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Orchestrating complex application architectures in heterogeneous clouds
Caballer M., Zala S., García Á., Moltó G., Fernández P., Velten M. Journal of Grid Computing16 (1):3-18,2018.Type:Article
Date Reviewed: Aug 19 2019

The authors present INDIGO-DataCloud for deploying cloud applications across multiple cloud management platforms (CMPs) that require complex topologies and operational requirements, such as auto scaling resources according to dynamic application needs. The evolution of standards for cloud technologies and frameworks is often not at the same pace as the solutions brought forth, which limits the potential of a given cloud infrastructure and often limits/decreases the functionality and flexibility of the solutions developed. The authors lament that cloud solution providers do not allow scientific users span over several different infrastructures.

To address the above, and to address the gaps in utilizing private clouds for scientific application users, the authors present an overview of Indigo-DataCloud, which attempts to orchestrate computing resources across heterogeneous cloud infrastructures to deliver scientific applications to end users. They introduce a high-level architecture for such orchestration and describe the details that led to the technological choices. The authors also articulate a need for promoting the use of open standards (TOSCA in particular), and even discuss earlier efforts in achieving such open-source orchestration. They indicate that such efforts failed due to the need for their own CMPs. Their proposed solution is framed as a vertical slice cutting across infrastructure, platform, and software services, with the following proposed advancements: advanced scheduling strategies based on preemptive instances using two popular CMPs to provide for heterogeneity (infrastructure as a service, IaaS); adopting service-level agreement (SLA)-based orchestration components supportive of multi-cloud deployments (platform as a service, PaaS); and high-level REST interfaces to facilitate the heterogeneous use of computing infrastructures (software as a service, SaaS).

In summary, the paper presents a good orchestration solution over heterogeneous clouds. While it is a good window into the pitfalls of present-day commercial solutions, it also, albeit accidentally, highlights the inherent complexity in trying to be everything to everyone. For example, the proposed approach is also limited by the authors’ technological choices; instead of being bound by one CMP as in other such open-source efforts, it is bound by two. Whether this additional layer of complexity is needed for a practical application that has specific goals is questionable. Nevertheless, researchers and developers can use this well-written paper for understanding the tradeoffs between fit for purpose versus general-purpose needs, as well as for designing applications that demand heterogeneity as a fundamental requirement.

Reviewer:  Srini Ramaswamy Review #: CR146661 (1911-0387)
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