On Autonomic Platform-as-a-Service: Characterisation and Conceptual Model

In this position paper, we envision a Platform-as-a-Service conceptual and architectural solution for large-scale and data intensive applications. Our architectural approach is based on autonomic principles, therefore, its ultimate goal is to reduce human intervention, the cost, and the perceived complexity by enabling the autonomic platform to manage such applications itself in accordance with high-level policies. Such policies allow the platform to (i) interpret the application specifications; (ii) to map the specifications onto the target computing infrastructure, so that the applications are executed and their Quality of Service (QoS), as specified in their SLA, enforced; and, most importantly, (iii) to adapt automatically such previously established mappings when unexpected behaviours violate the expected. Such adaptations may involve modifications in the arrangement of the computational infrastructure, i.e. by re-designing a different communication network topology that dictates how computational resources interact, or even the live-migration to a different computational infrastructure. The ultimate goal of these challenges is to (de)provision computational machines, storage and networking links and their required topologies in order to supply for the application the virtualised infrastructure that better meets the SLAs. Generic architectural blueprints and principles have been provided for designing and implementing an autonomic computing system. We revisit them in order to provide a customised and specific view for PaaS platforms and integrate emerging paradigms such as DevOps for automate deployments, Monitoring as a Service for accurate and large-scale monitoring, or well-known formalisms such as Petri Nets for building performance models.

[1]  Frank Leymann,et al.  Deployment Aggregates - A Generic Deployment Automation Approach for Applications Operated in the Cloud , 2014, 2014 IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations.

[2]  Dimosthenis Kyriazis,et al.  Platform-as-a-Service Architecture for Real-Time Quality of Service Management in Clouds , 2010, 2010 Fifth International Conference on Internet and Web Applications and Services.

[3]  Frank Leymann,et al.  DevOpSlang - Bridging the Gap between Development and Operations , 2014, ESOCC.

[4]  Jennifer Rexford,et al.  The "Platform as a Service" Model for Networking , 2010, INM/WREN.

[5]  Rafael Tolosana-Calasanz,et al.  Towards Petri Net-Based Economical Analysis for Streaming Applications Executed Over Cloud Infrastructures , 2014, GECON.

[6]  Marco Aiello,et al.  Service-Oriented and Cloud Computing , 2012, Lecture Notes in Computer Science.

[7]  Shicong Meng,et al.  Resource-Aware Application State Monitoring , 2012 .

[8]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[9]  Salim Hariri,et al.  Autonomic Computing: An Overview , 2004, UPP.

[10]  Pascal Fradet,et al.  Unconventional Programming Paradigms , 2008 .

[11]  Frank Leymann,et al.  Standards-Based DevOps Automation and Integration Using TOSCA , 2014, 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.

[12]  Jeffrey O. Kephart,et al.  An architectural approach to autonomic computing , 2004 .

[13]  David Sinreich,et al.  An architectural blueprint for autonomic computing , 2006 .

[14]  Julie A. McCann,et al.  A survey of autonomic computing—degrees, models, and applications , 2008, CSUR.

[15]  G. Alonso,et al.  Parallel computing patterns for Grid workflows , 2006, 2006 Workshop on Workflows in Support of Large-Scale Science.

[16]  Dinkar Sitaram,et al.  Platform as a Service , 2012, CloudCom 2012.

[17]  Luiz Fernando Bittencourt,et al.  Cloud Federation: Characterisation and Conceptual Model , 2014, 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.

[18]  Shicong Meng,et al.  Enhanced Monitoring-as-a-Service for Effective Cloud Management , 2013, IEEE Transactions on Computers.

[19]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[20]  Dan C. Marinescu,et al.  Cloud Computing: Theory and Practice , 2013 .