Cloud Computing helps to efficiently utilize the abundance of computing resources in large data centers. It enables interested parties to deploy their services in data centers while the hardware infrastructure is maintained by the cloud provider. Cloud computing is interesting in particular as it enables automation of service deployment and management processes. However, the more complex the service structure becomes, the more complex deployment and management automation of all its parts can become. To this end, the concept of service orchestration is introduced to streamline service deployment and management processes. Orchestration enables the definition and execution of complex automation workflows targeted to provision computing infrastructure, deploy needed service features, and provide management support. In particular, the orchestration process enables the deployment and enforcement of security and compliance mechanisms in the context of systems where sensitive data is being processed. 

This thesis investigates the orchestration process as a uniform approach to deploy and manage network services and required security and compliance mechanisms. To this end, we investigate different use-cases where the orchestration process is applied to address specific requirements towards security and compliance. This thesis includes two parts. In the first part, we focus on centralized orchestration mechanisms, where all activities are performed from one trusted server. We explore the use-cases of a security testbed and collaborative AI engineering and investigate the advantages and limitations of orchestration mechanisms application in their context. In the second part, we shift towards the investigation of decentralized orchestration mechanisms. We employ blockchain technology as the main decentralization mechanism, exploring the advantages and limitations of its application in the context of digital marketplaces. We demonstrate that the shift towards blockchain-enabled orchestration enables the deployment and management of decentralized security mechanisms, ensuring compliant behavior of digital marketplace actors. 

The aim of this thesis is to advance the knowledge on the efficient design and evaluation of distributed marketplaces with an emphasis on trust and privacy. Distributed systems are an integral part of today's computing infrastructures, enabling multiple nodes to work towards a common goal. Although distributed, most of today's computational systems are still built with a centralized architecture, which assumes complete governance by a single organization. In the case of centralized marketplaces, the correct trade execution guarantees, \ie digital trust, and data privacy are provided centrally, containing all processes and operations within a single organization's boundaries. This puts the marketplace operator in a prime position to govern trade settlement conditions. However, trust issues are raised if more than one organization has to govern the marketplace. In such a case, trust and privacy are decentralized, and control is distributed among all organizations which are part of the marketplace system. Thus, a decentralized marketplace requires a robust and secure consensus mechanism, which enables digital trust while allowing organizations to process and store private data for further usage in trade settlements. 

This thesis investigates both centralized and decentralized marketplace architectures applied to use cases of AI artifacts and renewable energy trading. It begins with a study of a marketplace for Artificial Intelligence (AI) artifacts where multiple organizations collaborate on AI pipeline execution. The study defines a Secure Virtual Premise, which enables AI pipeline execution in a centralized marketplace governed by a trusted third party. The thesis continues with a survey of the telecommunication services marketplaces, where both centralized and decentralized architectures are discussed. In addition, the survey provides an in-depth investigation of blockchain technology as a main trust-enabling platform, providing distributed storage and data assurance to all processes in a decentralized marketplace. Having mapped the state-of-the-art, the research shifts towards an in-depth investigation of blockchain-based decentralized renewable energy marketplaces. The main aim of such a marketplace is to incentivize the widespread adoption of renewable energy sources, resulting in the decarbonization of electricity distribution systems. The designed marketplace enables automation and trusted execution of peer-to-peer (P2P) energy trade settlements in decentralized systems while preserving users' data privacy. Furthermore, the marketplace is aligned with the data and P2P energy trade regulations. The studies provide an in-depth requirements definition, system architecture, implementation, and performance evaluation of marketplaces based on two major blockchain platforms. The final study of this thesis provides the improvements towards the renewable energy marketplace model aiming at an enhancement of trust, privacy, and scalability.