(e.g., early-warning systems) to the users, hence, the storage and processing of data must be performed in close proximity to the sources of the information [4]. Fog storage can be considered as an ability to develop, deploy and orchestrate various database management services, such as databases and file systems closer to the edge of the network with sufficiently high performance towards the end users (e.g., low network latency and high bandwidth). Due to the better performance and limited storage capacities, Fog storage can be also used as a temporary storage until smart applications' data are analysed and processed, whilst data centres in the Cloud may still take the role of dependable long-term data storage. Different smart application designs can significantly affect various Quality of Service (QoS) database-service-related metrics. In order to address these types of problems, currently various DevOps approaches aim at achieving operationally high QoS by introducing specific orchestration and application control technologies, for example, deployment decision-making algorithms, monitoring tools and similar. With regard to database-service operations, previous studies have investigated a variety of non-functional requirements (NFRs) and their trade-offs [5]. The present study focuses on three NFR attributes, namely, data storage availability, throughput and costs. However, the presented approach is flexible and can be extended towards consideration of multiple NFRs that are related to database-service operations. For any smart application to reach its business objectives, it is necessary to provide assurances that the application will satisfy the necessary QoS. Providing QoS is an essential task because the database-services potentially have to be deployed across different providers, closer to the IoT devices, that is, at the Edge of the network. Hence, stipulating Service Level Agreements (SLAs) between the software engineers and the infrastructure providers is a requirement that should be addressed in the process of providing guarantees that the required QoS will be maintained above the requested thresholds at all times. At this time, to the best of our knowledge, there is no SLA design for database-services that operates under greatly varying conditions between the Things and the Cloud. The present work focuses on the SLA specifications that are necessary to facilitate optimal QoS negotiated between Fog storage providers and software engineers as storage customers. This work is set in the context of the European Union-Republic of Korea DECENTER project ([[https://www.decenter-project.eu/](https://www.decenter-project.eu/)]([https://www.decenter-project.eu/](https://www.decenter-project.eu/)), accessed on 5 January 2022), which investigates a variety of IoT-based smart applications. The project's use cases in areas, such as smart city crossing safety, robotic logistics, smart and safe construction site, and ambient intelligence operate under different conditions; thus, they have different requirements for availability, throughput and costs. The project delivered a Fog Computing platform, where an important feature is the need to provide QoS assurances for databases-service operations. The Kubernetes-based [6] orchestration mechanisms allow to dynamically integrate and orchestrate containers across the Things-to-Cloud computing continuum. In the domain of Fog computing, costumers do not deal with physical resources. Instead, underlying physical resources enable the existence of virtual resources in a form of virtual machines or containers, which can be developed, set up for execution, started, stopped or even rented by customers, each targeting their specific purpose. Virtual resources usually share a common physical infrastructure, in addition to some overhead introduced by the virtualisation, these virtual resources compete for physical resources. This usually leads to reduced performance compared to the model of having one physical instance for each service.