ABSTRACT Background Topology and Orchestration Specification for Cloud Applications (TOSCA) is a specification language used for modelling topology and orchestration of cloud applications. This language particularly allows the description of workflows that can be used for specifying management tasks such as (un)deployment plans. Motivations This textual language for describing TOSCA workflows does not provide any visual notation for graphically designing or observing the corresponding workflows. Moreover, this specification language is error‐prone and can be source of mistakes during the writing of the management plans. Methods In this article, we propose a transformation from TOSCA to the graphical Business Process Model and Notation (BPMN), which allows the visualisation of TOSCA workflows. We also provide automated verification techniques for analysing TOSCA (un)deployment workflows in terms of functional and architectural properties as well as execution times. The transformation and verification steps are achieved in a fully automated way. Results This approach computes BPMN models and verification results within a reasonable time on realistic applications.

We demonstrate a new customizable toolchain for validating Kubernetes manifests. The toolchain supports multiple types of validation, including validations against JSON schema, Kubernetes built-in rules, best practices, and custom business rules expressed in Common Expression Language (CEL). It also enables the detection of inconsistencies within a defined set of rules. The main goal is to highlight the value of each validation type and demonstrate how their combination improves the robustness of Kubernetes manifests, ensuring reliable deployments.

Modern distributed applications increasingly rely on cloud-native platforms to abstract the complexity of deployment and scalability. As the de facto orchestration standard, Kubernetes enables this abstraction, but its declarative configuration model makes the architectural understanding difficult. Developers, operators, and architects struggle to form accurate mental models from raw manifests, Helm charts, or cluster state descriptions. We introduce KubeDiagrams, an open-source tool that transforms Kubernetes manifests into architecture diagrams. By grounding our design in a user-centered study of real-world visualization practices, we identify the specific challenges Kubernetes users face and map these to concrete design requirements. KubeDiagrams integrates seamlessly with standard Kubernetes artifacts, preserves semantic fidelity to core concepts, and supports extensibility and automation. We detail the tool’s architecture, visual encoding strategies, and extensibility mechanisms. Three case studies illustrate how KubeDiagrams enhances system comprehension and supports architectural reasoning in distributed cloud-native systems. KubeDiagrams addresses concrete pain points in Kubernetes-based DevOps practices and is valued for its automation, clarity, and low-friction integration into real-world tooling environments.

Cloud computing offers opportunities to increase productivity and reduce costs. Quickly adapting to changing needs is key to maintaining cloud applications. In traditional development, coordination is implemented in computational code. Although change impact analyses are studied, adjusting the implementation is time-consuming and error-prone when the coordination strategy changes. Exogenous coordination separates the implemented coordination and computational code to cope with this problem. This separation improves the reusability of components. Additionally, other applications with similar interaction patterns can reuse the coordination specification. The main contribution of this paper is to propose a methodology to develop and maintain cloud applications following the exogenous approach. To illustrate the idea, we introduce a new framework named OCCIwareBIP, which integrates JavaBIP — a framework for the exogenous coordination of concurrent Java components into OCCIware — a framework for designing cloud applications. We also leverage the coordination model to verify the deadlock-freedom of the cloud application. Finally, we present an application to show the ability of our approach to guarantee the safety and benefits of modularization in developing concurrent cloud applications.

Abstract Deploying a cloud configuration in a real cloud platform is mostly cost- and time- consuming, as large number of cloud resources have to be rented for the time needed to run the configuration. Thereafter, cloud simulation tools are used as a cheap alternative to test cloud configuration. However, most of the existing cloud simulation tools require extensive technical skills and do not support simulation of any kind of cloud resources. In this context, using a model-driven approach can be helpful as it allows developers to efficiently describe their needs at a high level of abstraction. To do, we propose, in this article, a model-driven engineering approach based on the Open Cloud Computing Interface(OCCI) standard metamodel and CloudSim toolkit. We firstly extend OCCI metamodel for the supporting simulation of any kind of cloud resources. Afterward, to illustrate the extensibility of our approach, we enrich the proposed metamodel by new simulation capabilities. As proof of concept, we study the elasticity and pricing strategies of Amazon Web Services (AWS). This article benefits from OCCIware Studio to design an OCCI simulation extension and to provide a simulation designer for designing cloud configurations to be simulated. We detail the approach process from defining an OCCI simulation extension until the generation and the simulation of the OCCI cloud configurations. Finally, we validate the proposed approach by providing a realistic experimentation to study its usability, the resources coverage rate and the cost. The results are compared with the ones computed from AWS.

Elasticity is considered as a fundamental feature of cloud computing where the system capacity can adjust to the current application workloads by provisioning or de-provisioning computing resources automatically and timely. Many studies have been already conducted to elasticity management systems, however, almost all lack to offer a complete modular solution. In this article, we proposeMoDEMO, a new elasticity management system powering both vertical and horizontal elasticities, both VM and Container virtualization technologies, multiple cloud providers simultaneously, and various elasticity policies.MoDEMOis characterized by the following features: it represents (i) the first system that manages elasticity using Open Cloud Computing Interface (OCCI) model with respect to the OCCI standard specifications, (ii) the first unified system which combines the functionalities of the worldwide cloud providers: Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP), and (iii) allows a dynamic configuration at runtime during the execution of the application.MoDEMOpermits to timely adapt resource capacity according to the workload intensity and increase application performance without introducing a significant overhead.

In the context of Network Functions Virtualization (NFV), telecommunication systems are more and more deployed on the cloud, using orchestration engines such as OpenStack Heat. Heat takes as input templates that describe the components of the target system and automatically performs the deployment. This prevents consumers of cloud services from handling the challenges of manual deployment. However, deploying such systems remains challenging. Indeed, the templates given to Heat may contain errors that can lead to a failed or a partial deployment, thus compromising the systems reliability. To handle this challenge, we propose a formal approach and a tool for the verification of templates consistency prior to launching their deployment. A case study is presented to validate the approach.

We demonstrate a lightweight toolchain for validating descriptors of network functions compliant with the latest ETSI NFV standards, visualizing these descriptors in the form of various diagrams (i.e. network-oriented, function-oriented, and UML2-based), analyzing these descriptors formally with the Alloy Analyzer, and deploying these virtualized network functions on OpenStack.

With the advent of cloud computing, different cloud providers with heterogeneous services and Application Programming Interfaces (APIs) have emerged. Hence, building an interoperable multi-cloud system becomes a complex task. Our idea is to design fclouds framework to achieve semantic interoperability in multi-clouds, i.e., to identify the common concepts between cloud APIs and to reason over them. In this paper, we propose to take advantage of the Open Cloud Computing Interface (OCCI) standard and the Alloy formal specification language to define the fclouds language, which is a formal language for specifying heterogeneous cloud APIs. To do so, we formalize OCCI concepts and operational semantics, then we identify and validate five properties (consistency, sequentiality, reversibility, idempotence and safety) that denote their characteristics. To demonstrate the effectiveness of our cloud formal language, we present thirteen case studies where we formally specify infrastructure, platform, Internet of Things (IoT) and transverse cloud concerns. Thanks to the Alloy analyzer, we verify that these heterogeneous APIs uphold the properties of fclouds and also validate their own specific properties. Then, thanks to formal transformation rules and equivalence properties, we draw a precise alignment between our case studies, which promotes semantic interoperability in a multi-cloud system.

Elasticity is a key feature in cloud computing as it enables the automatic and timely provisioning and depro- visioning of computing resources. To achieve elasticity, clouds rely on virtualization techniques including Virtual Machines (VMs) and containers. While many studies address the vertical elasticity of VMs and other few works handle vertical elasticity of containers, no work manages the coordination between these two ver- tical elasticities. In this paper, we present the first approach to coordinate vertical elasticity of both VMs and containers. We propose an auto-scaling technique that allows containerized applications to adjust their resources at both container and VM levels. This work has been evaluated and validated using the RUBiS benchmark application. The results show that our approach reacts quickly and improves application perfor- mance. Our coordinated elastic controller outperforms container vertical elasticity controller by 18.34% and VM vertical elasticity controller by 70%. It also outperforms container horizontal elasticity by 39.6%.

To tackle the cloud-provider lock-in, the Open Grid Forum (OGF) is developing the Open Cloud Computing Interface (OCCI), a standardized interface for managing any kind of cloud resources. Besides the OCCI Core model, which defines the basic modeling elements for cloud resources, the OGF also defines extensions that reflect the requirements of different cloud service levels, such as IaaS and PaaS. However, so far the OCCI PaaS extension is very coarse grained and lacks of supporting use cases and implementations. Especially, it does not define how the components of the application itself can be managed. In this paper, we present a model-driven framework that extends the OCCI PaaS extension and is able to use different configuration management tools to manage the whole lifecycle of cloud applications. We demonstrate the feasibility of the approach by presenting four different use cases and prototypical implementations for three different configuration management tools.

Today, Google Cloud Platform (GCP) is one of the leaders among cloud APIs. Although it was established only five years ago, GCP has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP Model, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP. GCP Model is conform to the Open Cloud Computing Interface (OCCI) metamodel and is implemented based on the open source model-driven Eclipse-based OCCIware tool chain. Thanks to our GCP Model, we offer corrections to the drawbacks we identified.

Elasticity is a fundamental property in cloud computing that has recently witnessed major developments. This article reviews both classical and recent elasticity solutions and provides an overview of containerization, a new technological trend in lightweight virtualization. It also discusses major issues and research challenges related to elasticity in cloud computing. We comprehensively review and analyze the proposals developed in this field. We provide a taxonomy of elasticity mechanisms according to the identified works and key properties. Compared to other works in literature, this article presents a broader and detailed analysis of elasticity approaches and is considered as the first survey addressing the elasticity of containers.

Elasticity is the key feature of cloud computing to scale computing resources according to application workloads timely. In the literature as well as in industrial products, much attention was given to the elasticity of virtual machines, but much less to the elasticity of containers. However, containers are the new trend for packaging and deploying microservices-based applications. Moreover, most of approaches focus on horizontal elasticity, fewer works address vertical elasticity. In this paper, we propose ELASTICDOCKER, the first system powering vertical elasticity of Docker containers autonomously. Based on the well-known IBM's autonomic computing MAPE-K principles, ELASTICDOCKER scales up and down both CPU and memory assigned to each container according to the application workload. As vertical elasticity is limited to the host machine capacity, ELASTICDOCKER does container live migration when there is no enough resources on the hosting machine. Our experiments show that ELASTICDOCKER helps to reduce expenses for container customers, make better resource utilization for container providers, and improve Quality of Experience for application end-users. In addition, based on the observed migration performance metrics, the experiments reveal a high efficient live migration technique. As compared to horizontal elasticity, ELASTICDOCKER outperforms Kubernetes elasticity by 37.63%.

Multi-cloud computing has been proposed as a way to reduce vendor lock-in, to improve resiliency during outages and geo-presence, to boost performance and to lower costs. However, semantic differences between cloud providers, as well as their heterogeneous management interfaces, make changing from one provider to another very complex and costly. This is quite challenging for the implementation of multi-cloud systems. In this paper, we aim to take advantage of formal methods to define a precise semantics for multi-clouds. We propose fclouds, a formal-based framework for semantic interoperability in multi-clouds. This framework contains a catalogue of formal models that mathematically describe cloud APIs and reason over them. A precise alignment can be described between their concepts, which promotes semantic interoperability.

With the emergence of Docker, it becomes easier to encapsulate applications and their dependencies into lightweight Linux containers and make them available to the world by deploying them in the cloud. Compared to hypervisor-based virtualization approaches, the use of containers provides faster start-ups times and reduces the consumption of computer resources. However, Docker lacks of deployability verification tool for containers at design time. Currently, the only way to be sure that the designed containers will execute well is to test them in a running system. If errors occur, a correction is made but this operation can be repeated several times before the deployment becomes operational. Docker does not provide a solution to increase or decrease the size of container resources in demand. Besides the deployment of containers, Docker lacks of synchronization between the designed containers and those deployed. Moreover, container management with Docker is done at low level, and therefore requires users to focus on low level system issues. In this paper we focus on these issues related to the management of Docker containers. In particular, we propose an approach for modeling Docker containers. We provide tooling to ensure the deployability and the management of Docker containers. We illustrate our proposal using an event processing application and show how our solution provides a significantly better compromise between performance and development costs than the basic Docker container solution.

Open Cloud Computing Interface (OCCI) proposes one of the first widely accepted, community-based, open standards for managing any kinds of cloud resources. But as it is specified in natural language, OCCI is imprecise, ambiguous, incomplete, and needs a precise definition of its core concepts. Indeed, the OCCI Core Model has conceptual drawbacks: an imprecise semantics of its type classification system, a nonextensible data type system for OCCI attributes, a vague and limited extension concept and the absence of a configuration concept. To tackle these issues, this paper proposes a precise metamodel for OCCI. This metamodel defines rigourously the static semantics of the OCCI core concepts, of a precise type classification system, of an extensible data type system, and of both extension and configuration concepts. This metamodel is based on the Eclipse Modeling Framework (EMF), its structure is encoded with Ecore and its static semantics is rigourously defined with Object Constraint Language (OCL). As a consequence, this metamodel provides a concrete language to precisely define and exchange OCCI models. The validation of our metamodel is done on the first world-wide dataset of OCCI extensions already published in the literature, and addressing inter-cloud networking, infrastructure, platform, application, service management, cloud monitoring, and autonomic computing domains, respectively. This validation highlights simplicity, consistency, correctness, completeness, and usefulness of the proposed metamodel.

Cloud platforms are increasingly being used for hosting a broad diversity of services from traditional e-commerce applications to interactive web-based Ides. How-ever, we observe that the proliferation of offers by cloud providers raises several challenges. Developers will not only have to deploy applications for a specific cloud, but will also have to consider migrating services from one cloud to another, and to manage distributed applications spanning multiple clouds. In this paper, we present our federated multi-cloud PaaS infrastructure for addressing these challenges. This infrastructure is based on three foundations: i) an open service model used to design and implement both our multi-cloud PaaSand the SaaS applications running on top of it, ii) a configurable architecture of the federated PaaS, and iii) some infrastructure services for managing both our multi-cloud PaaS and the SaaS applications. We then show how this multi-cloud PaaS can be deployed on top of thirteen existing IaaS/PaaS. We finally report on three distributed SaaS applications developed with and deployed on our federated multi-cloud PaaS infrastructure.

Distributed systems like crisis management are subject to the dissemination of a huge volume of heterogeneous events, ranging from low level network data to high level crisis management intelligence, depending on the role of the rescue teams involved. In such systems, Complex Event Processing (CEP) has emerged as a solution to detect and react (in real-time) to complex events, which are correlations of more primitive events. Although various CEP engines implement the support for dealing with the business heterogeneity of events, the technological integration of these events remains uncovered. Therefore, in this paper we introduce DiCEPE (Distributed Complex Event Processing Engine), a platform which focuses on the integration of CEP engines in distributed systems. DiCEPE provides a native support for various communication protocols in order to federate CEP engines and ease the deployment of complex systems-of-systems. We illustrate our proposal using a nuclear crisis management scenario and show how DiCEPE leverages the coordination and the federation of different CEP engines.

SUMMARY ThetextitService Component Architecture (SCA) is a technology‐independent standard for developing distributed Service‐oriented Architectures (SOA). The SCA standard promotes the use of components and architecture descriptors, and mostly covers the lifecycle steps of implementation and deployment. Unfortunately, SCA does not address the governance of SCA applications and provides no support for the maintenance of deployed components. This article covers this issue and introduces the F RA SCA TI platform, a run‐time support for SCA with dynamic reconfiguration capabilities and run‐time management features. This article presents the internal component‐based architecture of the F RA SCA TI platform, and highlights its key features. The component‐based design of the F RA SCA TI platform introduces many degrees of flexibility and configurability in the platform itself and it can host the SOA applications. This article reports on micro‐benchmarks highlighting that run‐time manageability in the F RA SCA TI platform does not decrease its performance when compared with the de facto reference SCA implementation: Apache T USCANY . Finally, a smart home scenario illustrates the extension capabilities and the various reconfigurations of the F RA SCA TI platform. Copyright © 2011 John Wiley & Sons, Ltd.

SCA (Service Component Architecture) is an OASIS standard for describing service-oriented middleware architectures. In particular, SCA promotes a disciplined way for designing distributed architectures based on a component model and an Architecture Description Language (ADL). However, SCA does not cover the deployment and the run-time management of SCA applications. In this paper, we therefore describe the FraSCAti platform, which provides run-time support, deployment capabilities, and run-time management for SCA. Compared to state-of-the-art platforms, FraSCAti brings a dynamic reflective support to SCA and enables both introspecting and reconfiguring service-oriented architectures at run-time. To achieve this capability, the components are completed by a dedicated container, which is automatically generated by the platform. Furthermore, FraSCAti is a highly configurable platform that can be easily customized by finely selecting the features and functionalities which need to be included. In this way, the platform can be adapted to different application needs and middleware environments.

In this paper, we present DeployWare to address the deployment of distributed and heterogeneous software systems on large scale infrastructures such as grids. Deployment of software systems on grids raises many challenges like: 1) the complexity to take into account orchestration of all the deployment tasks and management of software dependencies; 2) the heterogeneity of both physical infrastructures and software composing the system to deploy; 3) the validation to early detect errors before concrete deployments; and 4) scalability to tackle thousands of nodes. To address these challenges, DeployWare provides a metamodel that abstracts concepts of the deployment, a virtual machine that executes deployment processes on grids from DeployWare descriptions, and a graphical console that allows to manage deployed systems, at runtime. To validate our approach, we have experimented DeployWare with a lot of software technologies, such as CORBA and SOA-based systems, on one thousand of nodes of Grid'5000, the french experimental grid infrastructure.

The Real-Time Specification for Java (RTSJ) is becoming a popular choice in the world of real-time programming. However, the complexities introduced by RTSJ bring the needs for an extensive framework comprising all the aspects of RTSJ development. As the first contribution of this paper, we present a real-time component model directly fitting the needs of RTSJ. Our motivation is to clearly separate real-time and business concerns of applications. We further argue that the RTSJ concerns need to be considered at early stages of architecture design in order to mitigate the complexities of the implementation phase. Therefore, as our second contribution, we propose a design process introducing gradually RTSJ concepts into the architecture. We are thus able to alleviate the development of real-time systems and to tailor them for different real-time conditions. Finally, we demonstrate the feasibility of our solution on an example scenario.

Multiplication of mobile devices and generalized use of wireless networks imply changes on the design and execution of distributed software applications targeting ubiquitous computing. Many strong requirements have to be addressed: heterogeneity and limited resources of wireless networks and mobile devices, networked communications between distributed applications, dynamic discovery and automatic deployment on mobile devices. In this paper, we present a component-based software infrastructure to design, discover, deploy, and execute ubiquitous contextual services, i.e. distributed applications providing services to mobile end-users but only available from a particular place. These ubiquitous contextual services are designed as assemblies of distributed software components. These assemblies are dynamically discovered according to end-users' physical location and device capabilities. Then, appropriate assemblies are automatically deployed on users' devices. We have implemented this approach (the software infrastructure and a ubiquitous application example) on top of the OMG CORBA Component Model and the OpenCCM open source platform

Building component-based distributed applications is a complex task involving a set of cooperating actors like architects, developers, transactions or persistency specialists. For more than ten years, the Object Management Group (OMG) has defined open standards to build interoperable distributed applications. First, the Common Object Request Broker Architecture (CORBA) introduced interoperability between heterogeneous distributed objects, object oriented middleware. Now, the Model Driven Architecture (MDA) has introduced interoperability between heterogeneous models, model oriented middleware. In this context, we advocate the separation of concerns in order to structure the modeling and meta modeling of enterprise distributed component architectures. In the meantime, design related knowledge is most often lost at runtime. Nevertheless, this knowledge could be important to reify architectures of applications at runtime and to support their administration and reconfiguration. Thus, we intend to support separation of concerns from design to runtime of applications, using a meta data repository centric approach. This paper discusses our proposal, CODeX, to structure the definition of meta models in order to offer dedicated points of view of a model to each of the actors of the software engineering process, from architects to application administrators.

Nowadays, autonomous distributed systems, such as large-scale telecom and manufacturing applications, rely on the use of middleware. In order to find back resources and to interconnect applications, the middleware has to provide a trading function. Unfortunately, standard traders such as the ODP/OMG CosTrading service, are error-prone due to the lack of type checking at compilation time, but only performed at runtime. In order to address this problem, we have defined the Trader Oriented Request Broker Architecture (TORBA) to provide a trading framework and its associated tools, which tend to offer type-safe trading operations that are simple to use from applications and checked at compilation time. Based on the concept of Trading Contracts, a resource is described using the TORBA Definition Language, and then compiled to generate trading proxies offering simple interfaces to applications. The example used in this paper clearly states the benefits brought by the TDL trading contracts: type checking at compilation time, simple to use, and providing a powerful and reliable framework for CORBA object trading.