Automated Software Configuration for Cloud Deployment

Nowadays the Internet is being used as a platform for providing a wide variety of different services. That has created challenges related to scaling IT infrastructure management. Cloud computing is a popular solution for scaling infrastructure, either by building a self-hosted cloud or by using cloud platform provided by external organizations. This way some the challenges related to large scale can be transferred to the cloud administrators. OpenStack is a group of open-source software projects for running cloud platforms. It is currently the most commonly used software for building private clouds. Since initially published by NASA and Rackspace, it has been used by various organizations such as Walmart, China Mobile and Cern nuclear research institute. The largest production deployments of OpenStack clouds consist of thousands of physical server computers located in multiple datacenters. The OpenStack community has created many deployment methods that take advantage of automated software configuration management. The deployment methods are built with state of the art software for automating different administrative tasks. They take different approaches to automating infrastructure management for OpenStack. This thesis compares some of the automated deployment methods for OpenStack and examines the benefits of using automation for configuration management. We present comparisons based on technical documentations as well as reference literature. Additionally, we conducted a questionnaire for OpenStack administrators about the use of automation. Lastly, we tested one of the deployment methods in a virtualized environment

Container-based IoT Sensor Node on Raspberry Pi and the Kubernetes Cluster Framework

In recent years, Internet of Things is envisioned to become a promising paradigm in the future Internet. It allows physical objects or things to interact with each other and with users, thus providing machine-to-machine communication that is long been promised. As this paradigm continues to grow, it is changing the nature of the devices that are being attached. This opens a path of embedded systems to be the natural means of communication, control, and development. The ability of these systems to connect and share useful information via Internet is becoming ubiquitous. In many cases, enormous amount of data is generated from embedded devices that need to be processed in an efficient way along with the required computation power. Container-based virtualization has come into existence to accomplish those needs in order to produce an improved system, which has the capability to adapt operational features in terms of security, availability, and isolation. This thesis project is aimed to design and develop a Kubernetes managed container-based embedded IoT sensor node through the use of a cluster. In this project, the cluster was formed by connecting five Raspberry Pi boards to a network switch. This sensor node operates by collecting data from camera and temperature sensors, processing it in a containerized environment, and then sending it to the cloud platform using the Apache Kafka framework. The main motivation of adopting state-of-the-art technologies is to achieve fault-tolerant behavior and processing location flexibility using edge computing. In the end, the overall cluster is evaluated on the basis of architecture, performance, fault-tolerance, and high availability that depicts the feasibility, scalability, and robustness of this sensor node. The experimental results also conclude that the cluster is fault tolerant and has a flexibility over data processing in terms of cloud and edge computing

Continuous integration and application deployment with the Kubernetes technology

Poslední dobou by téměř každý chtěl své aplikace nasadit do Kubernetes. Jenže pro plné využití Kubernetes je třeba přijmout s otevřenou náručí postupy průběžné integrace (CI) a nasazení (CD). Je třeba CI/CD pipeline. Ale k dispozici je až zdrcující množství open-source nástrojů, kde každý pokrývá různé části celého procesu. Následující text vysvětlí základy technologií, kterých bude pro pipeline třeba. A následně shrne některé z populárních open-source nástrojů využívaných pro CI/CD. Z open-source nástrojů navrhneme pipeline. Závěrečné porovnání možných řešení (včetně proprietárních) poskytne čtenáři konkrétní tipy a rady ohledně vytváření vlastní pipeline.It seems nearly everyone would like to deploy to Kubernetes nowadays. To efficiently leverage the power of Kubernetes one must first fully embrace continuous integration (CI) and deployment (CD) practices. A CI/CD pipeline is needed. But there is an overwhelming amount of open-source tools that cover various parts of the whole process.The following text explains the basics of the underlying technologies needed for a pipeline deploying to Kubernetes. And subsequently summarizes some of the popular open-source tools used for CI/CD. Then it designs a working pipeline from the researched tools. Finally, it summarizes some of the possible pipelines (including proprietary) and provides the reader with specific bits of advice on how to implement a pipeline

Infrastructure management in multicloud environments

With the increasing number of cloud service providers and data centres around the world, cloud services users are becoming increasingly concerned about where their data is stored and who has access to the data. The legal reach of customers’ countries does not expand over the country’s borders without special agreements that can take a long while to get. Because it is safer for a cloud service customer to use a cloud service provider that is domestically legally accounta-ble, customers are moving to using these cloud service providers. For the case company this causes both a technical problem and a managerial problem. The technical problem is how to manage cloud environments when the business expands to multiple countries, with said countries customers requiring that the data is stored within their country. Different cloud service providers can also be heterogeneous in their features to manage infrastructure, which makes managing and developing the infrastructure even more difficult. For example, application programming interfaces (API) that makes automation easier can vary between providers. From a management point of view, different time zones also make it harder to quickly respond to any issues in the IT infrastruc-ture when the case company employees are working in the same time zone. The objective of this thesis is to address the issue by investigating which tools and functionali-ties are commonly utilized for automating IT infrastructure and are additionally supported by cloud service providers while being compatible with the specific requirements of the organization in question. The research will help the case organization replace and add new tools to help maintain the IT infrastructure. This thesis will not investigate the managerial problem of case company em-ployees working in the same time zone. The thesis will also not research security, version control, desktop and laptop management or log collection tools or produce a code-based solution to set-ting up an IT environment since further research needs to be done after the tools presented in this thesis have been decided upon. The research does also not investigate every cloud service pro-vider in every country as case company business strategies can change and the size of the thesis would grow too much. Qualitative research method is used for this thesis and the data gathered comes from literature and articles from various source. Both literature and article review provided the theoretical aspects of this research. Data was also gathered by looking at a few countries that have companies whose business is cloud service providing and comparing the findings regarding infrastructure management and automatization. The research is divided into five parts. The first part tries to introduce the background, re-search objective and structure of the research., while the second part tries to explain the theoreti-cal background. In the third part of the research methodology is explained as what material was used and how it was gathered and descriptions of the results, fourth part analyses the results, while the fifth and final part concludes the research

IoT@run-time: a model-based approach to support deployment and self-adaptations in IoT systems

Today, most Internet of Things (IoT) systems leverage edge and fog computing to meet increasingly restrictive requirements and improve quality of service (QoS). Although these multi-layer architectures can improve system performance, their design is challenging because the dynamic and changing IoT environment can impact the QoS and system operation. In this thesis, we propose a modeling-based approach that addresses the limitations of existing studies to support the design, deployment, and management of self-adaptive IoT systems. We have designed a domain specific language (DSL) to specify the self-adaptive IoT system, a code generator that generates YAML manifests for the deployment of the IoT system, and a framework based on the MAPE-K loop to monitor and adapt the IoT system at runtime. Finally, we have conducted several experimental studies to validate the expressiveness and usability of the DSL and to evaluate the ability and performance of our framework to address the growth of concurrent adaptations on an IoT system.Hoy en día, la mayoría de los sistemas de internet de las cosas (IoT, por su sigla en inglés) aprovechan la computación en el borde (edge computing) y la computación en la niebla (fog computing) para cumplir requisitos cada vez más restrictivos y mejorar la calidad del servicio. Aunque estas arquitecturas multicapa pueden mejorar el rendimiento del sistema, diseñarlas supone un reto debido a que el entorno de IoT dinámico y cambiante puede afectar a la calidad del servicio y al funcionamiento del sistema. En esta tesis proponemos un enfoque basado en el modelado que aborda las limitaciones de los estudios existentes para dar soporte en el diseño, el despliegue y la gestión de sistemas de IoT autoadaptables. Hemos diseñado un lenguaje de dominio específico (DSL) para modelar el sistema de IoT autoadaptable, un generador de código que produce manifiestos YAML para el despliegue del sistema de IoT y un marco basado en el bucle MAPE-K para monitorizar y adaptar el sistema de IoT en tiempo de ejecución. Por último, hemos llevado a cabo varios estudios experimentales para validar la expresividad y usabilidad del DSL y evaluar la capacidad y el rendimiento de nuestro marco para abordar el crecimiento de las adaptaciones concurrentes en un sistema de IoT.Avui dia, la majoria dels sistemes d'internet de les coses (IoT, per la sigla en anglès) aprofiten la informàtica a la perifèria (edge computing) i la informàtica a la boira (fog computing) per complir requisits cada cop més restrictius i millorar la qualitat del servei. Tot i que aquestes arquitectures multicapa poden millorar el rendiment del sistema, dissenyar-les suposa un repte perquè l'entorn d'IoT dinàmic i canviant pot afectar la qualitat del servei i el funcionament del sistema. En aquesta tesi proposem un enfocament basat en el modelatge que aborda les limitacions dels estudis existents per donar suport al disseny, el desplegament i la gestió de sistemes d'IoT autoadaptatius. Hem dissenyat un llenguatge de domini específic (DSL) per modelar el sistema d'IoT autoadaptatiu, un generador de codi que produeix manifestos YAML per al desplegament del sistema d'IoT i un marc basat en el bucle MAPE-K per monitorar i adaptar el sistema d'IoT en temps d'execució. Finalment, hem dut a terme diversos estudis experimentals per validar l'expressivitat i la usabilitat del DSL i avaluar la capacitat i el rendiment del nostre marc per abordar el creixement de les adaptacions concurrents en un sistema d'IoT.Tecnologies de la informació i de xarxe