Master Thesis MSTR-2019-52

BibliographySowoidnich, Yannic: Concept for executing management operations on components of application instances.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Master Thesis No. 52 (2019).
60 pages, english.
Abstract

A large field of technologies exist for orchestrating cloud applications. Many of them focus on automated deployment techniques, rather than continous management of application instances. Executing operations for deploying applications is different from executing management operations, due to their dependencies to the application state. Proper state management is important to guarantee valid execution of management operations. Cloud providers such as Amazon have embedded functions for managing cloud applications, but they come with major drawbacks. They increase vendor-dependency and they do not support multi-cloud deployments. Technologies like Chef, Puppet or Terraform work with declarative process models, which cannot be used for non-state-changing operations and they mostly only allow simple operations. It is impossible to execute more customized fine grained operations with those technologies. Also, most of these management tools only support executing operations on the whole application, not on specific components of the application. The objective of this thesis is to find a way for executing management operations on running application instances by combining the information of the deployment model with the instance model of the application. The conceptual approach proposed in this thesis will consider and solve above addressed issues, as well as ensuring proper state management of application instances. The practical feasibility of this concept is validated by a prototypical implementation based on the TOSCA standard and the OpenTOSCA ecosystem.

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Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Leymann, Prof. Frank; Saatkamp, Karoline
Entry dateOctober 23, 2019
   Publ. Institute   Publ. Computer Science