Orchestrator conversation: Distributed management of cloud applications. Issue 6 (10th July 2018) - Sebrechts, Merlijn; Van Seghbroeck, Gregory; Wauters, Tim; Volckaert, Bruno; De Turck, Filip
Summary: Managing cloud applications is complex, and the current state of the art is not addressing this issue. The ever‐growing software ecosystem continues to increase the knowledge required to manage cloud applications at a time when there is already an IT skills shortage. Solving this issue requires capturing IT operation knowledge in software so that this knowledge can be reused by system administrators who do not have it. The presented research tackles this issue by introducing a new and fundamentally different way to approach cloud application management: a hierarchical collection of independent software agents, collectively managing the cloud application. Each agent encapsulates knowledge of how to manage specific parts of the cloud application, is driven by sending and receiving cloud models, and collaborates with other agents by communicating using conversations. The entirety of communication and collaboration in this collection is called the orchestrator conversation. A thorough evaluation shows the orchestrator conversation makes it possible to encapsulate IT operations knowledge that current solutions cannot, reduces the complexity of managing a cloud application, and happens inherently concurrent. The evaluation also shows that the conversation figures out how to deploy a single big data cluster in less than 100 milliseconds, which scales linearly to less than 10 seconds for 100 clusters, resulting in a minimal overhead compared with the deployment time of at least 20 minutes with the state of the art. Abstract : The orchestrator conversation simplifies model‐based management of cloud applications by giving system administrators tools to create design‐ and run‐time abstractions that hide underlying operational complexity. The orchestrator conversation consists of a hierarchical collection of independent software agents driven by cloud models that collectively manage a cloud application and collaborate to resolve service dependencies. Evaluations show it reduces complexity with a minimal overhead, <100 milliseconds for a single cluster, which scales well to <10 s for 100 clusters.