Related papers: Self-Adaptive Microservice-based Systems -- Landsc…
Modern software systems often have to cope with uncertain operation conditions, such as changing workloads or fluctuating interference in a wireless network. To ensure that these systems meet their goals these uncertainties have to be…
Self-adaptation can be realized in various ways. Rule-based approaches prescribe the adaptation to be executed if the system or environment satisfy certain conditions and result in scalable solutions, however, with often only satisfying…
Context. Service-oriented architecture and its microservice-based approach increase an attack surface of applications. Exposed microservices become a pivot point for advanced persistent threats and completely change the threat landscape.…
Self-adaptivity allows software systems to autonomously adjust their behavior during run-time to reduce the cost complexities caused by manual maintenance. In this paper, an approach for building an external adaptation engine for…
Microservice architectures form the backbone of modern software systems for their scalability, resilience, and maintainability, but their rise in cloud-native environments raises energy efficiency concerns. While prior research addresses…
Self-adaptation can be realized in various ways. Rule-based approaches prescribe the adaptation to be executed if the system or environment satisfies certain conditions. They result in scalable solutions but often with merely satisfying…
Nowadays, many companies design and develop their software systems as a set of loosely coupled microservices that communicate via their Application Programming Interfaces (APIs). While the loose coupling improves maintainability,…
The cloud is a new paradigm that is paving the way for new approaches and standards. The architectural styles are evolving in response to the cloud's requirements. In recent years, microservices have emerged as the preferred architectural…
Migration to the cloud has been a popular topic in industry and academia in recent years. Despite many benefits that the cloud presents, such as high availability and scalability, most of the on-premise application architectures are not…
In the past years, machine learning (ML) has become a popular approach to support self-adaptation. While ML techniques enable dealing with several problems in self-adaptation, such as scalable decision-making, they are also subject to…
Cloud applications are more and more microservice-oriented, but a concrete charting of the microservices architecture landscape -- namely, the space of technical options available for microservice software architects in their…
The Adaptable TeaStore specification provides a microservice-based case study for implementing self-adaptation through a control loop. We argue that implementations of this specification should be informed by key properties of…
The challenging deployment of compute-intensive applications from domains such as Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computing systems to explore new design approaches. Approximate…
Following previous work on the automated deployment orchestration of component based applications, where orchestrations are expressed in terms of behaviours satisfying component interface functional dependences, we develop a formal model…
Cloud-native systems are the mainstream for enterprise solutions, given their scalability, resilience, and other benefits. While the benefits of cloud-native systems fueled by microservices are known, less guidance exists on their…
The promise of increased agility, autonomy, scalability, and reusability has made the microservices architecture a \textit{de facto} standard for the development of large-scale and cloud-native commercial applications. Software patterns are…
Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system's run-time behavior. On the one hand, control systems consider properties that concern static aspects…
The advent of edge devices dedicated to machine learning tasks enabled the execution of AI-based applications that efficiently process and classify the data acquired by the resource-constrained devices populating the Internet of Things. The…
Data analytics and data science play a significant role in nowadays society. In the context of Smart Grids (SG), the collection of vast amounts of data has seen the emergence of a plethora of data analysis approaches. In this paper, we…
Modern distributed applications are moving toward a microservice architecture, in which each service is developed and managed independently, and new features and updates are delivered continuously. A guiding principle of microservice…