Towards Automated and Optimized Security Orchestration in Cloud SLA

In cloud computing, providers pool their resources and make them available to customers. Next-generation computer scientists are flocking to the cutting-edge field of cloud computing for their research and exploration of uncharted territory. There are still several barriers that cloud service providers must overcome in order to provide cloud services in accordance with service level agreements. Each cloud service provider aspires to achieve maximum performance as per Service Level Agreements (SLAs), and this is especially true when it comes to the delivery of services. A cloud service level agreement (SLA) guarantees that cloud service providers will satisfy the needs of large businesses and offer their clients with a specified list of services. The authors offer a web service level agreement–inspired approach for cloud service agreements. We adopt patterns and antipatterns to symbolize the best and worst practices of OCCI (Open Cloud Computing Interface Standard), REST (Representational State Transfer), and TOSCA (Topology and Orchestration Specification for Cloud Applications) with DevOps solutions, all of which API developers should bear in mind when designing APIs. When using this method, everything pertaining to the cloud service, from creation to deployment to measurement to evaluation to management to termination, may be handled mechanically. When distributing resources to cloud apps, our system takes into account the likelihood of SLA breaches and responds by providing more resources if necessary. We say that for optimal performance, our suggested solution should be used in a private cloud computing setting. As more and more people rely on cloud computing for their day-to-day workloads, there has been a corresponding rise in the need for efficient orchestration and management strategies that foster interoperability

Ecosystem synergies, change and orchestration

This thesis investigates ecosystem synergies, change, and orchestration. The research topics are motivated by my curiosity, a fragmented research landscape, theoretical gaps, and new phenomena that challenge extant theories. To address these motivators, I conduct literature reviews to organise existing studies and identify their limited assumptions in light of new phenomena. Empirically, I adopt a case study method with abductive reasoning for a longitudinal analysis of the Alibaba ecosystem from 1999 to 2020. My findings provide an integrated and updated conceptualisation of ecosystem synergies that comprises three distinctive but interrelated components: 1) stack and integrate generic resources for efficiency and optimisation, 2) empower generative changes for variety and evolvability, and 3) govern tensions for sustainable growth. Theoretically grounded and empirically refined, this new conceptualisation helps us better understand the unique synergies of ecosystems that differ from those of alternative collective organisations and explain the forces that drive voluntary participation for value co-creation. Regarding ecosystem change, I find a duality relationship between intentionality and emergence and develop a phasic model of ecosystem sustainable growth with internal and external drivers. This new understanding challenges and extends prior discussions on their dominant dualism view, focus on partial drivers, and taken-for-granted lifecycle model. I propose that ecosystem orchestration involves systematic coordination of technological, adoption, internal, and institutional activities and is driven by long-term visions and adjusted by re-visioning. My analysis reveals internal orchestration's important role (re-envisioning, piloting, and organisation architectural reconfiguring), the synergy and system principles in designing adoption activities, and the expanding arena of institutional activities. Finally, building on the above findings, I reconceptualise ecosystems and ecosystem sustainable growth to highlight multi-stakeholder value creation, inclusivity, long-term orientation and interpretative approach. The thesis ends with discussing the implications for practice, policy, and future research.Open Acces