The essential deployment metamodel: a systematic review of deployment automation technologies

In recent years, a plethora of deployment technologies evolved, many following a declarative approach to automate the delivery of software components. Even if such technologies share the same purpose, they differ in features and supported mechanisms. Thus, it is difficult to compare and select deployment automation technologies as well as to migrate from one technology to another. Hence, we present a systematic review of declarative deployment technologies and introduce the essential deployment metamodel (EDMM) by extracting the essential parts that are supported by all these technologies. Thereby, the EDMM enables a common understanding of declarative deployment models by facilitating the comparison, selection, and migration of technologies. Moreover, it provides a technology-independent baseline for further deployment automation research.

[1]  Rajiv Ranjan,et al.  A Taxonomy and Survey of Cloud Resource Orchestration Techniques , 2017, ACM Comput. Surv..

[2]  Antonio Brogi,et al.  TosKer: A synergy between TOSCA and Docker for orchestrating multicomponent applications , 2018, Softw. Pract. Exp..

[3]  Archana Ganapathi,et al.  Why Do Internet Services Fail, and What Can Be Done About It? , 2002, USENIX Symposium on Internet Technologies and Systems.

[4]  Jeisson Vergara-Vargas,et al.  A model-driven deployment approach for scaling distributed software architectures on a cloud computing platform , 2017, 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS).

[5]  Gerhard Wickler,et al.  Automated Planning for Configuration Changes , 2011, LISA.

[6]  Antonio Brogi,et al.  Cloud Container Technologies: A State-of-the-Art Review , 2019, IEEE Transactions on Cloud Computing.

[7]  Wouter Joosen,et al.  A Survey of System Configuration Tools , 2010, LISA.

[8]  ChenPeter Pin-Shan.  The entity-relationship modeltoward a unified view of data , 1976 .

[9]  Sasko Ristov,et al.  Cloud portability standardization overview , 2015, 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[10]  Eoin Woods,et al.  Software Systems Architecture: Working with Stakeholders Using Viewpoints and Perspectives , 2005 .

[11]  Laurian M. Chirica,et al.  The entity-relationship model: toward a unified view of data , 1975, SIGF.

[12]  Oliver Kopp,et al.  Streamlining DevOps automation for Cloud applications using TOSCA as standardized metamodel , 2016, Future Gener. Comput. Syst..

[13]  Giuseppina Cretella,et al.  Defining Cloud Services Workflow: A Comparison between TOSCA and OpenStack Hot , 2015, 2015 Ninth International Conference on Complex, Intelligent, and Software Intensive Systems.

[14]  Thomas A. Limoncelli,et al.  Proceedings of the 25th international conference on Large Installation System Administration , 2011 .

[15]  Antonio Brogi,et al.  TOSCA in a Nutshell: Promises and Perspectives , 2014, ESOCC.

[16]  Frank Leymann,et al.  A GENTL Approach for Cloud Application Topologies , 2014, ESOCC.

[17]  Rudi Van Drunen.  Proceedings of the 24th international conference on Large installation system administration , 2010 .

[18]  Jez Humble,et al.  Continuous Delivery: Reliable Software Releases Through Build, Test, and Deployment Automation , 2010 .

[19]  Uwe Breitenbücher.  Eine musterbasierte Methode zur Automatisierung des Anwendungsmanagements , 2016 .

[20]  Oliver Kopp,et al.  OpenTOSCA - A Runtime for TOSCA-Based Cloud Applications , 2013, ICSOC.

[21]  Gerti Kappel,et al.  A Systematic Review of Cloud Modeling Languages , 2018, ACM Comput. Surv..

[22]  Yan Liu,et al.  Model Driven Deployment of Auto-Scaling Services on Multiple Clouds , 2018, 2018 IEEE International Conference on Software Architecture Companion (ICSA-C).

[23]  Oliver Kopp,et al.  Declarative vs . Imperative : Two Modeling Patterns for the Automated Deployment of Applications , 2017 .

[24]  Peter P. Chen.  The entity-relationship model: toward a unified view of data , 1975, VLDB '75.

[25]  Kief Morris,et al.  Infrastructure as Code: Managing Servers in the Cloud , 2016 .

[26]  Pavel Masek,et al.  Unleashing Full Potential of Ansible Framework: University Labs Administration , 2018, 2018 22nd Conference of Open Innovations Association (FRUCT).