Elasticity Measurement in CaaS Environments - Extending the Existing BUNGEE Elasticity Benchmark to AWS\u27s Elastic Container Service

Rapid elasticity and automatic scaling are core concepts of most current cloud computing systems. Elasticity describes how well and how fast cloud systems adapt to increases and decreases in workload. In parallel, software architectures are moving towards employing containerised microservices running on systems managed by container orchestration platforms. Cloud users who employ such container-based systems may want to compare the elasticity of different systems or system settings to ensure rapid elasticity and maintain service level objectives while avoiding over-provisioning. Previous research has established a variety of metrics to measure elasticity. Some existing benchmark tools are designed to measure elasticity in “Infrastructure as a Service” (IaaS) systems, but no research exists to date for measuring elasticity in systems based on containers and container orchestration. In this dissertation, an existing benchmark designed for IaaS systems, the BUNGEE benchmark developed at the University of Würzburg, was extended to be applicable to Amazon’s Elastic Container Service, a container-based cloud system. An experiment was conducted to test if the extension of the BUNGEE benchmark described in this dissertation delivers reproducible results and is therefore valid. For validation, the crucial phase of the benchmark - the system analysis phase - was run 32 times. It was established with statistical tests if the results vary by more than the acceptable level. Results indicate that there is some amount of variability, but it does not exceed the acceptable level and is consistent with the amount of performance variability encountered by other researchers in Amazon’s cloud systems. Therefore, it is concluded that the BUNGEE benchmark is likely applicable to container-based cloud systems. However, some parameters and configuration settings specific to container orchestration systems were identified that could impede reproducibility of results and should be considered in future experiments

Cloud Host Selection using Iterative Particle-Swarm Optimization for Dynamic Container Consolidation

A significant portion of the energy consumption in cloud data centres can be attributed to the inefficient utilization of available resources due to the lack of dynamic resource allocation techniques such as virtual machine migration and workload consolidation strategies to better optimize the utilization of resources. We present a new method for optimizing cloud data centre management by combining virtual machine migration with workload consolidation. Our proposed Energy Efficient Particle Swarm Optimization (EE-PSO) algorithm to improve resource utilization and reduce energy consumption. We carried out experimental evaluations with the Container CloudSim toolkit to demonstrate the effectiveness of the proposed EE-PSO algorithm in terms of energy consumption, quality of service guarantees, the number of newly created VMs, and container migrations

Enabling Distributed Applications Optimization in Cloud Environment

The past few years have seen dramatic growth in the popularity of public clouds, such as Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Container-as-a-Service (CaaS). In both commercial and scientific fields, quick environment setup and application deployment become a mandatory requirement. As a result, more and more organizations choose cloud environments instead of setting up the environment by themselves from scratch. The cloud computing resources such as server engines, orchestration, and the underlying server resources are served to the users as a service from a cloud provider. Most of the applications that run in public clouds are the distributed applications, also called multi-tier applications, which require a set of servers, a service ensemble, that cooperate and communicate to jointly provide a certain service or accomplish a task. Moreover, a few research efforts are conducting in providing an overall solution for distributed applications optimization in the public cloud. In this dissertation, we present three systems that enable distributed applications optimization: (1) the first part introduces DocMan, a toolset for detecting containerized application’s dependencies in CaaS clouds, (2) the second part introduces a system to deal with hot/cold blocks in distributed applications, (3) the third part introduces a system named FP4S, a novel fragment-based parallel state recovery mechanism that can handle many simultaneous failures for a large number of concurrently running stream applications

Cloud provider independence using DevOps methodologies with Infrastructure-as-Code

On choosing cloud computing infrastructure for IT needs there is a risk of becoming dependent and locked-in on a specific cloud provider from which it becomes difficult to switch should an entity decide to move all of the infrastructure resources into a different provider. There’s widespread information available on how to migrate existing infrastructure to the cloud notwithstanding common cloud solutions and providers don't have any clear path or framework for supporting their tenants to migrate off the cloud into another provider or cloud infrastructure with similar service levels should they decide to do so. Under these circumstances it becomes difficult to switch from cloud provider not just because of the technical complexity of recreating the entire infrastructure from scratch and moving related data but also because of the cost it may involve. One possible solution is to evaluate the use of Infrastructure-as-Code languages for defining infrastructure (“Infrastructure-as-Code”) combined with DevOps methodologies and technologies to create a mechanism that helps streamline the migration process between different cloud infrastructure especially if taken into account from the beginning of a project. A well-structured DevOps methodology combined with Infrastructure-as-Code may allow a more integrated control on cloud resources as those can be defined and controlled with specific languages and be submitted to automation processes. Such definitions must take into account what is currently available to support those operations under the chosen cloud infrastructure APIs, always seeking to guarantee the tenant an higher degree of control over its infrastructure and higher level of preparation of the necessary steps for the recreation or migration of such infrastructure should the need arise, somehow integrating cloud resources as part of a development model. The objective of this dissertation is to create a conceptual reference framework that can identify different forms for migration of IT infrastructure while always contemplating a higher provider independence by resorting to such mechanisms, as well as identify possible constraints or obstacles under this approach. Such a framework can be referenced from the beginning of a development project if foreseeable changes in infrastructure or provider are a possibility in the future, taking into account what the API’s provide in order to make such transitions easier.Ao optar-se por infraestruturas de computação em nuvem para soluções de TI existe um risco associado de se ficar dependente de um fornecedor de serviço específico, do qual se torna difícil mudar caso se decida posteriormente movimentar toda essa infraestrutura para um outro fornecedor. Encontra-se disponível extensa documentação sobre como migrar infraestrutura já  existente para modelos de computação em nuvem, de qualquer modo as soluções e os fornecedores de serviço não dispõem de formas ou metodologias claras que suportem os seus clientes em migrações para fora da nuvem, seja para outro fornecedor ou infraestrutura com semelhantes tipos de serviço, caso assim o desejem. Nestas circunstâncias torna-se difícil mudar de fornecedor de serviço não apenas pela complexidade técnica associada à criação de toda a infraestrutura de raiz e movimentação de todos os dados associados a esta mas também devido aos custos que envolve uma operação deste tipo. Uma possível solução é avaliar a utilização de linguagens para definição de infraestrutura como código (“Infrastructure-as-Code”) em conjunção com metodologias e tecnologias “DevOps” de forma a criar um mecanismo que permita flexibilizar um processo de migração entre diferentes infraestruturas de computação em nuvem, especialmente se for contemplado desde o início de um projecto. Uma metodologia “DevOps” devidamente estruturada quando combinada com definição de infraestrutura como código pode permitir um controlo mais integrado de recursos na nuvem uma vez que estes podem ser definidos e controlados através de linguagens específicas e submetidos a processos de automação. Tais definições terão de ter em consideração o que existe disponível para suportar as necessárias operações através das “API’s” das infraestruturas de computação em nuvem, procurando sempre garantir ao utilizador um elevado grau de controlo sobre a sua infraestrutura e um maior nível de preparação dos passos necessários para recriação ou migração da infraestrutura caso essa necessidade surja, integrando de certa forma os recursos de computação em nuvem como parte do modelo de desenvolvimento. Esta dissertação tem como objetivo a criação de um modelo de referência conceptual que identifique formas de migração de infraestruturas de computação procurando ao mesmo tempo uma maior independência do fornecedor de serviço com recurso a tais mecanismos, assim como identificar possíveis constrangimentos ou impedimentos nesta aproximação. Tal modelo poderá ser referenciado desde o início de um projecto de desenvolvimento caso seja necessário contemplar uma possível necessidade futura de alterações ao nível da infraestrutura ou de fornecedor, com base no que as “API’s” disponibilizam, de modo a facilitar essa operação.info:eu-repo/semantics/publishedVersio

Container description ontology for CaaS

[EN] Besides its classical three service models (IaaS, PaaS, and SaaS), container as a service (CaaS) has gained significant acceptance. It offers without the difficulty of high-performance challenges of traditional hypervisors deployable applications. As the adoption of containers is increasingly wide spreading, the use of tools to manage them across the infrastructure becomes a vital necessity. In this paper, we propose a conceptualisation of a domain ontology for the container description called CDO. CDO presents, in a detailed and equal manner, the functional and non-functional capabilities of containers, Dockers and container orchestration systems. In addition, we provide a framework that aims at simplifying the container management not only for the users but also for the cloud providers. In fact, this framework serves to populate CDO, help the users to deploy their application on a container orchestration system, and enhance interoperability between the cloud providers by providing migration service for deploying applications among different host platforms. Finally, the CDO effectiveness is demonstrated relying on a real case study on the deployment of a micro-service application over a containerised environment under a set of functional and non-functional requirements.K. Boukadi; M.a Rekik; J. Bernal Bernabe; Lloret, J. (2020). Container description ontology for CaaS. International Journal of Web and Grid Services (Online). 16(4):341-363. https://doi.org/10.1504/IJWGS.2020.11094434136316

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

Migration of a cloud-based microservice platform to a container solution

Este trabajo presenta las labores realizadas durante 6 meses de prácticas en Gandi SAS, en el proyecto Caliopen. Caliopen es un proyecto open-source de mensajería orientado a respetar la privacidad de sus usuarios. El objetivo del trabajo es la administración y mejora de la plataforma de mensajería del proyecto, haciéndola evolucionar a una solución estable y escalable. La memoria describe el estudio y la implantación de una solución basada en Kubernetes para la nueva plataforma, desplegada en la plataforma de IaaS de Gandi. En el proceso también se describen las diferentes herramientas y utilidades desarrolladas, así como la solución implementada para monitorizar el sistema

Performance analysis of container-based networking solutions for high-performance computing cloud

Recently, cloud service providers have been gradually changing from virtual machine-based cloud infrastructures to container-based cloud-native infrastructures that consider performance and workload-management issues. Several data network performance issues for virtual instances have arisen, and various networking solutions have been newly developed or utilized. In this paper, we propose a solution suitable for a high-performance computing (HPC) cloud through a performance comparison analysis of container-based networking solutions. We constructed a supercomputer-based test-bed cluster to evaluate the serviceability by executing HPC jobs