Microservices-based IoT Applications Scheduling in Edge and Fog Computing: A Taxonomy and Future Directions

Edge and Fog computing paradigms utilise distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of the fast-evolving IoT applications. Due to the fine-grained modularity of the microservices along with their independently deployable and scalable nature, MSA exhibits great potential in harnessing both Fog and Cloud resources to meet diverse QoS requirements of the IoT application services, thus giving rise to novel paradigms like Osmotic computing. However, efficient and scalable scheduling algorithms are required to utilise the said characteristics of the MSA while overcoming novel challenges introduced by the architecture. To this end, we present a comprehensive taxonomy of recent literature on microservices-based IoT applications scheduling in Edge and Fog computing environments. Furthermore, we organise multiple taxonomies to capture the main aspects of the scheduling problem, analyse and classify related works, identify research gaps within each category, and discuss future research directions.Comment: 35 pages, 10 figures, submitted to ACM Computing Survey

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

CoScal: Multi-faceted Scaling of Microservices with Reinforcement Learning

The emerging trend towards moving from monolithic applications to microservices has raised new performance challenges in cloud computing environments. Compared with traditional monolithic applications, the microservices are lightweight, fine-grained, and must be executed in a shorter time. Efficient scaling approaches are required to ensure microservices’ system performance under diverse workloads with strict Quality of Service (QoS) requirements and optimize resource provisioning. To solve this problem, we investigate the trade-offs between the dominant scaling techniques, including horizontal scaling, vertical scaling, and brownout in terms of execution cost and response time. We first present a prediction algorithm based on gradient recurrent units to accurately predict workloads assisting in scaling to achieve efficient scaling. Further, we propose a multi-faceted scaling approach using reinforcement learning called CoScal to learn the scaling techniques efficiently. The proposed CoScal approach takes full advantage of data-driven decisions and improves the system performance in terms of high communication cost and delay. We validate our proposed solution by implementing a containerized microservice prototype system and evaluated with two microservice applications. The extensive experiments demonstrate that CoScal reduces response time by 19%-29% and decreases the connection time of services by 16% when compared with the state-of-the-art scaling techniques for Sock Shop application. CoScal can also improve the number of successful transactions with 6%-10% for Stan’s Robot Shop application

Edge computing platforms for Internet of Things

Internet of Things (IoT) has the potential to transform many domains of human activity, enabled by the collection of data from the physical world at a massive scale. As the projected growth of IoT data exceeds that of available network capacity, transferring it to centralized cloud data centers is infeasible. Edge computing aims to solve this problem by processing data at the edge of the network, enabling applications with specialized requirements that cloud computing cannot meet. The current market of platforms that support building IoT applications is very fragmented, with offerings available from hundreds of companies with no common architecture. This threatens the realization of IoT's potential: with more interoperability, a new class of applications that combine the collected data and use it in new ways could emerge. In this thesis, promising IoT platforms for edge computing are surveyed. First, an understanding of current challenges in the field is gained through studying the available literature on the topic. Second, IoT edge platforms having the most potential to meet these challenges are chosen and reviewed for their capabilities. Finally, the platforms are compared against each other, with a focus on their potential to meet the challenges learned in the first part. The work shows that AWS IoT for the edge and Microsoft Azure IoT Edge have mature feature sets. However, these platforms are tied to their respective cloud platforms, limiting interoperability and the possibility of switching providers. On the other hand, open source EdgeX Foundry and KubeEdge have the potential for more standardization and interoperability in IoT but are limited in functionality for building practical IoT applications

Serverless computing

Serverless computing has emerged as a new mindset when it comes to cloud computing, promising efficient resource utilization, automatic scaling, and cost optimization for a wide range of applications. This thesis explores the adoption, performance, and cost considera tions of deploying applications that use intend to use serverless functions, one of the leading Serverless types. This thesis starts by providing an overview of Serverless computing, including its key advan tages and disadvantages and the rising adoption it has gained throughout the recent years. It presents a comprehensive comparison of various Serverless platforms and discusses the unique features offered by each. After this context phase, this thesis presents a design section composed by a migration guide that allows developers to transition from a traditional application to one that takes advan tage of serverless benefits. The guide outlines best practices and step-by-step instructions, facilitating the adoption of Serverless computing in real-world scenarios. Using the previously created guide, the next section carries out a practical use case: the mi gration of complex computational logic from a traditional Java application to AWS Lambda functions. Performance evaluations are conducted, considering metrics such as the execution duration and the amount of concurrent executions. These findings are then evaluated next to the costs associated with deploying and running Java applications in a virtual machine or with a Serverless architecture. While Serverless computing is quite promising, networking issues often arise in practice, affecting the overall efficiency of Serverless applications. This thesis addresses these chal lenges, identifying the installation and migration difficulties, how to overcome them, and what are the expected limitations, while proposing potential solutions. In summary, this thesis offers valuable insights into the adoption, performance, and cost opti mization of Serverless computing for Java applications. It provides a roadmap for developers looking to take advantage of the benefits of Serverless computing in their projects

The impact of microservices: an empirical analysis of the emerging software architecture

Dissertação de mestrado em Informatics EngineeringThe applications’ development paradigm has faced changes in recent years, with modern development being characterized by the need to continuously deliver new software iterations. With great affinity with those principles, microservices is a software architecture which features characteristics that potentially promote multiple quality attributes often required by modern, large-scale applications. Its recent growth in popularity and acceptance in the industry made this architectural style often described as a form of modernizing applications that allegedly solves all the traditional monolithic applications’ inconveniences. However, there are multiple worth mentioning costs associated with its adoption, which seem to be very vaguely described in existing empirical research, being often summarized as "the complexity of a distributed system". The adoption of microservices provides the agility to achieve its promised benefits, but to actually reach them, several key implementation principles have to be honored. Given that it is still a fairly recent approach to developing applications, the lack of established principles and knowledge from development teams results in the misjudgment of both costs and values of this architectural style. The outcome is often implementations that conflict with its promised benefits. In order to implement a microservices-based architecture that achieves its alleged benefits, there are multiple patterns and methodologies involved that add a considerable amount of complexity. To evaluate its impact in a concrete and empirical way, one same e-commerce platform was developed from scratch following a monolithic architectural style and two architectural patterns based on microservices, featuring distinct inter-service communication and data management mechanisms. The effort involved in dealing with eventual consistency, maintaining a communication infrastructure, and managing data in a distributed way portrayed significant overheads not existent in the development of traditional applications. Nonetheless, migrating from a monolithic architecture to a microservicesbased is currently accepted as the modern way of developing software and this ideology is not often contested, nor the involved technical challenges are appropriately emphasized. Sometimes considered over-engineering, other times necessary, this dissertation contributes with empirical data from insights that showcase the impact of the migration to microservices in several topics. From the trade-offs associated with the use of specific patterns, the development of the functionalities in a distributed way, and the processes to assure a variety of quality attributes, to performance benchmarks experiments and the use of observability techniques, the entire development process is described and constitutes the object of study of this dissertation.O paradigma de desenvolvimento de aplicações tem visto alterações nos últimos anos, sendo o desenvolvimento moderno caracterizado pela necessidade de entrega contínua de novas iterações de software. Com grande afinidade com esses princípios, microsserviços são uma arquitetura de software que conta com características que potencialmente promovem múltiplos atributos de qualidade frequentemente requisitados por aplicações modernas de grandes dimensões. O seu recente crescimento em popularidade e aceitação na industria fez com que este estilo arquitetural se comumente descrito como uma forma de modernizar aplicações que alegadamente resolve todos os inconvenientes apresentados por aplicações monolíticas tradicionais. Contudo, existem vários custos associados à sua adoção, aparentemente descritos de forma muito vaga, frequentemente sumarizados como a "complexidade de um sistema distribuído". A adoção de microsserviços fornece a agilidade para atingir os seus benefícios prometidos, mas para os alcançar, vários princípios de implementação devem ser honrados. Dado que ainda se trata de uma forma recente de desenvolver aplicações, a falta de princípios estabelecidos e conhecimento por parte das equipas de desenvolvimento resulta em julgamentos errados dos custos e valores deste estilo arquitetural. O resultado geralmente são implementações que entram em conflito com os seus benefícios prometidos. De modo a implementar uma arquitetura baseada em microsserviços com os benefícios prometidos existem múltiplos padrões que adicionam considerável complexidade. De modo a avaliar o impacto dos microsserviços de forma concreta e empírica, foi desenvolvida uma mesma plataforma e-commerce de raiz segundo uma arquitetura monolítica e duas arquitetura baseadas em microsserviços, contando com diferentes mecanismos de comunicação entre os serviços. O esforço envolvido em lidar com consistência eventual, manter a infraestrutura de comunicação e gerir os dados de uma forma distribuída representaram desafios não existentes no desenvolvimento de aplicações tradicionais. Apesar disso, a ideologia de migração de uma arquitetura monolítica para uma baseada em microsserviços é atualmente aceite como a forma moderna de desenvolver aplicações, não sendo frequentemente contestada nem os seus desafios técnicos são apropriadamente enfatizados. Por vezes considerado overengineering, outras vezes necessário, a presente dissertação visa contribuir com dados práticos relativamente ao impacto da migração para arquiteturas baseadas em microsserviços em diversos tópicos. Desde os trade-offs envolvidos no uso de padrões específicos, o desenvolvimento das funcionalidades de uma forma distribuída e nos processos para assegurar uma variedade de atributos de qualidade, até análise de benchmarks de performance e uso de técnicas de observabilidade, todo o desenvolvimento é descrito e constitui o objeto de estudo da dissertação

Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Cloud Cost Optimization: A Comprehensive Review of Strategies and Case Studies

Cloud computing has revolutionized the way organizations manage their IT infrastructure, but it has also introduced new challenges, such as managing cloud costs. This paper explores various techniques for cloud cost optimization, including cloud pricing, analysis, and strategies for resource allocation. Real-world case studies of these techniques are presented, along with a discussion of their effectiveness and key takeaways. The analysis conducted in this paper reveals that organizations can achieve significant cost savings by adopting cloud cost optimization techniques. Additionally, future research directions are proposed to advance the state of the art in this important field