Cloud-Native Application Development: Tools, Techniques, And Case Studies

Building, delivering, and managing existing applications in cloud processing environments is known as the "cloud native" product approach. In order to meet customer demands, modern enterprises must create incredibly flexible, versatile, and adaptive systems that they can update quickly. In order to achieve this, they employ modern tools and processes that inherently facilitate the development of applications on cloud infrastructure. These cloud-native innovations give adopters a creative advantage by enabling rapid and continuous adjustments to applications without compromising service delivery. Organisations that adopt the cloud-native methodology might avoid investing in the acquisition and maintenance of costly physical infrastructure. Long-term reserve money is subsequently put to good use. The cost of money for developing cloud-native systems may also benefit the customers

Introducing a Research Program for Quantum Humanities: Theoretical Implications

Quantum computing is a new form of computing that is based on the principles of quantum mechanics. It has the potential to revolutionize many fields, including the humanities and social sciences. The idea behind quantum humanities is to explore the potential of quantum computing to answer new questions in these fields, as well as to consider the potential societal impacts of this technology. This paper proposes a research program for quantum humanities, which includes the application of quantum algorithms to humanities and social science research, the reflection on the methods and techniques of quantum computing, and the evaluation of its potential societal implications. This research program aims to define the field of quantum humanities and to establish it as a meaningful part of the humanities and social sciences.Comment: 21 pages, 2 figure

Creating a sustainable digital infrastructure: The role of service-oriented architecture

The United Nations’ goal of generating sustainable industry, innovation, and infrastructure is the point of departure for our reflective paper. The paper elaborates on the concepts of digital infrastructure, service-oriented architecture, and microservices. It emphasizes the benefits and challenges of creating a sustainable infrastructure based on a service-oriented environment, in which cloud services constitute an important part. We outline the prerequisites for obtaining a sustainable digital infrastructure based on services. Service-oriented architecture (SOA) and recently, microservice architecture, and cloud services, can provide organizations with the improved agility and flexibility essential for generating sustainability in a market focusing on digitalization. The reuse capability of SOA provides a common pool of information technology (IT) resources and qualifies as a green IT approach that impacts environmental protection. Previous research has identified IT and business alignment together with SOA governance as the most critical criteria when implementing SOA. This paper discusses these issues in-depth to explain sustainability.publishedVersio

Pattern Views: Concept and Tooling for Interconnected Pattern Languages

Patterns describe proven solutions for recurring problems. Typically, patterns in a particular domain are interrelated and organized in pattern languages. As real-world problems often require patterns of multiple domains, different pattern languages have to be considered to address these problems. However, cross-domain knowledge about how patterns of different languages relate to each other is either hidden in individual pattern descriptions or not documented at all. This makes it difficult to identify relevant patterns across pattern languages. Therefore, we introduce a concept and tooling that enables to capture patterns and their relations across pattern languages for a particular problem context

Toward a technical debt conceptualization for serverless computing

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Serverless computing aims at reducing processing and operational units to single event-driven functions for service orchestration and choreography. With its micro-granular architectural characteristics, serverless computing is bound to face considerable architectural issues and challenges in the medium- and long-term; are these bound to become Technical Debt? As known to many, technical debt is a metaphor that reflects the additional long-run project costs connected to immediately-expedient but unsavvy technical decisions. However, what does technical debt mean and how is it expressed in serverless computing and other hybrid compute models? This article represents the first attempt to conceptualize Technical Debt in such a context; we base our arguments over a technical overview of serverless computing concepts and practices and elaborate on them via empirical inquiry. Our results suggest that higher serviceability of serverless technologies is also characterized by the absence of mechanisms to support an adequate maintainability, testability, and monitoring of serverless systems. Indeed, in case of unexpected behaviours, testing and maintenance activities are more complex and more expensive, as mainly based on non-automated, manual tasks

Jolie and LEMMA: Model-Driven Engineering and Programming Languages Meet on Microservices

Part 3: Large-Scale Decentalised SystemsInternational audienceIn microservices, Model-Driven Engineering (MDE) has emerged as a powerful methodology for architectural design. Independently, the community of programming languages has investigated new linguistic abstractions for effective microservice development. Here, we present the first preliminary study of how the two approaches can crosspollinate, taking the LEMMA framework and the Jolie programming language as respective representatives. We establish a common ground for comparing the two technologies in terms of metamodels, discuss practical enhancements that can be derived from the comparison, and present some directions for future work that arise from our new viewpoint

MetaNet: automated dynamic selection of scheduling policies in cloud environments

Task scheduling is a well-studied problem in the context of optimizing the Quality of Service (QoS) of cloud computing environments. In order to sustain the rapid growth of computational demands, one of the most important QoS metrics for cloud schedulers is the execution cost. In this regard, several data-driven deep neural networks (DNNs) based schedulers have been proposed in recent years to allow scalable and efficient resource management in dynamic workload settings. However, optimal scheduling frequently relies on sophisticated DNNs with high computational needs implying higher execution costs. Further, even in non-stationary environments, sophisticated schedulers might not always be required and we could briefly rely on low-cost schedulers in the interest of cost-efficiency. Therefore, this work aims to solve the non-trivial meta problem of online dynamic selection of a scheduling policy using a surrogate model called MetaNet. Unlike traditional solutions with a fixed scheduling policy, MetaNet on-the-fly chooses a scheduler from a large set of DNN based methods to optimize task scheduling and execution costs in tandem. Compared to state-of-the-art DNN schedulers, this allows for improvement in execution costs, energy consumption, response time and service level agreement violations by up to 11, 43, 8 and 13 percent, respectively