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Effective devOps with AWS : implement continuous delivery and integration in the AWS environment
This book will help you to understand how the most successful tech start-ups launch and scale their services on AWS, and will teach you how you can do the same. It explains how to treat infrastructure as code, meaning you can bring resources online and offline as easily as you control your software. You will get insight into monitoring and alerting, so you can make sure your users have the best experience when using your service. You will learn how to implement automatic AWS instance provisioning using CloudFormation, deploy your application on a provisioned infrastructure with Ansible, manage infrastructure using Terraform, build and deploy a CI/CD pipeline with automated testing on AWS, understand the container journey for a CI/CD pipeline using AWS ECS and monitor and secure your AWS environment.
Book
Flexible IoT Agriculture Systems for Irrigation Control Based on Software Services
IoT technology applied to agriculture has produced a number of contributions in the recent years. Such solutions are, most of the time, fully tailored to a particular functional target and focus extensively on sensor-hardware development and customization. As a result, software-centered solutions for IoT system development are infrequent. This is not suitable, as the software is the bottleneck in modern computer systems, being the main source of performance loss, errors, and even cyber attacks. This paper takes a software-centric perspective to model and design IoT systems in a flexible manner. We contribute a software framework that supports the design of the IoT systems’ software based on software services in a client–server model with REST interactions; and it is exemplified on the domain of efficient irrigation in agriculture. We decompose the services’ design into the set of constituent functions and operations both at client and server sides. As a result, we provide a simple and novel view on the design of IoT systems in agriculture from a sofware perspective: we contribute simple design structure based on the identification of the front-end software services, their internal software functions and operations, and their interconnections as software services. We have implemented the software framework on an IoT irrigation use case that monitors the conditions of the field and processes the sampled data, detecting alarms when needed. We demonstrate that the temporal overhead of our solution is bounded and suitable for the target domain, reaching a response time of roughly 11 s for bursts of 3000 requests.
Journal Article
A Model of Competition Between Perpetual Software and Software as a Service
Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the perpetual software vendor adopts one of three different strategies: (1) an entry deterrence strategy, (2) a market segmentation strategy, or (3) a sequential dominance strategy. Surprisingly, we find that vendor competition does not always result in higher consumer surplus, and it might lead to a socially inefficient outcome under certain conditions. We further show insights into how the incumbent perpetual software vendor can defend its market position by providing incremental quality improvement through patching and/or by releasing consecutive versions with major quality upgrades. Finally, we extend our model to include the vendor’s quality improvement cost and users’ switching cost. These additional analyses help to identify the effect of different quality and cost factors on the market competitive equilibrium.
Journal Article
Cyber Security in IoT-Based Cloud Computing: A Comprehensive Survey
Cloud computing provides the flexible architecture where data and resources are dispersed at various locations and are accessible from various industrial environments. Cloud computing has changed the using, storing, and sharing of resources such as data, services, and applications for industrial applications. During the last decade, industries have rapidly switched to cloud computing for having more comprehensive access, reduced cost, and increased performance. In addition, significant improvement has been observed in the internet of things (IoT) with the integration of cloud computing. However, this rapid transition into the cloud raised various security issues and concerns. Traditional security solutions are not directly applicable and sometimes ineffective for cloud-based systems. Cloud platforms’ challenges and security concerns have been addressed during the last three years, despite the successive use and proliferation of multifaceted cyber weapons. The rapid evolution of deep learning (DL) in the artificial intelligence (AI) domain has brought many benefits that can be utilized to address industrial security issues in the cloud. The findings of the proposed research include the following: we present a comprehensive survey of enabling cloud-based IoT architecture, services, configurations, and security models; the classification of cloud security concerns in IoT into four major categories (data, network and service, applications, and people-related security issues), which are discussed in detail; we identify and inspect the latest advancements in cloud-based IoT attacks; we identify, discuss, and analyze significant security issues in each category and present the limitations from a general, artificial intelligence and deep learning perspective; we provide the technological challenges identified in the literature and then identify significant research gaps in the IoT-based cloud infrastructure to highlight future research directions to blend cybersecurity in cloud.
Journal Article
Service quality in cloud gaming: instrument development and validation
PurposeThe global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.Design/methodology/approachA three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.FindingsCloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.Practical implicationsPractitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.Originality/valueThis study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.
Journal Article
The Impact of the COVID-19 Pandemic on the Global Web and Video Conferencing SaaS Market
The COVID-19 pandemic related government interventions produced rapid decreases in worldwide economic and social activity, with multifaceted economic and social consequences. In particular, the disruption of key industries and significant lifestyle changes in the aftermath of the pandemic outbreak led to the exponential adoption of web and video conferencing Software as a Service (SaaS) programs and to the solutions-led video conferencing market growth. However, the magnitude and persistence of the COVID-19 pandemic impact on the video conferencing solutions segment remain uninvestigated. Building on previous evidence linking population web-search behavior, private consumption, and retail sales, this study sources and employs Google Trends data as an analytical and forecasting tool for the solutions segment of the videoconferencing market. It implements a univariate forecast evaluation approach that assesses the predictive performance of several statistical and machine-learning models for the relative search volume (RSV) in the two SaaS program leaders, Zoom and Teams. ETS is found to provide the best forecast of consumer GT search interest for both RSV series. A baseline level for the consumer interest over the first pandemic wave is subsequently produced with ETS and further serves to estimate the excess search interest over the February 2020–August 2020 period. Results indicate that the pandemic has created an excess or abnormal consumer interest in the global web and videoconferencing SaaS market that would not have occurred in the absence of the pandemic. Other findings indicate that the impact is persistent as the excess interest stabilized at higher levels than in the pre-pandemic period for both SaaS market leaders, although a higher saturation of the Zoom market is detected.
Journal Article