SUMMARYWith the rapid development and application of cloud computing, there exist plenty of clouds that are distributed on the open Internet, decentralized in the management, evolving with various services providing diverse functionalities and QoS. Moreover, because of the potential correlativity of cloud services and the dynamic of tenants' requirements, these services in multiple clouds are expected to be effectively managed in an autonomic and transparent way so that tenants can obtain continuous and efficient services. To this end, this paper proposes an approach based on self-organizing multi-agent system to achieving crossclouds services management, including the service provision at the tenant-end and services aggregation at the cloud-end. In this approach, the clouds services are managed by a series of autonomous agents that are capable of autonomously accessing managed services. They can interact with each other to obtain macro-level services aggregation in terms of self-organization to adapt to the changes of both tenants' requirements and cloud services. The paper details the architecture, mechanisms, and algorithms to implement the aggregation and provision of services in cross-clouds. We also develop relevant crossclouds services management platform called as CCloudMan, with which several experiments based on the public data sets have been conducted and the experimental results show the efficiency and usability of our proposed approach.

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With the features of high distribution in deployment and independence in running, the microservice systems that operate in heterogeneous infrastructures and open Internet environment are expected to be self-adaptive to adapt to various changes of both operating contexts and application requirements. This requires the adaptability of the microservice systems to be diverse and flexible, and independent of implementation technologies and platforms. This paper presents a reference architecture for self-adaptive microservice systems with the abilities of multi-layer controlled self-adaptations, including infrastructure-controlled layer and application-controlled layer. Such reference architecture presents a blueprint to cope with diverse changes from different levels in microservice systems and supports the interactions between layers. We have implemented a practical platform called SAMSP based on the reference architecture and Kubernetes and evaluated our approach using a sample. The experimental results are promising, and demonstrate the feasibility and effectiveness of our proposed reference architecture.