CloudsStorm: An Application-Driven Framework to Enhance the Programmability and Controllability of Cloud Virtual Infrastructures
Most current IaaS (Infrastructure-as-a-Service) clouds provide dedicated virtual infrastructure resources to cloud applications with only limited programmability and controllability, which enlarges the management gap between infrastructures and applications. Traditional DevOps (development and operations) approaches are not suitable in today’s cloud environments, because of the slow, manual and error-prone collaboration between developers and operations personnel. It is essential to involve the operation into the cloud application development phase, which needs to make the infrastructure able to be controlled by the application directly. Moreover, each of these cloud providers offers their own set of APIs to access the resources. It causes the vendor lock-in problem for the application when managing its infrastructure across federated clouds or multiple data centers. To mitigate this gap, we have designed CloudsStorm, an application-driven DevOps framework that allows the application directly program and control its infrastructure. In particular, it provides multi-level programmability and controllability according to the applications’ specifications. We evaluate it by comparing its functionality to other proposed solutions. Moreover, we implement an extensible TSV-Engine, which is the core component of CloudsStorm for managing infrastructures. It is the first to be able to provision a networked infrastructure among public clouds. At last, we conduct a set of experiments on actual clouds and compare with other related DevOps tools. The experimental results demonstrate our solution is efficient and outperforms others.
This research has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreements 643963 (SWITCH project), 654182 (ENVRIPLUS project) and 676247 (VRE4EIC project). The research is also partially funded by the COMMIT project. The author, Huan Zhou, is also sponsored by China Scholarship Council.
- 2.Keahey, K., Freeman, T.: Contextualization: providing one-click virtual clusters. In: IEEE Fourth International Conference on eScience 2008, pp. 301–308 (2008)Google Scholar
- 4.Dastjerdi, A.V., Garg, S.K., Rana, O.F., Buyya, R.: CloudPick: a framework for QoS-aware and ontology-based service deployment across clouds. Softw.: Pract. Exp. 45, 197–231 (2015)Google Scholar
- 7.Marshall, P., Tufo, H.M., Keahey, K., La Bissoniere, D., Woitaszek, M.: Architecting a large-scale elastic environment-recontextualization and adaptive cloud services for scientific computing. In: ICSOFT (2012)Google Scholar
- 11.Hu, Y., Wang, J., Zhou, H., Martin, P., Taal, A., de Laat, C., Zhao, Z.: Deadline-aware deployment for time critical applications in clouds. In: Rivera, F.F., Pena, T.F., Cabaleiro, J.C. (eds.) Euro-Par 2017. LNCS, vol. 10417, pp. 345–357. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-64203-1_25CrossRefGoogle Scholar
- 16.Zhou, H., Wang, J., Hu, Y., Su, J., Martin, P., de Laat, C., Zhao, Z.: Fast resource co-provisioning for time critical applications based on networked infrastructures. In: IEEE International Conference on Cloud Computing, pp. 802–805 (2016)Google Scholar
- 17.Zhao, Z., Taal, A., Jones, A., Taylor, I., Stankovski, V., Vega, I.G., Hidalgo, F.J., Suciu, G., Ulisses, A., Ferreira, P.: A software workbench for interactive, time critical and highly self-adaptive cloud applications (SWITCH). In: 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 1181–1184. IEEE (2015)Google Scholar