Event Processing In Action

Author: Opher Etzion
Editor: Manning Publications
ISBN: 9781935182214
Size: 20,21 MB
Format: PDF, ePub, Docs
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Written for working software architects and developers, this edition presents common event-driven patterns and explains how to detect and implement them. Throughout the book, readers follow a comprehensive use case that incorporates all event processing programming styles in practice today.

The Power Of Events

Author: David C. Luckham
Editor: Addison-Wesley Professional
ISBN: 9780201727890
Size: 14,90 MB
Format: PDF, Kindle
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Complex Event Processing (CEP) is a defined set of tools and techniques for analyzing and controlling the complex series of interrelated events that drive modern distributed information systems. This emerging technology helps IS and IT professionals understand what is happening within the system, quickly identify and solve problems, and more effectively utilize events for enhanced operation, performance, and security. CEP can be applied to a broad spectrum of information system challenges, including business process automation, schedule and control processes, network monitoring and performance prediction, and intrusion detection. "The Power of Events" introduces CEP and shows specifically how this innovative technology can be utilized to enhance the quality of large-scale, distributed enterprise systems. The book describes the challenges faced by today's information systems, explains fundamental CEP concepts, and highlights CEP's role within a complex and evolving contemporary context. After thoroughly introducing the concept, the book moves on to a more detailed, technical explanation of CEP, featuring the Rapide(TM) event pattern language, reactive event pattern rules, event pattern constraints, and event processing agents. It offers practical advice on building CEP-based solutions that solve real world IS/IT problems. Readers will learn about such essential topics as: Managing the open electronic enterprise in the "global event cloud"Process architectures and on-the-fly process evolutionEvents, timing, causality, and aggregationEvent patterns and event abstraction hierarchiesCausal event tracking and information gapsMultiple views and hierarchical viewingDynamic process architecturesThe Rapide event pattern languageEvent pattern rules, constraints, and agentsEvent processing networks (EPNs)Causal models and event pattern mapsImplementing event abstraction hierarchies Several comprehensive case studies illustrate the benefits of CEP, as well as key strategies for applying the technology. Examples include the real-time monitoring of events flowing between the business processes of collaborating enterprises, and a hierarchically organized set of event-driven views of a financial trading system. One of the case studies shows how to apply CEP to network viewing and intrusion detection. The book concludes with a look at building an infrastructure for CEP, showing how the technology can provide a significant competitive advantage amidst the myriad of event-driven, Internet-based applications now coming onto the market. 0201727897B05172002

Event Streams In Action

Author: Alexander Dean
Editor: Pearson Professional
ISBN: 9781617292347
Size: 10,77 MB
Format: PDF, ePub
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Summary Event Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications. About the Book Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain. What's inside Validating and monitoring event streams Event analytics Methods for event modeling Examples using Apache Kafka and Amazon Kinesis About the Reader For readers with experience coding in Java, Scala, or Python. About the Author Alexander Dean developed Snowplow, an open source event processing and analytics platform. Valentin Crettaz is an independent IT consultant with 25 years of experience. Table of Contents PART 1 - EVENT STREAMS AND UNIFIED LOGS Introducing event streams The unified log 24 Event stream processing with Apache Kafka Event stream processing with Amazon Kinesis Stateful stream processing PART 2- DATA ENGINEERING WITH STREAMS Schemas Archiving events Railway-oriented processing Commands PART 3 - EVENT ANALYTICS Analytics-on-read Analytics-on-write

Event Processing For Business

Author: David C. Luckham
Editor: John Wiley & Sons
ISBN: 1118171853
Size: 14,71 MB
Format: PDF
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Find out how Events Processing (EP) works and how it can work for you Business Event Processing: An Introduction and Strategy Guide thoroughly describes what EP is, how to use it, and how it relates to other popular information technology architectures such as Service Oriented Architecture. Explains how sense and response architectures are being applied with tremendous results to businesses throughout the world and shows businesses how they can get started implementing EP Shows how to choose business event processing technology to suit your specific business needs and how to keep costs of adopting it down Provides practical guidance on how EP is best integrated into an overall IT strategy and how its architectural styles differ from more conventional approaches This book reveals how to make the most advantageous use of event processing technology to develop real time actionable management information from the events flowing through your company's networks or resulting from your business activities. It explains to managers and executives what it means for a business enterprise to be event-driven, what business event processing technology is, and how to use it.

Proceedings Of The Master Seminar On Event Processing Systems For Business Process Management Systems

Author: Baumgraß, Anne
Editor: Universitätsverlag Potsdam
ISBN: 3869563478
Size: 17,30 MB
Format: PDF, ePub, Mobi
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Traditionally, business process management systems only execute and monitor business process instances based on events that originate from the process engine itself or from connected client applications. However, environmental events may also influence business process execution. Recent research shows how the technological improvements in both areas, business process management and complex event processing, can be combined and harmonized. The series of technical reports included in this collection provides insights in that combination with respect to technical feasibility and improvements based on real-world use cases originating from the EU-funded GET Service project – a project targeting transport optimization and green-house gas reduction in the logistics domain. Each report is complemented by a working prototype. This collection introduces six use cases from the logistics domain. Multiple transports – each being a single process instance – may be affected by the same events at the same point in time because of (partly) using the same transportation route, transportation vehicle or transportation mode (e.g. containers from multiple process instances on the same ship) such that these instances can be (partly) treated as batch. Thus, the first use case shows the influence of events to process instances processed in a batch. The case of sharing the entire route may be, for instance, due to origin from the same business process (e.g. transport three containers, where each is treated as single process instance because of being transported on three trucks) resulting in multi-instance process executions. The second use case shows how to handle monitoring and progress calculation in this context. Crucial to transportation processes are frequent changes of deadlines. The third use case shows how to deal with such frequent process changes in terms of propagating the changes along and beyond the process scope to identify probable deadline violations. While monitoring transport processes, disruptions may be detected which introduce some delay. Use case four shows how to propagate such delay in a non-linear fashion along the process instance to predict the end time of the instance. Non-linearity is crucial in logistics because of buffer times and missed connection on intermodal transports (a one-hour delay may result in a missed ship which is not going every hour). Finally, use cases five and six show the utilization of location-based process monitoring. Use case five enriches transport processes with real-time route and traffic event information to improve monitoring and planning capabilities. Use case six shows the inclusion of spatio-temporal events on the example of unexpected weather events.

Web Oriented Event Processing

Author: Stuehmer, Roland
Editor: KIT Scientific Publishing
ISBN: 3731502658
Size: 20,94 MB
Format: PDF
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Towards Semantically Enabled Complex Event Processing

Author: Robin Keskisärkkä
Editor: Linköping University Electronic Press
ISBN: 9176854795
Size: 11,32 MB
Format: PDF, Kindle
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The Semantic Web provides a framework for semantically annotating data on the web, and the Resource Description Framework (RDF) supports the integration of structured data represented in heterogeneous formats. Traditionally, the Semantic Web has focused primarily on more or less static data, but information on the web today is becoming increasingly dynamic. RDF Stream Processing (RSP) systems address this issue by adding support for streaming data and continuous query processing. To some extent, RSP systems can be used to perform complex event processing (CEP), where meaningful high-level events are generated based on low-level events from multiple sources; however, there are several challenges with respect to using RSP in this context. Event models designed to represent static event information lack several features required for CEP, and are typically not well suited for stream reasoning. The dynamic nature of streaming data also greatly complicates the development and validation of RSP queries. Therefore, reusing queries that have been prepared ahead of time is important to be able to support real-time decision-making. Additionally, there are limitations in existing RSP implementations in terms of both scalability and expressiveness, where some features required in CEP are not supported by any of the current systems. The goal of this thesis work has been to address some of these challenges and the main contributions of the thesis are: (1) an event model ontology targeted at supporting CEP; (2) a model for representing parameterized RSP queries as reusable templates; and (3) an architecture that allows RSP systems to be integrated for use in CEP. The proposed event model tackles issues specifically related to event modeling in CEP that have not been sufficiently covered by other event models, includes support for event encapsulation and event payloads, and can easily be extended to fit specific use-cases. The model for representing RSP query templates was designed as an extension to SPIN, a vocabulary that supports modeling of SPARQL queries as RDF. The extended model supports the current version of the RSP Query Language (RSP-QL) developed by the RDF Stream Processing Community Group, along with some of the most popular RSP query languages. Finally, the proposed architecture views RSP queries as individual event processing agents in a more general CEP framework. Additional event processing components can be integrated to provide support for operations that are not supported in RSP, or to provide more efficient processing for specific tasks. We demonstrate the architecture in implementations for scenarios related to traffic-incident monitoring, criminal-activity monitoring, and electronic healthcare monitoring.

The Language Dura A Declarative Event Query Language For Reactive Event Processing

Author: Steffen Hausmann
Editor: epubli
ISBN: 3737513775
Size: 17,52 MB
Format: PDF, Docs
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This work investigates means towards more reactive event processing to close the gap between the requirements of modern emergency management and the capabilities of current event processing approaches

Event Processing With Cics

Author: Rufus Credle
Editor: IBM Redbooks
ISBN: 073843857X
Size: 18,95 MB
Format: PDF, Kindle
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This completely refreshed IBM Redbooks® publication provides a detailed introduction to the latest capabilities for business event processing with IBM® CICS® V5. Events make it possible to identify and react to situations as they occur, and an event-driven approach, where changes are detected as they happen, can enable an application or an Enterprise to respond in a much more timely fashion. CICS event processing support was first introduced in CICS TS V4.1, and this IBM Redbooks® publication now covers all the significant enhancements and extensions which have been made since then. CICS Transaction Server for z/OS provides capabilities for capturing application events, which can give insight into the business activities carried out within CICS applications, and system events, which give insight into changes in state within the CICS system. Application events can be generated from existing applications, without requiring any application changes. Simple tooling allows both application and system events to be defined and deployed into CICS without disruption to the system, and the resulting events can be made available to a variety of event consumers. CICS events can amongst other things be used to drive processing within CICS, to populate dashboards that are provided by IBM Business Monitor and to search for patterns in events using IBM Operational Decision Manager. This IBM Redbooks® publication is divided into the following parts: Part 1 introduces event processing. We explain what it is and why you need it, and discuss how CICS makes it easy to both capture and emit events. Part 2 of the book focuses on the details of event processing with CICS. It gives a step-by-step guide to implementing CICS events, along with the environment used in the examples. Part 3 provides some guidance on governance and troubleshooting for CICS events, and describes how to integrate CICS events with IBM Operational Decision Manager and IBM Business Monitor. The Appendices include additional reference information.