CloudsStorm: An Application-Driven Framework to Enhance the Programmability and Controllability of Cloud Virtual Infrastructures

  • Huan ZhouEmail author
  • Yang Hu
  • Jinshu Su
  • Cees de Laat
  • Zhiming Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10967)


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.


  1. 1.
    Wettinger, J., et al.: Streamlining DevOps automation for Cloud applications using TOSCA as standardized metamodel. FGCS 56, 317–332 (2016)CrossRefGoogle Scholar
  2. 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
  3. 3.
    Caballer, M., de Alfonso, C., Moltó, G., Romero, E., Blanquer, I., García, A.: Codecloud: a platform to enable execution of programming models on the clouds. J. Syst. Softw. 93, 187–198 (2014)CrossRefGoogle Scholar
  4. 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
  5. 5.
    Diaz-Montes, J., AbdelBaky, M., Zou, M., Parashar, M.: CometCloud: enabling software-defined federations for end-to-end application workflows. IEEE Internet Comput. 19(1), 69–73 (2015)CrossRefGoogle Scholar
  6. 6.
    Jeferry, K., Kousiouris, G., Kyriazis, D., Altmann, J., Ciuffoletti, A., Maglogiannis, I., Nesi, P., Suzic, B., Zhao, Z.: Challenges emerging from future cloud application scenarios. Procedia Comput. Sci. 68, 227–237 (2015)CrossRefGoogle Scholar
  7. 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
  8. 8.
    Caballer, M., Blanquer, I., Moltó, G., de Alfonso, C.: Dynamic management of virtual infrastructures. J. Grid Comput. 13(1), 53–70 (2015)CrossRefGoogle Scholar
  9. 9.
    Zhao, Z., Grosso, P., Van der Ham, J., Koning, R., De Laat, C.: An agent based network resource planner for workflow applications. Multiagent Grid Syst. 7(6), 187–202 (2011)CrossRefGoogle Scholar
  10. 10.
    Wang, J., Taal, A., Martin, P., Hu, Y., Zhou, H., Pang, J., de Laat, C., Zhao, Z.: Planning virtual infrastructures for time critical applications with multiple deadline constraints. Future Gener. Comput. Syst. 75, 365–375 (2017)CrossRefGoogle Scholar
  11. 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). Scholar
  12. 12.
    Ouyang, X., Garraghan, P., Primas, B., McKee, D., Townend, P., Xu, J.: Adaptive speculation for efficient internetware application execution in clouds. ACM Trans. Internet Technol. (TOIT) 18(2), 15 (2018)CrossRefGoogle Scholar
  13. 13.
    Zhao, Z., Van Albada, D., Sloot, P.: Agent-based flow control for HLA components. Simulation 81(7), 487–501 (2005)CrossRefGoogle Scholar
  14. 14.
    Baldin, I., et al.: ExoGENI: a multi-domain infrastructure-as-a-service testbed. In: McGeer, R., Berman, M., Elliott, C., Ricci, R. (eds.) The GENI Book, pp. 279–315. Springer, Cham (2016). Scholar
  15. 15.
    Kang, J.-M., Lin, T., Bannazadeh, H., Leon-Garcia, A.: Software-defined infrastructure and the SAVI testbed. In: Leung, V.C.M., Chen, M., Wan, J., Zhang, Y. (eds.) TridentCom 2014. LNICST, vol. 137, pp. 3–13. Springer, Cham (2014). Scholar
  16. 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. 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

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Huan Zhou
    • 1
    • 2
    Email author
  • Yang Hu
    • 1
  • Jinshu Su
    • 2
  • Cees de Laat
    • 1
  • Zhiming Zhao
    • 1
  1. 1.Informatics InstituteUniversity of AmsterdamAmsterdamThe Netherlands
  2. 2.School of Computer ScienceNational University of Defense TechnologyChangshaChina

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