Application for managing container-based software development environments

Abstract. Virtualizing the software development process can enhance efficiency through unified, remotely managed environments. Docker containers, a popular technology in software development, are widely used for application testing and deployment. This thesis examines the use of containers as cloud-based development environments. This study explores the history and implementation of container-based virtualization before presenting containers as a novel cloud-based software development environment. Virtual containers, like virtual machines, have been extensively used in software development for code testing but not as development environments. Containers are also prevalent in the final stages of software production, specifically in the distribution and deployment of completed applications. In the practical part of the thesis, an application is implemented to improve the usability of a container-based development environment, addressing challenges in adopting new work environments. The work was conducted for a private company, and multiple experts provided input. The management application enhanced the container-based development environment’s efficiency by improving user rights management, virtual container management, and user interface. Additionally, the new management tools reduced training time for new employees by 50%, facilitating their integration into the organization. Container-based development environments with efficient management tools provide a secure, efficient, and unified platform for large-scale software development. Virtual containers also hold potential for future improvements in energy-saving strategies and organizational work method harmonization and integration.Sovellus konttipohjaisten ohjelmistonkehitysympäristöjen hallintaan. Tiivistelmä. Ohjelmistokehitysprosessin virtualisointi voi parantaa tehokkuutta yhtenäisten, etähallittujen ympäristöjen avulla. Ohjelmistonkehityksessä suosittu ohjelmistonkehitysteknologia, Docker-kontteja käytetään laajalti sovellusten testaamisessa ja käyttöönotossa. Tässä opinnäytetyössä tarkastellaan konttien käyttöä pilvipohjaisina kehitysympäristöinä. Tämä tutkimus tutkii konttipohjaisen virtualisoinnin historiaa ja toteutusta, jonka jälkeen esitellään konttien käyttöä uudenlaisena pilvipohjaisena ohjelmistokehitysympäristönä. Virtuaalisia kontteja, kuten virtuaalikoneita, on käytetty laajasti ohjelmistokehityksessä kooditestauksessa, mutta ei kehitysympäristöinä. Kontit ovat myös yleisiä ohjelmistotuotannon loppuvaiheissa, erityisesti valmiiden sovellusten jakelussa ja käyttöönotossa. Opinnäytetyön käytännön osassa toteutetaan konttipohjaisen kehitysympäristön käytettävyyttä parantava sovellus, joka vastaa uusien työympäristöjen käyttöönoton haasteisiin. Työ suoritettiin yksityiselle yritykselle, ja sen suunnitteluun osallistui useita asiantuntijoita. Hallintasovellus lisäsi konttipohjaisen kehitysympäristön tehokkuutta parantamalla käyttäjäoikeuksien hallintaa, virtuaalisen kontin hallintaa ja käyttöliittymää. Lisäksi uudet hallintatyökalut lyhensivät uusien työntekijöiden koulutusaikaa 50%, mikä helpotti heidän integroitumistaan organisaatioon. Säiliöpohjaiset kehitysympäristöt varustettuina tehokkailla hallintatyökaluilla tarjoavat turvallisen, tehokkaan ja yhtenäisen alustan laajamittaiseen ohjelmistokehitykseen. Virtuaalisissa konteissa on myös potentiaalia tulevaisuuden parannuksiin energiansäästöstrategioissa ja organisaation työmenetelmien harmonisoinnissa ja integroinnissa

Adaptive learning-based resource management strategy in fog-to-cloud

Technology in the twenty-first century is rapidly developing and driving us into a new smart computing world, and emerging lots of new computing architectures. Fog-to-Cloud (F2C) is among one of them, which emerges to ensure the commitment for bringing the higher computing facilities near to the edge of the network and also help the large-scale computing system to be more intelligent. As the F2C is in its infantile state, therefore one of the biggest challenges for this computing paradigm is to efficiently manage the computing resources. Mainly, to address this challenge, in this work, we have given our sole interest for designing the initial architectural framework to build a proper, adaptive and efficient resource management mechanism in F2C. F2C has been proposed as a combined, coordinated and hierarchical computing platform, where a vast number of heterogeneous computing devices are participating. Notably, their versatility creates a massive challenge for effectively handling them. Even following any large-scale smart computing system, it can easily recognize that various kind of services is served for different purposes. Significantly, every service corresponds with the various tasks, which have different resource requirements. So, knowing the characteristics of participating devices and system offered services is giving advantages to build effective and resource management mechanism in F2C-enabled system. Considering these facts, initially, we have given our intense focus for identifying and defining the taxonomic model for all the participating devices and system involved services-tasks. In any F2C-enabled system consists of a large number of small Internet-of-Things (IoTs) and generating a continuous and colossal amount of sensing-data by capturing various environmental events. Notably, this sensing-data is one of the key ingredients for various smart services which have been offered by the F2C-enabled system. Besides that, resource statistical information is also playing a crucial role, for efficiently providing the services among the system consumers. Continuous monitoring of participating devices generates a massive amount of resource statistical information in the F2C-enabled system. Notably, having this information, it becomes much easier to know the device's availability and suitability for executing some tasks to offer some services. Therefore, ensuring better service facilities for any latency-sensitive services, it is essential to securely distribute the sensing-data and resource statistical information over the network. Considering these matters, we also proposed and designed a secure and distributed database framework for effectively and securely distribute the data over the network. To build an advanced and smarter system is necessarily required an effective mechanism for the utilization of system resources. Typically, the utilization and resource handling process mainly depend on the resource selection and allocation mechanism. The prediction of resources (e.g., RAM, CPU, Disk, etc.) usage and performance (i.e., in terms of task execution time) helps the selection and allocation process. Thus, adopting the machine learning (ML) techniques is much more useful for designing an advanced and sophisticated resource allocation mechanism in the F2C-enabled system. Adopting and performing the ML techniques in F2C-enabled system is a challenging task. Especially, the overall diversification and many other issues pose a massive challenge for successfully performing the ML techniques in any F2C-enabled system. Therefore, we have proposed and designed two different possible architectural schemas for performing the ML techniques in the F2C-enabled system to achieve an adaptive, advance and sophisticated resource management mechanism in the F2C-enabled system. Our proposals are the initial footmarks for designing the overall architectural framework for resource management mechanism in F2C-enabled system.La tecnologia del segle XXI avança ràpidament i ens condueix cap a un nou món intel·ligent, creant nous models d'arquitectures informàtiques. Fog-to-Cloud (F2C) és un d’ells, i sorgeix per garantir el compromís d’acostar les instal·lacions informàtiques a prop de la xarxa i també ajudar el sistema informàtic a gran escala a ser més intel·ligent. Com que el F2C es troba en un estat preliminar, un dels majors reptes d’aquest paradigma tecnològic és gestionar eficientment els recursos informàtics. Per fer front a aquest repte, en aquest treball hem centrat el nostre interès en dissenyar un marc arquitectònic per construir un mecanisme de gestió de recursos adequat, adaptatiu i eficient a F2C.F2C ha estat concebut com una plataforma informàtica combinada, coordinada i jeràrquica, on participen un gran nombre de dispositius heterogenis. La seva versatilitat planteja un gran repte per gestionar-los de manera eficaç. Els serveis que s'hi executen consten de diverses tasques, que tenen requisits de recursos diferents. Per tant, conèixer les característiques dels dispositius participants i dels serveis que ofereix el sistema és un requisit per dissenyar mecanismes eficaços i de gestió de recursos en un sistema habilitat per F2C. Tenint en compte aquests fets, inicialment ens hem centrat en identificar i definir el model taxonòmic per a tots els dispositius i sistemes implicats en l'execució de tasques de serveis. Qualsevol sistema habilitat per F2C inclou en un gran nombre de dispositius petits i connectats (conegut com a Internet of Things, o IoT) que generen una quantitat contínua i colossal de dades de detecció capturant diversos events ambientals. Aquestes dades són un dels ingredients clau per a diversos serveis intel·ligents que ofereix F2C. A més, el seguiment continu dels dispositius participants genera igualment una gran quantitat d'informació estadística. En particular, en tenir aquesta informació, es fa molt més fàcil conèixer la disponibilitat i la idoneïtat dels dispositius per executar algunes tasques i oferir alguns serveis. Per tant, per garantir millors serveis sensibles a la latència, és essencial distribuir de manera equilibrada i segura la informació estadística per la xarxa. Tenint en compte aquests assumptes, també hem proposat i dissenyat un entorn de base de dades segura i distribuïda per gestionar de manera eficaç i segura les dades a la xarxa. Per construir un sistema avançat i intel·ligent es necessita un mecanisme eficaç per a la gestió de l'ús dels recursos del sistema. Normalment, el procés d’utilització i manipulació de recursos depèn principalment del mecanisme de selecció i assignació de recursos. La predicció de l’ús i el rendiment de recursos (per exemple, RAM, CPU, disc, etc.) en termes de temps d’execució de tasques ajuda al procés de selecció i assignació. Adoptar les tècniques d’aprenentatge automàtic (conegut com a Machine Learning, o ML) és molt útil per dissenyar un mecanisme d’assignació de recursos avançat i sofisticat en el sistema habilitat per F2C. L’adopció i la realització de tècniques de ML en un sistema F2C és una tasca complexa. Especialment, la diversificació general i molts altres problemes plantegen un gran repte per realitzar amb èxit les tècniques de ML. Per tant, en aquesta recerca hem proposat i dissenyat dos possibles esquemes arquitectònics diferents per realitzar tècniques de ML en el sistema habilitat per F2C per aconseguir un mecanisme de gestió de recursos adaptatiu, avançat i sofisticat en un sistema F2C. Les nostres propostes són els primers passos per dissenyar un marc arquitectònic general per al mecanisme de gestió de recursos en un sistema habilitat per F2C.Postprint (published version

Cyber Security and Critical Infrastructures

This book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles: an editorial explaining current challenges, innovative solutions, real-world experiences including critical infrastructure, 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems, and a review of cloud, edge computing, and fog's security and privacy issues

Relationships Among Dimensions of Information System Success and Benefits of Cloud

Despite the many benefits offered by cloud computing’s design architecture, there are many fundamental performance challenges for IT managers to manage cloud infrastructures to meet business expectations effectively. Grounded in the information systems success model, the purpose of this quantitative correlational study was to evaluate the relationships among the perception of information quality, perception of system quality, perception of service quality, perception of system use, perception of user satisfaction, and net benefits of cloud computing services. The participants (n = 137) were IT cloud services managers in the United States, who completed the DeLone and McLean ISS authors’ validated survey instrument. The multiple regression finding were signification, F(5, 131) = 85.16, p \u3c .001, R2 = 0.76. In the final model, perception of information quality (β = .188, t = 2.844, p \u3c .05), perception of service quality (β = .178, t = 2.102, p \u3c .05), and perception of user satisfaction (β = .379, t = 5.024, p \u3c .001) were statistically significant; perception of system quality and perception of system use were not statistically significant. A recommendation is for IT managers to implement comprehensive customer evaluation of the cloud service(s) to meet customer expectations and afford satisfaction. The implications for positive social change include decision-makers in healthcare, human services, social services, and other critical service organizations better understand the vital predictors of attitude toward system use and user satisfaction of customer-facing cloud-based applications