Towards Monitoring Cloud Services using Models@run.time

Cloud computing represents a new trend to provide software services. In order to deliver these services there are certain quality levels that should be considered. The provided services need to comply with a set of contract terms and non-functional requirements specified by a service level agreement (SLA). In addition, to support the fulfillment of the SLA a monitoring process should be defined. This allows service providers to determine the actual quality level of services in the cloud. In this paper, we define a monitoring process for the usage of models at runtime, specifying lowand high-level nonfunctional requirements contained in a SLA. Models at runtime provide flexibility to the monitoring infrastructure due to their reflection mechanisms; the modification of non-functional requirements may dynamically change the monitoring computation, avoiding the need to adjust the monitoring infrastructure. In our approach, models at runtime are part of a monitoring middleware that interacts with cloud services; it retrieves data in the model at runtime, analyzes the information, and provides a report detailing the issues of non-compliance of non-functional requirements.

[1]  Gordon S. Blair,et al.  Models@ run.time , 2009, Computer.

[2]  Sahin Albayrak,et al.  Meta-Modeling Runtime Models , 2010, Models@run.time.

[3]  Wei-Tek Tsai,et al.  SaaS performance and scalability evaluation in clouds , 2011, Proceedings of 2011 IEEE 6th International Symposium on Service Oriented System (SOSE).

[4]  Luciano Baresi,et al.  The disappearing boundary between development-time and run-time , 2010, FoSER '10.

[5]  Antonello Calabrò,et al.  GLIMPSE: a generic and flexible monitoring infrastructure , 2011, EWDC '11.

[6]  Harry G. Perros,et al.  Service Performance and Analysis in Cloud Computing , 2009, 2009 Congress on Services - I.

[7]  David McPhee,et al.  Information Technology Infrastructure Library (ITIL®) , 2011, Encyclopedia of Information Assurance.

[8]  Martin Gogolla,et al.  Using Models at Runtime to Address Assurance for Self-Adaptive Systems , 2015, Models@run.time@Dagstuhl.

[9]  Paul Grefen,et al.  Clearing the sky : understanding SLA elements in cloud computing , 2013 .

[10]  Heiko Ludwig,et al.  The WSLA Framework: Specifying and Monitoring Service Level Agreements for Web Services , 2003, Journal of Network and Systems Management.

[11]  Gordon S. Blair,et al.  Summary of the 8th International Workshop on Models @ Run.time , 2013, MoDELS@Run.time.

[12]  Anacleto Correia,et al.  SLALOM: a Language for SLA specification and monitoring , 2011, ArXiv.

[13]  Nelly Bencomo,et al.  Requirements reflection: requirements as runtime entities , 2010, 2010 ACM/IEEE 32nd International Conference on Software Engineering.

[14]  Uwe Zdun,et al.  Systematic literature review of the objectives, techniques, kinds, and architectures of models at runtime , 2016, Software & Systems Modeling.

[15]  Antonello Calabrò,et al.  Towards a Model-Driven Infrastructure for Runtime Monitoring , 2011, SERENE.

[16]  Anacleto Correia,et al.  Model-Driven Service Level Management , 2010, AIMS.

[17]  Du Wan Cheun,et al.  A Quality Model for Evaluating Software-as-a-Service in Cloud Computing , 2009, 2009 Seventh ACIS International Conference on Software Engineering Research, Management and Applications.

[18]  César A. F. De Rose,et al.  CASViD: Application Level Monitoring for SLA Violation Detection in Clouds , 2012, 2012 IEEE 36th Annual Computer Software and Applications Conference.

[19]  Schahram Dustdar,et al.  Low level Metrics to High level SLAs - LoM2HiS framework: Bridging the gap between monitored metrics and SLA parameters in cloud environments , 2010, 2010 International Conference on High Performance Computing & Simulation.

[20]  Xavier Franch,et al.  Comprehensive Explanation of SLA Violations at Runtime , 2014, IEEE Transactions on Services Computing.