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Process-Oriented Dependability

Posted by: Architecture and Analytics Platforms Team

June 6, 2018

Process-Oriented Dependability

Overview

Gartner has stated “Through 2015, 80% of outages impacting mission-critical services will be caused by people and process issues, and more than 50% of those outages will be caused by change/configuration/release integration and hand-off issues.” Our vision is make a dramatic reduction in these numbers for consumers of cloud services.

This is difficult because the consumer has limited visibility and control over the cloud environment. Predicting and controlling reliability and performance of applications must rely on the visibility and control granted to the consumer by the providers of the cloud.

Our approach relies on creating a process model for each operations process and using that model to guide near real time detection, diagnosis, and recovery from errors in the execution of the process.

Dependable Cloud Operations

Demos

Please find the videos about POD-Discovery and POD-Viz as below (full-screen watching recommended):

 

Posters

Please refer to the following linked posters for details.

Releases

Two components of the POD framework are publicly available and their source code can be found here.

  • POD-CCaaS: The POD Conformance Checking Service provides functionality to investigate whether a sequence of activities that is observed during runtime deviates from the expected behavior. In this regard, the service provides functionality to analyze if the observed order of the activities conforms to a predefined model and if the execution of the activities is within the expected time frame.
  • POD-Assertion Evaluation: The Assertion Evaluation can be used to examine the impact of the process execution on its environment. In particular, the process execution can be monitored with regard to assertions that are defined offline and that refer to the state of the environment in which the process is executed.

Publications on POD, business process management, and process mining

  • Contextual anomaly detection for a critical industrial system based on logs and metrics
    Mostafa Farshchi, Ingo Weber, Raffaele Della Corte, Antonio Pecchia, Marcello Cinque, Jean-Guy Schneider, and John Grundy
    EDCC’18: European Dependable Computing Conference, short paper, Iasi, Romania, September 2018
  • AB Testing for process versions with contextual multi-armed bandit algorithms
    Suhrid Satyal, Ingo Weber, Helen Paik, Claudio Di Ciccio, and Jan Mendling
    CAISE’18: International Conference on Advanced Information Systems Engineering, Tallinn, Estonia, June 2018
  • Improving the reliability in predictive process monitoring
    Christopher Klinkmüller, Nick van Beest, and Ingo Weber
    CAISE Forum’18: International Conference on Advanced Information Systems Engineering, Forum Track, Tallinn, Estonia, June 2018
  • AB-BPM: Performance-driven instance routing for business process improvement
    Suhrid Satyal, Ingo Weber, Helen Paik, Claudio Di Ciccio, and Jan Mendling
    BPM’17: International Conference on Business Process Management, Barcelona, Spain, September 2017
  • Analyzing control flow information to improve the effectiveness of process model matching techniques
    Christopher Klinkmüller and Ingo Weber
    Decision Support Systems, 100:6-14, August 2017
  • Rollback mechanisms for cloud management APIs using AI planning
    Suhrid Satyal, Ingo Weber, Len Bass, and Min Fu
    IEEE Transactions on Dependable and Secure Computing (TDSC), accepted July 2017
  • Metric selection and anomaly detection for cloud operations using log and metric correlation analysis
    Mostafa Farshchi, Jean-Guy Schneider, Ingo Weber, and John Grundy
    Journal of Systems and Software, April 2017.
  • R2C: Robust Rolling-Upgrade in Clouds
    Daniel Sun, Alan Fekete, Vincent Gramoli, Guoqiang Li, Xiwei Xu, and Liming Zhu
    IEEE Transactions on Dependable and Secure Computing, (32.3) 2016.
  • Behavioral Classification of Business Process Executions at Runtime
    Nick van Beest, Ingo Weber
    PRAISE 2016, Rio de Janeiro, Brazil, September, 2016.
  • [PDF]Process-oriented non-intrusive recovery for sporadic operations on cloud
    Min Fu, Liming Zhu, Ingo Weber, Len Bass, Anna Liu and Sherry Xu
    DSN 2016, Toulouse, France, July, 2016.
  • [PDF]Developing dependable and secure cloud applications
    Ingo Weber, Surya Nepal and Liming Zhu
    IEEE Internet Computing, Volume 20 Number 3, pp. 74-79, May, 2016. (Re-published in the digest magazine IEEE Computing Edge, July, 2016)
  • [PDF]Anomaly detection of cloud application operations using log and cloud metric correlation analysis
    Mostafa Farshchi, Jean-Guy Schneider, Ingo Weber and John GrundyExperience report
    ISSRE 2015, pp. 24-34, Washington DC, USA, November, 2015.
  • [PDF]Error diagnosis of cloud application operation using bayesian networks and online optimisatio
    Sherry Xu, Liming Zhu, Daniel Sun, An Binh Tran, Ingo Weber, Min Fu and Len Bass
    EDCC2015, Paris, France, September, 2015.
  • [PDF]CCaaS: Online conformance checking as a service
    Ingo Weber, Andreas Rogge-Solti, Chao Li and Jan Mendling
    BPM 2015, Demo Track, Innsbruck, Austria, August, 2015.
  • [PDF]Discovering and visualizing operations processes with POD-Discovery and POD-Viz
    Ingo Weber, Chao Li, Len Bass, Sherry Xu and Liming Zhu
    DSN 2015, Rio de Janeiro, Brazil, June, 2015.
  • [PDF]Mining processes with multi-instantiation
    Ingo Weber, Mostafa Farshchi, Jan Mendling and Jean-Guy Schneider
    ACM SAC 2015, Salamanca, Spain, April, 2015.
  • [PDF]Recovery for failures in rolling upgrade on clouds
    Min Fu, Liming Zhu, Len Bass and Anna Liu
    DCDV 2014, Atlanta GA, USA, June, 2014.
  • [PDF]POD-diagnosisError diagnosis of sporadic operations on cloud applications.
    Sherry Xu, Liming Zhu, Ingo Weber, Len Bass and Daniel Sun
    DSN 2014, Atlanta GA, USA, June, 2014.
  • [PDF]A recoverability-oriented analysis for operations on cloud applications.
    Min Fu, Liming Zhu, Len Bass and Sherry Xu
    WICSA 2014, Sydney, Australia, April, 2014.
  • [PDF]Detecting cloud provisioning errors using an annotated process model.
    Sherry Xu, Ingo Weber, Hiroshi Wada, Len Bass, Liming Zhu and Steve Teng
    MW4NextGen’13, Beijing, China, December, 2013.