Approaches for Service Deployment
IEEE Internet Computing
Mulini: an automated staging framework for QoS of distributed multi-tier applications
Proceedings of the 2007 workshop on Automating service quality: Held at the International Conference on Automated Software Engineering (ASE)
Dependency-aware maintenance for highly available service-oriented grid
Journal of Systems and Software
Rapid application configuration in Amazon cloud using configurable virtual appliances
Proceedings of the 2011 ACM Symposium on Applied Computing
Service research challenges and solutions for the future internet
Towards automated deployment of built-to-order systems
DSOM'05 Proceedings of the 16th IFIP/IEEE Ambient Networks international conference on Distributed Systems: operations and Management
Towards formalising installation and reconfiguration tasks of AADL architecture
International Journal of Communication Networks and Distributed Systems
| Hi-index | 0.00 |
IT today is driven by the trend of increasing scale and complexity. Utility and Grid computing models, PlanetLab, and traditional data centers, are reaching the scale of thousands of computers. Installed software consists of dozens of interdependent applications and services. As the complexity and scale of these systems continues to grow, it becomes increasingly difficult to administer and manage them. At the same time, the service deployment technologies are still based on scripts and configuration files with minimal ability to express dependencies, to document and to verify configurations. This results in hard-to-use and erroneous system configurations. Language- and model-based tools, such as SmartFrog and Radia, are proposed for addressing these deployment challenges, but it is unclear whether they are beneficial over traditional solutions. In this paper, we quantitatively compare manual, script-, language-, and model-based deployment solutions as a function of scale, complexity, and susceptibility to change. We also qualitatively compare them in terms of expressiveness and barrier to first use. We demonstrate that script-based solutions are well matched for large scale deployments, language-based for services of large complexity, and model-based for dynamic changes to the design. Finally, we offer a table summarizing rules of thumb regarding which solution to use in which case, subject to deployment needs.