Ensuring high quality and safety of food products has become a key factor on one hand to protect and improve consumers health and, on the other one, to gain market share. For this reason, much effort in the last year has been devoted to the development of integrated and innovative Agriculture and Food (Agri-Food) supply chains management systems, which should be responsible, in addition to track and store orders and deliveries, to guarantee transparency and traceability of the food production and transformation process. In this paper, differently from traditional supply chains which are based on centralized systems, we propose a fully distributed approach, based on blockchain technology, to define a supply chain management system able to provide quality, integrity and traceability of the entire supply chain process. The proposed framework is based on the Hyperledger Fabric technology, which is a permissioned blockchain system: a prototype has been developed and, by using some use cases, we show the effectiveness of the approach.

Microservice architecture is increasingly favored for building large-scale applications designed for deployment in distributed and resource-constrained cloud-to-edge computing environments. As a cloud-native approach, microservices are particularly powerful due to their loosely coupled, independently deployable, and scalable characteristics. These features enable distributed deployment and flexible integration across robust cloud data centers and heterogeneous, often resource-limited, edge nodes. To fully leverage these advantages, there is a need for advanced placement algorithms that can optimize application performance by utilizing the strengths of microservices. In response to these challenges, we propose to extend Kubernetes with a load-aware orchestration strategy, which enhances its capability to deploy microservice applications within shared clusters characterized by dynamic resource usage patterns. Our approach orchestrates applications dynamically, based on real-time resource usage, allowing for continuous adjustment of their placement to match evolving conditions. Evaluation of a prototype system in a testbed environment demonstrates that this approach offers substantial benefits compared to the standard Kubernetes scheduler.

The orchestration of serverless applications presents different challenges due to the increasing request load they need to manage and the time-sensitive requirements. The combination of Cloud and Edge computing paradigms attempts to avoid their pitfalls while taking the best of both worlds: Cloud scalability and computing closer to the Edge where data is typically generated. However, placing microservices in such heterogeneous environments while meeting QoS constraints is a challenging task due to the geo-distribution of nodes and varying computational resources. In this paper we propose to extend Knative, an example of a serverless computing framework based on the Kubernetes platform, to enable dynamic serverless application orchestration, taking into account both infrastructure and application states. Our approach aims to reduce QoS violations and improve application response time in Cloud-to-Edge continuum scenarios.