Fully automated provisioning and deployment of applications is one of the most essential prerequisites to make use of the benefits of Cloud computing in order to reduce the costs for managing applications. A huge variety of approaches, tools, and providers are available to automate the involved processes. The DevOps community, for instance, provides tooling and reusable artifacts to implement deployment automation in an application-oriented manner. Platform-as-a-Service frameworks are available for the same purpose. In this work we systematically classify and characterize available deployment approaches independently from the underlying technology used. For motivation and evaluation purposes, we choose Web applications with different technology stacks and analyze their specific deployment requirements. Afterwards, we provision these applications using each of the identified types of deployment approaches in the Cloud to perform qualitative and quantitative measurements. Finally, we discuss the evaluation results and derive recommendations to decide which deployment approach to use based on the deployment requirements of an application. Our results show that deployment approaches can also be efficiently combined if there is no `best fit' for a particular application.

The wide adoption of the cloud computing paradigm by many different domains has increased both the number and type of available offerings as a service, e.g. Database-as-a-service (DBaaS) or Platform-as-a-Service (PaaS), and with them the possibilities to deploy and operate an application partially or completely in the cloud. The need for providing design support to application developers in this environment is the focus of this work. Toward this goal, in the following we first scope the discussion on the persistence layer of applications and we investigate the effect of different deployment scenarios on the performance of the application over time. Based on the results of this analyses we then propose an application (re-)distribution design support process, which we evaluate empirically by means of a well-known application. The results of this evaluation both highlight the strengths of our proposal, and at the same time, provide a clear path for the following steps in our work.

The Cloud computing paradigm emerged by establishing new resources provisioning and consumption models. Together with the improvement of resource management techniques, these models have contributed to an increase in the number of application developers that are strong supporters of partially or completely migrating their application to a highly scalable and pay-per-use infrastructure. In this paper we derive a set of functional and non-functional requirements and propose a process-based approach to support the optimal distribution of an application in the Cloud in order to handle fluctuating over time workloads. Using the TPC-H workload as the basis, and by means of empirical workload analysis and characterization, we evaluate the application persistence layer's performance under different deployment scenarios using generated workloads with particular behavior characteristics.

In the last years Cloud computing has become popular among IT organizations aiming to reduce their operational costs. Applications can be designed to run in the Cloud, or can be partially or completely migrated to it. Migrating the data layer of an application to the Cloud, however, implies that existing applications might need to be adapted in order to access their migrated to the Cloud databases. In this work we examine how we can use an existing ESB to enable transparent access to the relational data store running either in the Cloud or on-premise. The goal of our approach is to minimize the effort required to adapt the application. In particular, we discuss the requirements and prototype realization of a Cloud aware data access layer for transparent data access, using an existing open source and multi-tenant aware ESB as the basis. We then evaluate the performance of our proposed solution by considering different Cloud providers and using example data from an existing benchmark as application workload.

Nowadays different Cloud services enable enterprises to migrate applications to the Cloud. An application can be partially migrated by replacing some of its components with Cloud services, or by migrating one or multiple of its layers to the Cloud. As a result, accessing application data stored off-premise requires mechanisms to mitigate the negative impact on Quality of Service (QoS), e.g. due to network latency. In this work, we propose and realize an approach for transparently accessing data migrated to the Cloud using a multi-tenant open source Enterprise Service Bus (ESB) as the basis. Furthermore, we enhance the ESB with QoS awareness by integrating it with an open source caching solution. For evaluation purposes we generate a representative application workload using data from the TPC-H benchmark. Based on this workload, we then evaluate the optimal caching strategy among multiple eviction algorithms when accessing relational databases located at different Cloud providers.

Fully automated provisioning and deployment in order to reduce the costs for managing applications is one of the most essential requirements to make use of the benefits of Cloud computing. Several approaches and tools are available to automate the involved processes. The DevOps community, for example, provides tooling and artifacts to realize deployment automation on Infrastructure as a Service level in a mostly application-oriented manner. Platform as a Service frameworks are also available for the same purpose. In this paper we categorize and characterize available deployment approaches independently from the underlying technology used. For this purpose, we choose Web applications with different technology stacks and analyze their specific deployment requirements. Afterwards, we provision these applications using each of the identified types of deployment approaches in the Cloud. Finally, we discuss the evaluation results and derive recommendations which deployment approach to use based on the deployment requirements of an application.

The Platform as a Service (PaaS) model promotes the development and deployment of applications on top of middleware solutions offered by the provider. Deploying an application in this model entails both the deployment of the application on top of the platform, but potentially also the deployment of the middleware components required by the application. Existing works enable the abstraction from the underlying infrastructure and allow for the creation of generic deployment plans for middleware components that automate the deployment of applications. In this paper we propose a middleware-oriented deployment approach that defines how the deployment of middleware components can be defined in a manner that allows to offer them as PaaS building blocks, and enable the automatic deployment of application components on them. We also present an evaluation of our proposal, together with the lessons learned during this activity.

Migrating an existing application to the Cloud is a complex and multi-dimensional problem requiring in many cases adapting the application in significant ways. Looking specifically into the database layer of the application, i.e. the aspect providing data persistence and manipulation capabilities, this involves dealing with differences in the granularity of interactions, refactoring of the application to cope with remote data sources, and addressing data confidentiality concerns. Toward this goal, in this work we present an application migration methodology which incorporates these aspects, and a decision support, application refactoring and data migration tool that assists application developers in realizing this methodology. For purposes of evaluating our proposal we present the results of a case study conducted in the context of an eScience project.

Cloud services allow for hosting applications partially or completely in the Cloud by migrating their components and data. Especially with respect to data migration, a series of functional and non-functional challenges like data confidentiality arise when considering private and public Cloud data stores. In this paper we identify some of these challenges and propose a set of reusable solutions focusing on the non-functional aspects, organized together as a set of Cloud Data Patterns.

Multi-tenancy is an essential property of Cloud computing. It helps service providers to maximize resource utilization and reduce servicing costs per customer. It is therefore important for key components of the contemporary enterprise environment like the Enterprise Service Bus (ESB) to support and enable multi-tenancy. For this purpose, in this work we investigate the requirements for multi-tenant ESB solutions, propose an implementation-agnostic ESB architecture that addresses these requirements, and discuss our proof-of-concept realization of this architecture.

Cloud computing allows reducing capital expenditure by using resources on demand. We investigate how to build a database layer in the Cloud and present pure and hybrid Cloud data hosting solutions. The solutions are organized in a taxonomy. The properties used for organization are: application layer, deployment model, location, service model, data store type, and compatibility. Using the taxonomy, existing Cloud data hosting solutions are categorized.

Governing business compliance with regulations, laws, best practices, contracts, and the like is not an easy task, and so far there are only limited software products available that help a company to express compliance rules and to analyze its compliance state. We argue that todaypsilas SOA-based way of implementing and conducting business (e.g., using Web services and business process engines) lends itself very well to the development of a comprehensive compliance government solution that effectively aids companies in being compliant. In this paper, we contextualize the compliance problem in SOA-based businesses, we highlight which are the most salient research challenges that need to be addressed, and we describe our approach to compliance governance, spanning design, execution, and evaluation concerns.