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Optimizing the Integration of Agent-Based Cloud Orchestrators and Higher-Level Workloads

Abstract : The flexibility of cloud computing has put significant strain on operations teams. Manually installing and configuring applications in the cloud simply isn’t an option anymore. Configuration management automation solves the issue of getting a single application into a certain state automatically and reliably. However, the issue of automatic dependency management between multiple applications is still an “open, hard problem” according to researchers at Google. Agent-based modeling and orchestration tools like Juju solve the issue of getting from zero to a working set of correctly clustered and connected frameworks. The shortcomings of these state-of-the-art tools are that they don’t provide efficient ways to model and orchestrate workloads running on top of these frameworks. This paper presents a number of ways to deploy and orchestrate workloads with Juju, compares their performance and overhead, and suggests how this overhead can be minimized.
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https://hal.inria.fr/hal-01806071
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Submitted on : Friday, June 1, 2018 - 4:01:34 PM
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Long-term archiving on: : Sunday, September 2, 2018 - 3:49:06 PM

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Merlijn Sebrechts, Gregory Seghbroeck, Filip Turck. Optimizing the Integration of Agent-Based Cloud Orchestrators and Higher-Level Workloads. 11th IFIP International Conference on Autonomous Infrastructure, Management and Security (AIMS), Jul 2017, Zurich, Switzerland. pp.165-170, ⟨10.1007/978-3-319-60774-0_16⟩. ⟨hal-01806071⟩

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