This book constitutes the refereed proceedings of the 8th IFIP WG 2.14 European Conference on Service-Oriented and Cloud Computing, ESOCC 2020, held in Heraklion, Crete, Greece, in September 2020.

The 6 full and 8 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The main event mapped to the main research track which focused on the presentation of cutting-edge research in both the service-oriented and cloud computing areas. In conjunction, an industrial track was also held attempting to bring together academia and industry through showcasing the application of service-oriented and cloud computing research, especially in the form of case studies, in the industry.

The chapters 'Identification of Comparison Key Elements and their Relationships for Cloud Service Selection' and 'Technology-Agnostic Declarative Deployment Automation of Cloud Applications' are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Inhalt

Formal Methods.- Testing conformance in multi-component enterprise application management.- Formalizing Event-Driven Behavior of Serverless Applications.- Probabilistic Verification of Outsourced Computation Based on Novel Reversible PUFs.- Cloud Service and Platform Selection.- Multiplayer game backends: A Comparison of commodity cloud-based approaches.- Are Cloud Platforms Ready for Multi-Cloud?.- Identification of Comparison Key Elements and their Relationships for Cloud Service Selection.- Deployment and Workflows.- Deployable Self-Contained Workflow Models.- Technology-Agnostic Declarative Deployment Automation of Cloud Applications.- Blockchain-Based Healthcare Workflows in Federated Hospital Clouds.- Monitoring.- Monitoring Behavioral Compliance with Architectural Patterns based on Complex Event Processing.- Towards Real-Time Monitoring of Data Centers using Edge Computing.- Modeling Users' Performance: Predictive Analytics in an IoT Cloud Monitoring System.- Data Distribution and Analytics.- Multi-Source Distributed System Data for AI-powered Analytics.- Blockchain- and IPFS-based Data Distribution for the Internet of Things.