Cloud computing is characterized by a model in which computing resources are delivered as services in a pay-as-you-go manner, which eliminates the need for upfront investments, reducing the time to market and opportunity costs. Despite its benefits, cloud computing brought new concerns about provider dependence and data confidentiality, which further led to a growing trend on consuming resources from multiple clouds. However, building multi-cloud systems is still very challenging and time consuming due to the heterogeneity across cloud providers' offerings and the high-variability in the configuration of cloud providers.This variability is reflected by the large number of available services and the many different ways in which they can be combined and configured. In order to ensure correct setup of a multi-cloud environment, developers must be aware of service offerings and configuration options from multiple cloud providers. To tackle this problem, this thesis proposes a software product line-based approach for managing the variability in cloud environments in order to automate the setup and adaptation of multi-cloud environments. The contributions of this thesis enable to automatically generate a configuration or reconfiguration plan for a multi-cloud environment from a description of its requirements. The conducted experiments aim to assess the impact of the approach on the automated analysis of feature models and the feasibility of the approach to automate the setup and adaptation of multi-cloud environments.

To benefit from the promise of the cloud computing paradigm, applications must be deployed on well-suited and configured cloud environments fulfilling the application's requirements. We consider that the selection and configuration of such environments can leverage Software Product Line (SPL) principles. SPLs were defined to take advantage of software commonalities through the definition of reusable artifacts. This thesis thus proposes an approach based on SPLs to select and configure cloud environments regarding the requirements related to the application to deploy. In particular, we introduce a variability model enabling the description of commonalities and variabilities between clouds as feature models. In addition, we extend this variability model with attributes and cardinalities, together with constraints over them. Then, we propose an approach to check the consistency of cardinality-based feature models when evolving those models. Our approach provides a support to detect and explain automatically a cardinality inconsistency. Finally, we propose an automated platform to select and configure cloud environments, which generates configuration scripts regarding the requirements of the application to deploy. This work has been done as part of the European PaaSage project. The experiments we conducted to evaluate our approach show that it is well suited to handle the configuration of cloud environments, being both scalable and practical while improving the reliability of the deployment.

This book discusses various aspects of the multi-cloud paradigm. The initial portion of the book focuses on the motivations for the industry to embrace a multi-cloud option and the distinct business, technology, and user cases of multi-cloud implementations. The middle part of the book explains the challenges of setting up and sustaining multi-cloud environments. The latter portion focuses on the next-generation technologies and tools along with multi-cloud platforms, processes, patterns, and practices. The final segment of the book is dedicated for cloud brokerage systems. The various traits and tenets of cloud brokerage services especially for accomplishing cloud intermediation, integration, orchestration, governance, security, management, configuration, etc. are explained in detail. The book also clearly articulates how to have intelligent brokers.

This books is open access under a CC BY 4.0 license. This book summarizes work being undertaken within the collaborative MODAClouds research project, which aims to facilitate interoperability between heterogeneous Cloud platforms and remove the constraints of deployment, portability, and reversibility for end users of Cloud services. Experts involved in the project provide a clear overview of the MODAClouds approach and explain how it operates in a variety of applications. While the wide spectrum of available Clouds constitutes a vibrant technical environment, many early-stage issues pose specific challenges from a software engineering perspective. MODAClouds will provide methods, a decision support system, and an open source IDE and run-time environment for the high-level design, early prototyping, semiautomatic code generation, and automatic deployment of applications on multiple Clouds. It will free developers from the need to commit to a fixed Cloud technology stack during software design and offer benefits in terms of cost savings, portability of applications and data between Clouds, reversibility (moving applications and data from Cloud to non-Cloud environments), risk management, quality assurance, and flexibility in the development process.

The current work provides CIOs, software architects, project managers, developers, and cloud strategy initiatives with a set of architectural patterns that offer nuggets of advice on how to achieve common cloud computing-related goals. The cloud computing patterns capture knowledge and experience in an abstract format that is independent of concrete vendor products. Readers are provided with a toolbox to structure cloud computing strategies and design cloud application architectures. By using this book cloud-native applications can be implemented and best suited cloud vendors and tooling for individual usage scenarios can be selected. The cloud computing patterns offer a unique blend of academic knowledge and practical experience due to the mix of authors. Academic knowledge is brought in by Christoph Fehling and Professor Dr. Frank Leymann who work on cloud research at the University of Stuttgart. Practical experience in building cloud applications, selecting cloud vendors, and designing enterprise architecture as a cloud customer is brought in by Dr. Ralph Retter who works as an IT architect at T‐Systems, Walter Schupeck, who works as a Technology Manager in the field of Enterprise Architecture at Daimler AG,and Peter Arbitter, the former head of T Systems’ cloud architecture and IT portfolio team and now working for Microsoft. Voices on Cloud Computing Patterns Cloud computing is especially beneficial for large companies such as Daimler AG. Prerequisite is a thorough analysis of its impact on the existing applications and the IT architectures. During our collaborative research with the University of Stuttgart, we identified a vendor-neutral and structured approach to describe properties of cloud offerings and requirements on cloud environments. The resulting Cloud Computing Patterns have profoundly impacted our corporate IT strategy regarding the adoption of cloud computing. They help our architects, project managers and developers in the refinement of architectural guidelines and communicate requirements to our integration partners and software suppliers. Dr. Michael Gorriz – CIO Daimler AG Ever since 2005 T-Systems has provided a flexible and reliable cloud platform with its “Dynamic Services”. Today these cloud services cover a huge variety of corporate applications, especially enterprise resource planning, business intelligence, video, voice communication, collaboration, messaging and mobility services. The book was written by senior cloud pioneers sharing their technology foresight combining essential information and practical experiences. This valuable compilation helps both practitioners and clients to really understand which new types of services are readily available, how they really work and importantly how to benefit from the cloud. Dr. Marcus Hacke – Senior Vice President, T-Systems International GmbH This book provides a conceptual framework and very timely guidance for people and organizations building applications for the cloud. Patterns are a proven approach to building robust and sustainable applications and systems. The authors adapt and extend it to cloud computing, drawing on their own experience and deep contributions to the field. Each pattern includes an extensive discussion of the state of the art, with implementation considerations and practical examples that the reader can apply to their own projects. By capturing our collective knowledge about building good cloud applications and by providing a format to integrate new insights, this book provides an important tool not just for individual practitioners and teams, but for the cloud computing community at large. Kristof Kloeckner – General Manager,Rational Software, IBMSoftware Group

This book summarizes work being undertaken within the collaborative MODAClouds research project, which aims to facilitate interoperability between heterogeneous Cloud platforms and remove the constraints of deployment, portability, and reversibility for end users of Cloud services. Experts involved in the project provide a clear overview of the MODAClouds approach and explain how it operates in a variety of applications.While the wide spectrum of available Clouds constitutes a vibrant technical environment, many early-stage issues pose specific challenges from a software engineering perspective. MODAClouds will provide methods, a decision support system, and an open source IDE and run-time environment for the high-level design, early prototyping, semiautomatic code generation, and automatic deployment of applications on multiple Clouds. It will free developers from the need to commit to a fixed Cloud technology stack during software design and offer benefits in terms of cost savings, portability of applications and data between Clouds, reversibility (moving applications and data from Cloud to non-Cloud environments), risk management, quality assurance, and flexibility in the development process. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.