Description ...................................................................................................... 26 3.2 Gap Analysis................................................................................................................... 29 3.3 Evaluation Criteria ......................................................................................................... 31 3.3.1 Framework ............................................................................................................. 31 3.3.2 Rule Environment .................................................................................................. 33 3.4 Overview of the Reactive Performance Monitoring Framework .................................. 35 3.4.1 Architectural Pattern ............................................................................................. 36 3.4.1.1 Critical Interfaces ............................................................................................... 41 3.4.2 Methodology ......................................................................................................... 41 3.4.3 Rule Environment .................................................................................................. 49 3.4.4 OLAP Rule Engine .................................................................................................. 51 4 Case Studies ........................................................................................................................... 55 4.1