ON THE ROAD TO BENCHMARKING BPMN 2.0 WORKFLOW ENGINES

Similar documents
A Container-centric Methodology for Benchmarking Workflow Management Systems

Data-Aware Service Choreographies through Transparent Data Exchange

IMPROVING BUSINESS PROCESS MODELING USING RECOMMENDATION METHOD

Towards Management of SLA-Aware Business Processes Based on Key Performance Indicators

Six Strategies for Building High Performance SOA Applications

On the Suitability of BPMN for Business Process Modelling

On-demand Provisioning of Workflow Middleware and Services An Overview

Services and their Composition

Introducing Performance Engineering by means of Tools and Practical Exercises

SLA Business Management Based on Key Performance Indicators

A Classification of BPEL Extensions

Portable Cloud Services Using TOSCA

GSiB: PSE Infrastructure for Dynamic Service-oriented Grid Applications

REST vs. SOAP: Making the Right Architectural Decision

This is a closed book examination. You are not allowed to use any additional material during the exam. Date Name Last name score

Techniques for Composing REST services

Automatic Topology Completion of TOSCA-based Cloud Applications

Modeling RESTful Conversations with Extended BPMN Choreography Diagrams

Business Process Modeling

Useful Patterns for BPEL Developers

Data Flow and Validation in Workflow Modelling

25 May Code 3C3 Peeling the Layers of the 'Performance Onion John Murphy, Andrew Lee and Liam Murphy

Kanban vs Scrum. Henrik Kniberg - Crisp AB Agile coach & Java guy. A practical guide. Deep Lean, Stockholm May 19, 2009

Winery A Modeling Tool for TOSCA-based Cloud Applications

INFORMATION SYSTEMS EXAMINATIONS BOARD

Software Performance and Scalability

QoS Probing Of Real-World Web Services

A Framework for Adaptive Process Modeling and Execution (FAME)

A business process metamodel for Enterprise Information Systems automatic generation

Syllabus BT 416 Business Process Management

Performance of Enterprise Java Applications on VMware vsphere 4.1 and SpringSource tc Server

AN APPROACH TO DEVELOPING BUSINESS PROCESSES WITH WEB SERVICES IN GRID

Industrial Adoption of Automatically Extracted GUI Models for Testing

Performance Modeling in Industry A Case Study on Storage Virtualization

Multi-Paradigm Process Management

Journal of Engineering Research and Studies

Interaction Choreography Models in BPEL: Choreographies on the Enterprise Service Bus

Paul Brebner, Senior Researcher, NICTA,

Mining Process Models with Non-Free-Choice Constructs

A Contribution to Expert Decision-based Virtual Product Development

CMotion: A Framework for Migration of Applications into and between Clouds

Maximum performance, minimal risk for data warehousing

Performance Workload Design

Storage Intelligence in SSDs and Standards

Configurable and Collaborative Scientific Workflows

Pattern-based J2EE Application Deployment with Cost Analysis

Structural Patterns for Soundness of Business Process Models

Performance Modeling and Analysis of a Database Server with Write-Heavy Workload

Distributed Database Design

Performance Testing and Optimization in Web-Service Based Applications

Transforming LoadRunner Data into Information and Action

Delivering Quality in Software Performance and Scalability Testing

EFFECTIVE CONSTRUCTIVE MODELS OF IMPLICIT SELECTION IN BUSINESS PROCESSES. Nataliya Golyan, Vera Golyan, Olga Kalynychenko

BSc (Hons) Television and Broadcasting with Business Communication

Sample Exam Syllabus

Supporting the Workflow Management System Development Process with YAWL

Release & Deployment Management

Performance Monitoring for the Java Virtual Machine (JVM )

Programme Specification and Curriculum Map for BSc Honours Information Technology

An approach to grid scheduling by using Condor-G Matchmaking mechanism

Process Mining. ^J Springer. Discovery, Conformance and Enhancement of Business Processes. Wil M.R van der Aalst Q UNIVERS1TAT.

Linking BPMN, ArchiMate, and BWW: Perfect Match for Complete and Lawful Business Process Models?

Project Planning Tools. GANTT Chart. Chapter 7 Project Planning. GANTT Chart (Figure 7.3) CPM Chart (Figure 7.12) PERT Chart (Figure 7.

Stream Processing on GPUs Using Distributed Multimedia Middleware

BPMN PATTERNS USED IN MANAGEMENT INFORMATION SYSTEMS

The Data Access Handbook

Mike Chyi, Micro Focus Solution Consultant May 12, 2010

The Pitfalls of Deploying Solid-State Drive RAIDs

Release and Deployment Management Software

BPMN for REST. Cesare Pautasso Faculty of Informatics, USI Lugano, Switzerland

Figure 1: Illustration of service management conceptual framework

Process Execution Engine

Robin Hood: An Active Objects Load Balancing Mechanism for Intranet

A Business Process Services Portal

IBM Software Enabling business agility through real-time process visibility

Dashboard Reporting Business Intelligence

Transcription:

ON THE RO TO ENHMRKING PMN 2.0 WORKFLOW ENGINES Marigianna Skouradaki, ieter H. Roller, Frank Leymann Institute of rchitecture and pplication Systems University of Stuttgart Germany Vincenzo Ferme, esare Pautasso Faculty of Informatics University of Lugano (USI) Switzerland

What is a Workflow Engine? Workflow Engine Task ispatcher Process Navigator Users Job Executor ore Engine Service Invoker Web Service Transaction Manager Persistent Manager Instance atabase pplication Server MS 2

Many usiness Process Modeling/Execution Languages EP XPL PEL YWL PNML PMN 1992 1998 2002 2004 2008 3

PMN 2.0: Widely dopted Standard PMN 2.0 Jan 2011 ISO/IE 19510 PMN 2.0.2 Jan 2014 https://en.wikipedia.org/wiki/list_of_pmn_2.0_engines 4

Why do we need a benchmark? companies, developers 5

Why do we need a benchmark? companies, developers 1. How to choose the best engine according to the company requirements? 2. How to choose the best engine according to the company business process models? 5

Why do we need a benchmark? companies, developers 1. How to choose the best engine according to the company requirements? 2. How to choose the best engine according to the company business process models? 3. How to evaluate performance improvements during the engine development? 4. How to find out the engine bottlenecks? 5

Main hallenges in enchmarking PMN 2.0 Workflow Engines 6

Main hallenges in enchmarking PMN 2.0 Workflow Engines WORKLO HRTERIZTION ENHMRK EXEUTION 6

Main hallenges in enchmarking PMN 2.0 Workflow Engines 20% WORKLO HRTERIZTION 80% 1. efine the Workload Mix 2. efine the Load Functions ENHMRK EXEUTION 6

Main hallenges in enchmarking PMN 2.0 Workflow Engines 20% WORKLO HRTERIZTION 80% 1. efine the Workload Mix 2. efine the Load Functions Engine Users lient Engine x Engine Web Services ENHMRK EXEUTION 3. eal with engine-specific interfaces and PMN 2.0 customizations Instance atabase 4. synchronous execution of business processes 5. efine meaningful and reliable KPIs 6

1. efine the Workload Mix 7

1. efine the Workload Mix ontrol Flow ata Flow Events ctivities Task Types Execution ehavior G H E F I 7

1. efine the Workload Mix NUMER OF REL-WORL MOELS NUMER OF ENGINES SUPPORTING THE FETURE 8

1. efine the Workload Mix NUMER OF REL-WORL MOELS 200 0 NUMER OF ENGINES SUPPORTING THE FETURE 8

1. efine the Workload Mix NUMER OF REL-WORL MOELS 950 200 0 12 NUMER OF ENGINES SUPPORTING THE FETURE 8

1. efine the Workload Mix NUMER OF REL-WORL MOELS 950 800 700 600 400 200 0 F 2 4 5 8 10 12 NUMER OF ENGINES SUPPORTING THE FETURE 8

2. efine the Load Functions Start Events Workflow Engine Users Users Start Web Service pplication Server Instance atabase Web Services MS 9

3. eal with engine-specific interfaces and PMN 2.0 customizations Loading river Workflow Engine pplication Server Users Web Service Instance atabase MS 10

4. synchronous execution of processes Start Loading river Workflow Engine pplication Server Users Web Service Instance atabase MS 11

4. synchronous execution of processes Start Loading river End Workflow Engine Users Web Service pplication Server Instance atabase MS 11

The enchflow Project esign the first benchmark to assess and compare the performance of Workflow Engines that are compliant with usiness Process Model and Notation 2.0 (PMN 2.0) standard 20% 80% Engine Users lient Engine Engine Web Services Instance atabase 12

1. efine the Workload Mix E F G H REL-WORL PROESSES What we need: even more (anonymized) real-world PMN 2.0 process models 13

1. efine the Workload Mix Skouradaki et al. [SOSE2015] Graph Matching a1 a2 E F G a3 a6 a5 H a4 REL-WORL PROESSES REOURRING STRUTURES What we need: even more (anonymized) real-world PMN 2.0 process models 13

1. efine the Workload Mix Skouradaki et al. [SOSE2015] Graph Matching Selection riteria a1 a2 E F G a3 a6 a5 H a4 REL-WORL PROESSES REOURRING STRUTURES What we need: even more (anonymized) real-world PMN 2.0 process models 13

1. efine the Workload Mix Skouradaki et al. [SOSE2015] Graph Matching Selection riteria a1 a2 omposition riteria 50% a1 a2 E F G a3 a6 a5 50% a3 a5 H a4 REL-WORL PROESSES REOURRING STRUTURES WORKLO MIX What we need: even more (anonymized) real-world PMN 2.0 process models 13

Enabling the enchmark Execution Loading river Workflow Engine pplication Server Users Web Service Instance atabase MS 14

Enabling the enchmark Execution harness Faban Faban rivers Workflow Engine Users pplication Server Web Service Loading Functions Instance atabase MS 15

Enabling the enchmark Execution Faban harness Faban rivers Workflow Engine MS Web Service Loading Functions 1. Flexible deployment 2. Flexible HW Resources 3. Frozen Initial ondition Servers ocker ontainers 16

Enabling the enchmark Execution harness Faban rivers Workflow Engine MS Faban + 17

Enabling the enchmark Execution harness Workflow Engine Faban rivers MS Faban + 1. utomatically deploy and start the benchmark environment; 17

Enabling the enchmark Execution harness Workflow Engine Faban rivers MS Faban + 1. utomatically deploy and start the benchmark environment; 2. utomatically deploy the workload mix; 17

Enabling the enchmark Execution harness Workflow Engine Faban rivers MONITOR MS Faban + 1. utomatically deploy and start the benchmark environment; 2. utomatically deploy the workload mix; 3. etermine when the benchmark ends; 17

Enabling the enchmark Execution Workflow Faban rivers harness MONITOR Engine MS OLLETORS Instance atabase Faban + 1. utomatically deploy and start the benchmark environment; 2. utomatically deploy the workload mix; 3. etermine when the benchmark ends; 4. ollect the execution and process logs. 17

The enchflow Project Next Steps Release the first prototype of the enchmark environment» Yes: bstract the Interaction with the Engines; utomatic eploy and Undeploy of the S.U.T.; Execution and Process Log Gathering» No: utomatic Generation of rivers; Users, Web Services and External atching usiness Events Release the first prototype of the Workload Mix synthesizer First Experiments with KPIs efinition and omputation ollect More Process Models and Process Execution Logs enchflow Project: http://design.inf.usi.ch/research/projects/benchflow 18

KUP SLIES ited Works; Related Works. Marigianna Skouradaki, ieter H. Roller, Frank Leymann Institute of rchitecture and pplication Systems University of Stuttgart Germany Vincenzo Ferme, esare Pautasso Faculty of Informatics University of Lugano (USI) Switzerland

ited Works [SOSE2015] Skouradaki, Marigianna; Goerlach, Katharina; Hahn, Michael; Leymann, Frank. pplication of Sub-Graph Isomorphism to Extract Reoccurring Structures from PMN 2.0 Process Models. In Proceedings of 9th International IEEE Symposium on Service-Oriented System Engineering (SOSE 2015). San Francisco ay, US, March 30 - pril 3, 2015. (to appear) MS 20

Related Works ctive Endpoints Inc. ssessing ctivevos performance, 2011. http://www.activevos.com/ content/developers/ technical_notes/assessing_activevos_performance.pdf.. ianculli, W. inder, and M. L. rago. SOench: Performance evaluation of service-oriented middleware made easy. In Proc. of ISE 10 - Volume 2, pages 301 302, 2010. J. ardoso. usiness process control-flow complexity: Metric, evaluation, and validation. International Journal of Web Services Research, 5(2):49 76, 2008. G. in, K.-P. Eckert, and I. Schieferdecker. workload model for benchmarking PEL engines. In Proc. of ISTW 08, pages 356 360, 2008. M. umas, L. Garćıa-añuelos, and R. M. ijkman. Similarity search of business process models. IEEE ata Eng. ull., 32(3):23 28, 2009. J. Gray. The enchmark Handbook for atabase and Transaction Systems. Morgan Kaufmann, 2nd edition, 1992. G. Hackmann, M. Haitjema,. Gill, and G.-. Roman. Sliver: PEL workflow process execution engine for mobile devices. In Proc. of ISO 06, pages 503 508. Springer, 2006. S. Harrer, J. Lenhard, and G. Wirtz. PEL conformance in open source engines. In Proc. of SO 12, pages 1 8, 2012. MS 21

Related Works K. Huppler. The art of building a good benchmark. In Performance Evaluation and enchmarking, pages 18 30. Springer, 2009. Intel and ape lear. PEL scalability and performance testing. White paper, 2007. F. Leymann. Managing business processes via workflow technology. In Proc. of VL 2001, pages 729, 2001.. Liu, Q. Li, L. Huang, and M. Xiao. Facts: framework for fault-tolerant composition of transactional web services. IEEE Trans. on Services omputing, 3(1):46 59, 2010. J. Mendling. Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for orrectness. Springer, 2008. I. Molyneaux. The rt of pplication Performance Testing: Help for Programmers and Quality ssurance. O Reilly, 2009. M. Z. Muehlen and J. Recker. How much language is enough? theoretical and practical use of the business process modeling notation. In Proc. of ise 08, pages 465 479, 2008.. Röck and S. Harrer. Literature survey of performance benchmarking approaches of PEL engines. Technical report, Otto-Friedrich University of amberg, 2014.. H. Roller. Throughput Improvements for PEL MS Engines: Implementation Techniques and Measurements applied in SWoM. Ph thesis, University of Stuttgart, 2013. 22

Related Works N. Russell, W. M. van der alst, and. Hofstede. ll that glitters is not gold: Selecting the right tool for your PM needs. utter IT Journal, 20(11):31 38, 2007.. Schumm,. Karastoyanova, O. Kopp, F. Leymann, M. Sonntag, and S. Strauch. Process fragment libraries for easier and faster development of process-based applications. SSI, 2(1):39 55, 2011. M. Skouradaki,. Roller,. Pautasso, and F. Leymann. PELanon: nonymizing PEL processes. In Proc. of ZEUS 14, pages 9 15, 2014. Sun Microsystems. enchmarking PEL service engine, 2007. http://wiki.open-esb.java.net/ Wiki.jsp?page=pelPerformance.html.. Wetzstein, P. Leitner, F. Rosenberg, I. randic, S. ustdar, and F. Leymann. Monitoring and analyzing influential factors of business process performance. In Proc. of EO 09, pages 141 150, 2009. MS 23