ClouNS - A Cloud-native Application Reference Model for Enterprise Architects

The capability to operate cloud-native applications can generate enormous business growth and value. But enterprise architects should be aware that cloud-native applications are vulnerable to vendor lock-in. We investigated cloud-native application design principles, public cloud service providers, and industrial cloud standards. All results indicate that most cloud service categories seem to foster vendor lock-in situations which might be especially problematic for enterprise architectures. This might sound disillusioning at first. However, we present a reference model for cloud-native applications that relies only on a small subset of well standardized IaaS services. The reference model can be used for codifying cloud technologies. It can guide technology identification, classification, adoption, research and development processes for cloud-native application and for vendor lock-in aware enterprise architecture engineering methodologies

Ohjelmistokonttien hyödyntäminen pilvipohjaisen mobiiliverkon sovelluksissa

Mobile service providers and manufacturers have moved towards virtualized network functions, because the amount of mobile data traffic has increased a lot during the past few years. Virtual machines offer high flexibility and easier management. They also enable flexible scaling, which makes it easier to respond to the varying traffic patterns during the day. However, the traditional virtual machines contain overhead and have reduced performance in most of the operations. One high performing alternative to a virtual machine is a Linux container. Linux containers do not contain additional operating system or any unnecessary services. Containers are isolated user spaces which share host computer's kernel. This makes processes inside them perform almost as well as if they would be running directly on host. Also, the startup time of containers is extremely fast compared to virtual machines. This thesis studies, if Linux containers are suitable for telco applications. The research is conducted via proof-of-concept where parts of an existing telco application are moved to containers. First, the container technology and related tools are discussed. Benefits and requirements of the Linux containers are then studied based on the proof-of-concept. In this thesis, it was found out that containers are suitable for running small parts of the application. For example, the software update and scaling are a much more efficient processes with containers than with virtual machines. However, the isolation is weaker in containers than in virtual machines, and at the moment they are not suitable for applications or environments where strict isolation is a necessity.Mobiilidatan määrä on kasvanut voimakkaasti muutaman viime vuoden aikana. Tämän johdosta mobiiliverkon palveluntarjoajat ja laitevalmistajat ovat alkaneet virtualisoimaan mobiiliverkon laitteita. Virtualisointi tarjoaa joustavuutta ja helpottaa laitteiden hallintaa. Virtualisoinnin avulla mobiiliverkon laitteita voidaan skaalata verkon liikennemäärien mukaan. Virtuaalikoneet sisältävät ohjelmien suorituksen kannalta epäolennaisia palveluita ja niiden suorituskyky on usein heikompi verrattuna tavallisiin tietokoneisiin. Linux-kontit tarjoavat kevyemmän ja suorituskyvyltään tehokkaamman vaihtoehdon virtuaalikoneille. Ne eivät sisällä ylimääräistä käyttöjärjestelmää tai ylimääräisiä palveluita. Kontit ovat eristettyjä alueita käyttöjärjestelmän sisällä ja ne myös jakavat käyttöjärjestelmän ytimen. Tämän ansiosta prosessien suorituskyky kontin sisällä on lähes identtinen kuin ilman kontteja. Konttien käynnistymisaika on myös huomattavasti lyhyempi kuin virtuaalikoneiden. Tässä diplomityössä tutkitaan, soveltuvatko Linux-kontit mobiiliverkon sovellusten suorittamiseen. Tutkimus suoritetaan käytännön esimerkin avulla, jossa erään mobiiliverkon sovelluksen osia suoritetaan konteissa. Aluksi tutkitaan Linux-kontteja, niiden teknologista taustaa sekä niihin liittyviä työkaluja. Tämän jälkeen konttien hyötyjä ja niiden vaatimuksia tutkitaan edellä mainitun käytännön esimerkin avulla. Tässä työssä saatiin selville, että kontit soveltuvat pienien sovelluksen osien suorittamiseen. Esimerkiksi sovelluksen päivitys ja skaalaus on tehokkaampaa kontteja käytettäessä. Konttien eristys on kuitenkin heikompaa kuin virtuaalikoneiden ja tällä hetkellä ne eivät sovellu sovelluksille tai ympäristöihin, joissa vaaditaan vahvaa eristystä

Distributed Computing Framework Based on Software Containers for Heterogeneous Embedded Devices

The Internet of Things (IoT) is represented by millions of everyday objects enhanced with sensing and actuation capabilities that are connected to the Internet. Traditional approaches for IoT applications involve sending data to cloud servers for processing and storage, and then relaying commands back to devices. However, this approach is no longer feasible due to the rapid growth of IoT in the network: the vast amount of devices causes congestion; latency and security requirements demand that data is processed close to the devices that produce and consume it; and the processing and storage resources of devices remain underutilized. Fog Computing has emerged as a new paradigm where multiple end-devices form a shared pool of resources where distributed applications are deployed, taking advantage of local capabilities. These devices are highly heterogeneous, with varying hardware and software platforms. They are also resource-constrained, with limited availability of processing and storage resources. Realizing the Fog requires a software framework that simplifies the deployment of distributed applications, while at the same time overcoming these constraints. In Cloud-based deployments, software containers provide a lightweight solution to simplify the deployment of distributed applications. However, Cloud hardware is mostly homogeneous and abundant in resources. This work establishes the feasibility of using Docker Swarm -- an existing container-based software framework -- for the deployment of distributed applications on IoT devices. This is realized with the use of custom tools to enable minimal-size applications compatible with heterogeneous devices; automatic configuration and formation of device Fog; remote management and provisioning of devices. The proposed framework has significant advantages over the state of the art, namely, it supports Fog-based distributed applications, it overcomes device heterogeneity and it simplifies device initialization

Container-based microservice architecture for local IoT services

Abstract. Edge services are needed to save networking and computational resources on higher tiers, enable operation during network problems, and to help limiting private data propagation to higher tiers if the function needing it can be handled locally. MEC at access network level provides most of these features but cannot help when access network is down. Local services, in addition, help alleviating the MEC load and limit the data propagation even more, on local level. This thesis focuses on the local IoT service provisioning. Local service provisioning is subject to several requirements, related to resource/energy-efficiency, performance and reliability. This thesis introduces a novel way to design and implement a Docker container-based micro-service system for gadget-free future IoT (Internet of Things) network. It introduces a use case scenario and proposes few possible required micro-services as of solution to the scenario. Some of these services deployed on different virtual platforms along with software components that can process sensor data providing storage capacity to make decisions based on their algorithm and business logic while few other services deployed with gateway components to connect rest of the devices to the system of solution. It also includes a state-of-the-art study for design, implementation, and evaluation as a Proof-of-Concept (PoC) based on container-based microservices with Docker. The used IoT devices are Raspberry Pi embedded computers along with an Ubuntu machine with a rich set of features and interfaces, capable of running virtualized services. This thesis evaluates the solution based on practical implementation. In addition, the thesis also discusses the benefits and drawbacks of the system with respect to the empirical solution. The output of the thesis shows that the virtualized microservices could be efficiently utilized at the local and resource constrained IoT using Dockers. This validates that the approach taken in this thesis is feasible for providing such services and functionalities to the micro and nanoservice architecture. Finally, this thesis proposes numerous improvements for future iterations

Docker container-based big data processing system in multiple clouds for everyone

Big data processing is progressively becoming essential for everyone to extract the meaningful information from their large volume of data irrespective of types of users and their application areas. Big data processing is a broad term and includes several operations such as the storage, cleaning, organization, modelling, analysis and presentation of data at a scale and efficiency. For ordinary users, the significant challenges are the requirement of the powerful data processing system and its provisioning, installation of complex big data analytics and difficulty in their usage. Docker is a container-based virtualization technology and it has recently introduced Docker Swarm for the development of various types of multi-cloud distributed systems, which can be helpful in solving all above problems for ordinary users. However, Docker is predominantly used in the software development industry, and less focus is given to the data processing aspect of this container-based technology. Therefore, this paper proposes the Docker container-based big data processing system in multiple clouds for everyone, which explores another potential dimension of Docker for big data analysis. This Docker container-based system is an inexpensive and user-friendly framework for everyone who has the knowledge of basic IT skills. Additionally, it can be easily developed on a single machine, multiple machines or multiple clouds. This paper demonstrates the architectural design and simulated development of the proposed Docker container-based big data processing system in multiple clouds. Subsequently, it illustrates the automated provisioning of big data clusters using two popular big data analytics, Hadoop and Pachyderm (without Hadoop) including the Web-based GUI interface Hue for easy data processing in Hadoop