Comparison of Architectures and Performance of Database Replication Systems

One of the most demanding needs in cloud computing and big data is that of having scalable and highly available databases. One of the ways to attend these needs is to leverage the scalable replication techniques developed in the last decade. These techniques allow increasing both the availability and scalability of databases. Many replication protocols have been proposed during the last decade. The main research challenge was how to scale under the eager replication model, the one that provides consistency across replicas. This thesis provides an in depth study of three eager database replication systems based on relational systems: Middle-R, C-JDBC and MySQL Cluster and three systems based on In-Memory Data Grids: JBoss Data Grid, Oracle Coherence and Terracotta Ehcache. Thesis explore these systems based on their architecture, replication protocols, fault tolerance and various other functionalities. It also provides experimental analysis of these systems using state-of-the art benchmarks: TPC-C and TPC-W (for relational systems) and Yahoo! Cloud Serving Benchmark (In- Memory Data Grids). Thesis also discusses three Graph Databases, Neo4j, Titan and Sparksee based on their architecture and transactional capabilities and highlights the weaker transactional consistencies provided by these systems. It discusses an implementation of snapshot isolation in Neo4j graph database to provide stronger isolation guarantees for transactions.

A Novel Approach to Context-Aware Content-Based Middleware

La computación ubicua está extendiendo su aplicación desde entornos específicos hacia el uso cotidiano; el Internet de las cosas (IoT, en inglés) es el ejemplo más brillante de su aplicación y de la complejidad intrínseca que tiene, en comparación con el clásico desarrollo de aplicaciones. La principal característica que diferencia la computación ubicua de los otros tipos está en como se emplea la información de contexto. Las aplicaciones clásicas no usan en absoluto la información de contexto o usan sólo una pequeña parte de ella, integrándola de una forma ad hoc con una implementación específica para la aplicación. La motivación de este tratamiento particular se tiene que buscar en la dificultad de compartir el contexto con otras aplicaciones. En realidad lo que es información de contexto depende del tipo de aplicación: por poner un ejemplo, para un editor de imágenes, la imagen es la información y sus metadatos, tales como la hora de grabación o los ajustes de la cámara, son el contexto, mientras que para el sistema de ficheros la imagen junto con los ajustes de cámara son la información, y el contexto es representado por los metadatos externos al fichero como la fecha de modificación o la de último acceso. Esto significa que es difícil compartir la información de contexto, y la presencia de un middleware de comunicación que soporte el contexto de forma explícita simplifica el desarrollo de aplicaciones para computación ubicua. Al mismo tiempo el uso del contexto no tiene que ser obligatorio, porque si no se perdería la compatibilidad con las aplicaciones que no lo usan, convirtiendo así dicho middleware en un middleware de contexto. SilboPS, que es nuestra implementación de un sistema publicador/subscriptor basado en contenido e inspirado en SIENA [11, 9], resuelve dicho problema extendiendo el paradigma con dos elementos: el Contexto y la Función de Contexto. El contexto representa la información contextual propiamente dicha del mensaje por enviar o aquella requerida por el subscriptor para recibir notificaciones, mientras la función de contexto se evalúa usando el contexto del publicador y del subscriptor. Esto permite desacoplar la lógica de gestión del contexto de aquella de la función de contexto, incrementando de esta forma la flexibilidad de la comunicación entre varias aplicaciones. De hecho, al utilizar por defecto un contexto vacío, las aplicaciones clásicas y las que manejan el contexto pueden usar el mismo SilboPS, resolviendo de esta forma la incompatibilidad entre las dos categorías. En cualquier caso la posible incompatibilidad semántica sigue existiendo ya que depende de la interpretación que cada aplicación hace de los datos y no puede ser solucionada por una tercera parte agnóstica. El entorno IoT conlleva retos no sólo de contexto, sino también de escalabilidad. La cantidad de sensores, el volumen de datos que producen y la cantidad de aplicaciones que podrían estar interesadas en manipular esos datos está en continuo aumento. Hoy en día la respuesta a esa necesidad es la computación en la nube, pero requiere que las aplicaciones sean no sólo capaces de escalar, sino de hacerlo de forma elástica [22]. Desgraciadamente no hay ninguna primitiva de sistema distribuido de slicing que soporte un particionamiento del estado interno [33] junto con un cambio en caliente, además de que los sistemas cloud actuales como OpenStack u OpenNebula no ofrecen directamente una monitorización elástica. Esto implica que hay un problema bilateral: cómo puede una aplicación escalar de forma elástica y cómo monitorizar esa aplicación para saber cuándo escalarla horizontalmente. E-SilboPS es la versión elástica de SilboPS y se adapta perfectamente como solución para el problema de monitorización, gracias al paradigma publicador/subscriptor basado en contenido y, a diferencia de otras soluciones [5], permite escalar eficientemente, para cumplir con la carga de trabajo sin sobre-provisionar o sub-provisionar recursos. Además está basado en un algoritmo recientemente diseñado que muestra como añadir elasticidad a una aplicación con distintas restricciones sobre el estado: sin estado, estado aislado con coordinación externa y estado compartido con coordinación general. Su evaluación enseña como se pueden conseguir notables speedups, siendo el nivel de red el principal factor limitante: de hecho la eficiencia calculada (ver Figura 5.8) demuestra cómo se comporta cada configuración en comparación con las adyacentes. Esto permite conocer la tendencia actual de todo el sistema, para saber si la siguiente configuración compensará el coste que tiene con la ganancia que lleva en el throughput de notificaciones. Se tiene que prestar especial atención en la evaluación de los despliegues con igual coste, para ver cuál es la mejor solución en relación a una carga de trabajo dada. Como último análisis se ha estimado el overhead introducido por las distintas configuraciones a fin de identificar el principal factor limitante del throughput. Esto ayuda a determinar la parte secuencial y el overhead de base [26] en un despliegue óptimo en comparación con uno subóptimo. Efectivamente, según el tipo de carga de trabajo, la estimación puede ser tan baja como el 10 % para un óptimo local o tan alta como el 60 %: esto ocurre cuando se despliega una configuración sobredimensionada para la carga de trabajo. Esta estimación de la métrica de Karp-Flatt es importante para el sistema de gestión porque le permite conocer en que dirección (ampliar o reducir) es necesario cambiar el despliegue para mejorar sus prestaciones, en lugar que usar simplemente una política de ampliación. ABSTRACT The application of pervasive computing is extending from field-specific to everyday use. The Internet of Things (IoT) is the shiniest example of its application and of its intrinsic complexity compared with classical application development. The main characteristic that differentiates pervasive from other forms of computing lies in the use of contextual information. Some classical applications do not use any contextual information whatsoever. Others, on the other hand, use only part of the contextual information, which is integrated in an ad hoc fashion using an application-specific implementation. This information is handled in a one-off manner because of the difficulty of sharing context across applications. As a matter of fact, the application type determines what the contextual information is. For instance, for an imaging editor, the image is the information and its meta-data, like the time of the shot or camera settings, are the context, whereas, for a file-system application, the image, including its camera settings, is the information and the meta-data external to the file, like the modification date or the last accessed timestamps, constitute the context. This means that contextual information is hard to share. A communication middleware that supports context decidedly eases application development in pervasive computing. However, the use of context should not be mandatory; otherwise, the communication middleware would be reduced to a context middleware and no longer be compatible with non-context-aware applications. SilboPS, our implementation of content-based publish/subscribe inspired by SIENA [11, 9], solves this problem by adding two new elements to the paradigm: the context and the context function. Context represents the actual contextual information specific to the message to be sent or that needs to be notified to the subscriber, whereas the context function is evaluated using the publisher’s context and the subscriber’s context to decide whether the current message and context are useful for the subscriber. In this manner, context logic management is decoupled from context management, increasing the flexibility of communication and usage across different applications. Since the default context is empty, context-aware and classical applications can use the same SilboPS, resolving the syntactic mismatch that there is between the two categories. In any case, the possible semantic mismatch is still present because it depends on how each application interprets the data, and it cannot be resolved by an agnostic third party. The IoT environment introduces not only context but scaling challenges too. The number of sensors, the volume of the data that they produce and the number of applications that could be interested in harvesting such data are growing all the time. Today’s response to the above need is cloud computing. However, cloud computing applications need to be able to scale elastically [22]. Unfortunately there is no slicing, as distributed system primitives that support internal state partitioning [33] and hot swapping and current cloud systems like OpenStack or OpenNebula do not provide elastic monitoring out of the box. This means there is a two-sided problem: 1) how to scale an application elastically and 2) how to monitor the application and know when it should scale in or out. E-SilboPS is the elastic version of SilboPS. I t is the solution for the monitoring problem thanks to its content-based publish/subscribe nature and, unlike other solutions [5], it scales efficiently so as to meet workload demand without overprovisioning or underprovisioning. Additionally, it is based on a newly designed algorithm that shows how to add elasticity in an application with different state constraints: stateless, isolated stateful with external coordination and shared stateful with general coordination. Its evaluation shows that it is able to achieve remarkable speedups where the network layer is the main limiting factor: the calculated efficiency (see Figure 5.8) shows how each configuration performs with respect to adjacent configurations. This provides insight into the actual trending of the whole system in order to predict if the next configuration would offset its cost against the resulting gain in notification throughput. Particular attention has been paid to the evaluation of same-cost deployments in order to find out which one is the best for the given workload demand. Finally, the overhead introduced by the different configurations has been estimated to identify the primary limiting factor for throughput. This helps to determine the intrinsic sequential part and base overhead [26] of an optimal versus a suboptimal deployment. Depending on the type of workload, this can be as low as 10% in a local optimum or as high as 60% when an overprovisioned configuration is deployed for a given workload demand. This Karp-Flatt metric estimation is important for system management because it indicates the direction (scale in or out) in which the deployment has to be changed in order to improve its performance instead of simply using a scale-out policy.

A real case of a cognitive multiplayer game: design and development of the iOS client in Swift and its cloud architecture

as tecnologías emergentes como el cloud computing y los dispositivos móviles están creando una oportunidad sin precedentes para mejorar el sistema educativo, permitiendo tanto a los educadores personalizar y mejorar la experiencia de aprendizaje, como facilitar a los estudiantes que adquieran conocimientos sin importar dónde estén. Por otra parte, a través de técnicas de gamificacion será posible promover y motivar a los estudiantes a que aprendan materias arduas haciendo que la experiencia sea más motivadora. Los juegos móviles pueden ser el camino correcto para dar soporte a esta experiencia de aprendizaje mejorada. Este proyecto integra el diseño y desarrollo de una arquitectura en la nube altamente escalable y con alto rendimiento, así como el propio cliente de iOS, para dar soporte a una nueva version de Temporis, un juego móvil multijugador orientado a reordenar eventos históricos en una línea temporal (e.j. historia, arte, deportes, entretenimiento y literatura). Temporis actualmente está disponible en Google Play. Esta memoria describe el desarrollo de la nueva versión de Temporis (Temporis v.2.0) proporcionando detalles acerca de la mejora y adaptación basados en el Temporis original. En particular se describe el nuevo backend hecho en Go sobre Google App Engine creado para soportar miles de usuarios, asó como otras características por ejemplo como conseguir enviar noticaciones push desde la propia plataforma. Por último, el cliente de iOS en Temporis v.2.0 se ha desarrollado utilizando las últimas y más relevantes tecnologías, prestando especial atención a Swift (el lenguaje de programación nuevo de Apple, que es seguro y rápido), el Paradigma Funcional Reactivo (que ayuda a construir aplicaciones altamente interactivas además de a minimizar errores) y la arquitectura VIPER (una arquitectura que sigue los principios SOLID, se centra en la separación de asuntos y favorece la reutilización de código en otras plataformas). ABSTRACT Emerging technologies such as cloud computing and mobile devices are creating an unprecedented opportunity for enhancing the educational system, letting both educators customize and improve the learning experience, and students acquire knowledge regardless of where they are. Moreover, through gamification techniques it would be possible to encourage and motivate students to learn arduous subjects by making the experience more motivating. Mobile games can be a perfect vehicle to support this enhanced learning experience. This project integrates the design and development of a highly scalable and performant cloud architecture, as well as the iOS client that uses it, in order to provide support to a new version of Temporis, a mobile multiplayer game focused on ordering time-based (e.g. history, art, sports, entertainment and literature) in a timeline that currently is available on Google Play. This work describes the development of the new Temporis version (Temporis v.2.0), providing details about improvements and details on the adaptation of the original Temporis. In particular, the new Google App Engine backend is described, which was created to support thousand of users developed in Go language are provided, in addition to other features like how to achieve push notications in this platform. Finally, the mobile iOS client developed using the latest and more relevant technologies is explained paying special attention to Swift (Apple's new programming language, that is safe and fast), the Functional Reactive Paradigm (that helps building highly interactive apps while minimizing bugs) and the VIPER architecture (a SOLID architecture that enforces separation of concerns and makes it easy to reuse code for other platforms).

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Testing a Cloud Provider Network for Hybrid P2P and Cloud Streaming Architectures

The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters.

CumuloNimbo: Una plataforma como servicio con procesamiento transaccional altamente escalable.

El modelo de computaci¿on en la nube (cloud computing) ha ganado mucha popularidad en los últimos años, prueba de ello es la cantidad de productos que distintas empresas han lanzado para ofrecer software, capacidad de procesamiento y servicios en la nube. Para una empresa el mover sus aplicaciones a la nube, con el fin de garantizar disponibilidad y escalabilidad de las mismas y un ahorro de costes, no es una tarea fácil. El principal problema es que las aplicaciones tienen que ser rediseñadas porque las plataformas de computaci¿on en la nube presentan restricciones que no tienen los entornos tradicionales. En este artículo presentamos CumuloNimbo, una plataforma para computación en la nube que permite la ejecución y migración de manera transparente de aplicaciones multi-capa en la nube. Una de las principales características de CumuloNimbo es la gestión de transacciones altamente escalable y coherente. El artículo describe la arquitectura del sistema, así como una evaluaci¿on de la escalabilidad del mismo.

A federated repository for PaaS components in a multi-cloud environment

Cloud computing has seen an impressive growth in recent years, with virtualization technologies being massively adopted to create IaaS (Infrastructure as a Service) public and private solutions. Today, the interest is shifting towards the PaaS (Platform as a Service) model, which allows developers to abstract from the execution platform and focus only on the functionality. There are several public PaaS offerings available, but currently no private PaaS solution is ready for production environments. To fill this gap a new solution must be developed. In this paper we present a key element for enabling this model: a cloud repository based on the OSGi component model. The repository stores, manages, provisions and resolves the dependencies of PaaS software components and services. This repository can federate with other repositories located in the same or different clouds, both private and public. This way, dependencies can be fulfilled collaboratively, and new business models can be implemented.

Tecnología cloud para el hogar digital

El mundo tecnológico está cambiando hacia la optimización en la gestión de recursos gracias a la poderosa influencia de tecnologías como la virtualización y la computación en la nube (Cloud Computing). En esta memoria se realiza un acercamiento a las mismas, desde las causas que las motivaron hasta sus últimas tendencias, pasando por la identificación de sus principales características, ventajas e inconvenientes. Por otro lado, el Hogar Digital es ya una realidad para la mayoría de los seres humanos. En él se dispone de acceso a múltiples tipos de redes de telecomunicaciones (3G, 4G, WI-FI, ADSL…) con más o menos capacidad pero que permiten conexiones a internet desde cualquier parte, en todo momento, y con prácticamente cualquier dispositivo (ordenadores personales, smartphones, tabletas, televisores…). Esto es aprovechado por las empresas para ofrecer todo tipo de servicios. Algunos de estos servicios están basados en el cloud computing sobre todo ofreciendo almacenamiento en la nube a aquellos dispositivos con capacidad reducida, como son los smarthphones y las tabletas. Ese espacio de almacenamiento normalmente está en los servidores bajo el control de grandes compañías. Guardar documentos, videos, fotos privadas sin tener la certeza de que estos no son consultados por alguien sin consentimiento, puede despertar en el usuario cierto recelo. Para estos usuarios que desean control sobre su intimidad, se ofrece la posibilidad de que sea el propio usuario el que monte sus propios servidores y su propio servicio cloud para compartir su información privada sólo con sus familiares y amigos o con cualquiera al que le dé permiso. Durante el proyecto se han comparado diversas soluciones, la mayoría de código abierto y de libre distribución, que permiten desplegar como mínimo un servicio de almacenamiento accesible a través de Internet. Algunas de ellas lo complementan con servicios de streaming tanto de música como de videos, compartición y sincronización de documentos entre múltiples dispositivos, calendarios, copias de respaldo (backups), virtualización de escritorios, versionado de ficheros, chats, etc. El proyecto finaliza con una demostración de cómo utilizar dispositivos de un hogar digital interactuando con un servidor Cloud, en el que previamente se ha instalado y configurado una de las soluciones comparadas. Este servidor quedará empaquetado en una máquina virtual para que sea fácilmente transportable e utilizable. ABSTRACT. The technological world is changing towards optimizing resource management thanks to the powerful influence of technologies such as Virtualization and Cloud Computing. This document presents a closer approach to them, from the causes that have motivated to their last trends, as well as showing their main features, advantages and disadvantages. In addition, the Digital Home is a reality for most humans. It provides access to multiple types of telecommunication networks (3G, 4G, WI-FI, ADSL...) with more or less capacity, allowing Internet connections from anywhere, at any time, and with virtually any device (computer personal smartphones, tablets, televisions...).This is used by companies to provide all kinds of services. Some of these services offer storage on the cloud to devices with limited capacity, such as smartphones and tablets. That is normally storage space on servers under the control of important companies. Saving private documents, videos, photos, without being sure that they are not viewed by anyone without consent, can wake up suspicions in some users. For those users who want control over their privacy, it offers the possibility that it is the user himself to mount his own server and its own cloud service to share private information only with family and friends or with anyone with consent. During the project I have compared different solutions, most open source and with GNU licenses, for deploying one storage facility accessible via the Internet. Some supplement include streaming services of music , videos or photos, sharing and syncing documents across multiple devices, calendars, backups, desktop virtualization, file versioning, chats... The project ends with a demonstration of how to use our digital home devices interacting with a cloud server where one of the solutions compared is installed and configured. This server will be packaged in a virtual machine to be easily transportable and usable.

Valuation: Developer support for by-references to by-value type conversion.

Modern object oriented languages like C# and JAVA enable developers to build complex application in less time. These languages are based on selecting heap allocated pass-by-reference objects for user defined data structures. This simplifies programming by automatically managing memory allocation and deallocation in conjunction with automated garbage collection. This simplification of programming comes at the cost of performance. Using pass-by-reference objects instead of lighter weight pass-by value structs can have memory impact in some cases. These costs can be critical when these application runs on limited resource environments such as mobile devices and cloud computing systems. We explore the problem by using the simple and uniform memory model to improve the performance. In this work we address this problem by providing an automated and sounds static conversion analysis which identifies if a by reference type can be safely converted to a by value type where the conversion may result in performance improvements. This works focus on C# programs. Our approach is based on a combination of syntactic and semantic checks to identify classes that are safe to convert. We evaluate the effectiveness of our work in identifying convertible types and impact of this transformation. The result shows that the transformation of reference type to value type can have substantial performance impact in practice. In our case studies we optimize the performance in Barnes-Hut program which shows total memory allocation decreased by 93% and execution time also reduced by 15%.

An architecture for a heterogeneous private IaaS management system

Cloud computing and, more particularly, private IaaS, is seen as a mature technology with a myriad solutions tochoose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock-in. Several competing and incompatible interfaces and management styles have given even more voice to these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this paper, we propose a management architecture that tries to tackle these problems; it offers a common way of managing several cloud solutions, and an interface that can be tailored to the needs of the user. This management architecture is designed in a modular way, and using a generic information model. We have validated our approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack

An online failure prediction system for private IaaS platforms

The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines di_erent types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments.

Transactional failure recovery for a distributed key-value store

With the advent of cloud computing, many applications have embraced the ensuing paradigm shift towards modern distributed key-value data stores, like HBase, in order to benefit from the elastic scalability on offer. However, many applications still hesitate to make the leap from the traditional relational database model simply because they cannot compromise on the standard transactional guarantees of atomicity, isolation, and durability. To get the best of both worlds, one option is to integrate an independent transaction management component with a distributed key-value store. In this paper, we discuss the implications of this approach for durability. In particular, if the transaction manager provides durability (e.g., through logging), then we can relax durability constraints in the key-value store. However, if a component fails (e.g., a client or a key-value server), then we need a coordinated recovery procedure to ensure that commits are persisted correctly. In our research, we integrate an independent transaction manager with HBase. Our main contribution is a failure recovery middleware for the integrated system, which tracks the progress of each commit as it is flushed down by the client and persisted within HBase, so that we can recover reliably from failures. During recovery, commits that were interrupted by the failure are replayed from the transaction management log. Importantly, the recovery process does not interrupt transaction processing on the available servers. Using a benchmark, we evaluate the impact of component failure, and subsequent recovery, on application performance.

Development of a management system for virtual machines on private clouds

Cloud computing and, more particularly, private IaaS, is seen as a mature technol- ogy with a myriad solutions to choose from. However, this disparity of solutions and products has instilled in potential adopters the fear of vendor and data lock- in. Several competing and incompatible interfaces and management styles have increased even more these fears. On top of this, cloud users might want to work with several solutions at the same time, an integration that is difficult to achieve in practice. In this Master Thesis I propose a management architecture that tries to solve these problems; it provides a generalized control mechanism for several cloud infrastructures, and an interface that can meet the requirements of the users. This management architecture is designed in a modular way, and using a generic infor- mation model. I have validated the approach through the implementation of the components needed for this architecture to support a sample private IaaS solution: OpenStack.

CloudRoom: módulo de gestión de cursos online, abiertos y masivos

La razón de este proyecto, es la de desarrollar el módulo de cursos de la plataforma de Massive Online Open Courses (MOOCs), CloudRoom. Dicho módulo está englobado en una arquitectura orientada a servicios (SOA) y en una infraestructura de Cloud Computing utilizando Amazon Web Services (AWS). Nuestro objetivo es el de diseñar un Software as a Service (SaaS) robusto con las cualidades que a un producto de este tipo se le estiman: alta disponibilidad, alto rendimiento, gran experiencia de usuario y gran extensibilidad del sistema. Para lograrlo, se llevará a cabo la integración de las últimas tendencias tecnológicas dentro del desarrollo de sistemas distribuidos como Neo4j, Node.JS, Servicios RESTful, CoffeeScript. Todo esto siguiendo un estrategia de desarrollo PLAN-DO-CHECK utilizando Scrum y prácticas de metodologías ágiles. ---ABSTRACT---The reason of this Project is to develop the courses‟ module of CloudRoom, a Massive Online Open Courses platform. This module is encapsulated in a service-oriented architecture (SOA) based on a Cloud Computing infrastructure built on Amazon Web Services (AWS). Our goal is to design a robust Software as a Service (SaaS) with the qualities that are estimated in a product of this type: high availability, high performance, great user experience and great extensibility of the system. In order to address this, we carry out the integration of the latest technology trends in the development of distributed systems: Neo4j, Node.JS, RESTful Services and CoffeeScript. All of this, following a development strategy PLAN-DO-CHECK, using Scrum and practices of agile methodologies.

Implementación de una herramienta de productividad para el desarrollo y despliegue de aplicaciones

En la actualidad se está viviendo el auge del Cloud Computing (Computación en la Nube) y cada vez son más las empresas importantes en el sector de las Tecnologías de la Información que apuestan con fuerza por estos servicios. Por un lado, algunas ofrecen servicios, como Amazon y su sistema IaaS (Infrastructure as a Service) Amazon Web Services (AWS); por otro, algunas los utilizan, como ocurre en el caso de este proyecto, en el que Telefonica I+D hace uso de los servicios proporcionados por AWS para sus proyectos. Debido a este crecimiento en el uso de las aplicaciones distribuidas es importante tener en cuenta el papel que desempeñan los desarrolladores y administradores de sistemas que han de trabajar y mantener todas las máquinas remotas de uno o varios proyectos desde una única máquina local. El ayudar a realizar estas tareas de la forma más cómoda y automática posible es el objetivo principal de este proyecto. En concreto, el objetivo de este proyecto es el diseño y la implementación de una solución software que ayude a la productividad en el desarrollo y despliegue de aplicaciones en un conjunto de máquinas remotas desde una única máquina local, teniendo como base una prueba de concepto realizada anteriormente que prueba las funcionalidades más básicas de las librerías utilizadas para el desarrollo de la herramienta. A lo largo de este proyecto se han estudiado las diferentes alternativas que se encuentran en el mercado que ofrecen al menos parte de la soluci6n a los problemas abordados, pese a que los requisitos de la empresa indicaban que la herramienta debía implementarse de forma completa. Se estudió a fondo después la prueba de concepto de la que se partía para, con los conocimientos adquiridos sobre el tema, mejorarla cumpliendo los objetivos marcados. Tras el desarrollo y la implementaci6n completa de la herramienta se proponen posibles caminos a seguir en el futuro. ---ABSTRACT---Nowadays we are experiencing the rise of Cloud Computing and every day more and more important IT companies are betting hard for this kind of services. On one hand, some of these companies offer services such as Amazon IaaS (Infrastructure as a Service) system Amazon Web Services (AWS); on the other hand, some of them use these services, as in the case of this project, in which Telefonica I+D uses the services provided by AWS in their projects. Due this growth in the use of distributed applications it is important to consider the developers and system administrators' roles, who have to work and do the maintenance of all the remote machines from one or several projects from a single local machine. The main goal of this project is to help with these tasks making them as comfortable and automatically as possible. Specifically, the goal of this project is the design and implementation of a software solution that helps to achieve a better productivity in the development of applications on a set of remote machines from a single local machine, based on a proof of concept developed before, in which the basic functionality of the libraries used in this tool were tested. Throughout this project the different alternatives on the market that offer at least part of the solution to the problem addressed have been studied, although according to the requirements of the company, the tool should be implemented from scratch. After that, the basic proof of concept was thoroughly studied and improved with the knowledge acquired on the subject, fulfilling the marked goals. Once the development and full implementation of the tool is done, some ways of improvement for the future are suggested.