Stefan Walraven

A middleware layer for flexible and cost-efficient multi-tenant applications

Application-level multi-tenancy is an architectural design principle for Software-as-a-Service applications to enable the hosting of multiple customers (or tenants) by a single application instance. Despite the operational cost and maintenance benefits of application-level multi-tenancy, the current middleware component models for multi-tenant application design are inflexible with respect to providing different software variations to different customers. In this paper we show that this limitation can be solved by a multi-tenancy support layer that combines dependency injection with middleware support for tenant data isolation. Dependency injection enables injecting different software variations on a per tenant basis, while dedicated middleware support facilitates the separation of data and configuration metadata between tenants. We implemented a prototype on top of Google App Engine and we evaluated by means of a case study that the improved flexibility of our approach has little impact on operational costs and upfront application engineering costs.

Efficient customization of multi-tenant Software-as-a-Service applications with service lines

Application-level multi-tenancy is an architectural approach for Software-as-a-Service (SaaS) applications which enables high operational cost efficiency by sharing one application instance among multiple customer organizations (the so-called tenants). However, the focus on increased resource sharing typically results in a one-size-fits-all approach. In principle, the shared application instance satisfies only the requirements common to all tenants, without supporting potentially different and varying requirements of these tenants. As a consequence, multi-tenant SaaS applications are inherently limited in terms of flexibility and variability. This paper presents an integrated service engineering method, called service line engineering, that supports co-existing tenant-specific configurations and that facilitates the development and management of customizable, multi-tenant SaaS applications, without compromising scalability. Specifically, the method spans the design, implementation, configuration, composition, operations and maintenance of a SaaS application that bundles all variations that are based on a common core. We validate this work by illustrating the benefits of our method in the development of a real-world SaaS offering for document processing. We explicitly show that the effort to configure and compose an application variant for each individual tenant is significantly reduced, though at the expense of a higher initial development effort.

Comparing PaaS offerings in light of SaaS development

Software vendors increasingly aim to apply the Software-as-a-Service (SaaS) delivery model instead of the traditional on-premise model. Platforms-as-a-Service (PaaS), such as Google App Engine and Windows Azure, deliver a computing platform and solution stack as a service, but they also aim to facilitate the development of cloud applications (SaaS). Such PaaS offerings should enable third parties to build and deliver multi-tenant SaaS applications while shielding the complexity of the underpinning middleware and infrastructure. This paper compares, on the basis of a practical case study, three different and representative PaaS platforms with respect to their support for SaaS application development. We have reengineered an on-premise enterprise application into a SaaS application and we have subsequently deployed it in three PaaS-based cloud environments. We have investigated the following qualities of the PaaS platforms from the perspective of SaaS development: portability of the application code base, available support for creating and managing multi-tenant-aware applications, and quality of the tool support.

Towards performance isolation in multi-tenant SaaS applications

Multi-tenancy has shown promising results in achieving high operational cost efficiency by sharing hardware and software resources among multiple customer organisations, called tenants. In the context of cloud computing, this paradigm enables cloud providers to reduce operational costs by dividing resources and to simplify application management and maintenance. Maximum cost efficiency is achieved with application-level multi-tenancy. However, this high level of resource sharing complicates performance isolation between the different tenants, i.e. ensuring compliance with the SLAs of the different tenants and ensuring that the behaviour of one tenant cannot adversely affect the performance of the other tenants. This paper explores the challenges of performance isolation in the context of multi-tenant SaaS applications. In addition, we propose a middleware architecture to enforce performance isolation based on the tenant-specific SLAs, using a tenant-aware profiler and a scheduler. Our prototype reveals promising initial results.

Context-oriented programming for customizable SaaS applications

Software-as-a-Service (SaaS) applications are multi-tenant software applications that are delivered as highly configurable web services to individual customers, which are called tenants in this context. For reasons of complexity management and to lower maintenance cost, SaaS providers maintain and deploy a single version of the application code for all tenants. As a result, however, custom-made extensions for individual tenants cannot be efficiently integrated and managed. In this paper we show that by using a context-oriented programming model, cross-tier tenant-specific software variations can be easily integrated into the single-version application code base. Moreover, the selection of which variations to execute can be configured on a per tenant basis. Concretely, we provide a technical case study based on Google App Engine (GAE), a cloud platform for building multi-tenant web applications. We contribute by showing: (a) how ContextJ, a context-oriented programming (COP) language, can be used with GAE, (b) the increase in flexibility and customizability of tenant-specific software variations using ContextJ as compared to Googles dependency injection framework Guice, and (c) that the performance of using ContextJ is comparable to Guice. Based on these observations, we come to the conclusion that COP can be helpful for providing software variations in SaaS.

Towards Portability and Interoperability Support in Middleware for Hybrid Clouds

The cloud computing paradigm promises increased flexibility and scalability for consumers and providers of software services. Service providers that exploit private cloud environments offer restricted flexibility and scalability because of the limited capacity. However, such organizations are often reluctant to migrate to public clouds because of business continuity threats and vendor lock-in. Hybrid clouds potentially combine the benefits of private and public (external) clouds. Vendor lock-in can be avoided when multiple external clouds are supported and effectively exploited. This paper presents a middleware platform for hybrid cloud applications. The middleware enables organizations to control the execution of their applications in hybrid cloud environments. Driven by policies, the middleware can dynamically decide which requests and tasks are executed on a particular part of the hybrid cloud. The core of the middleware, and the focus of this paper, is an abstraction layer. The abstraction layer enables portability over multiple services including data storage, blob storage, and asynchronous task execution of various PaaS platforms as well as interoperability between the PaaS platforms. We have validated the core concept by building a prototype implementation that runs on top of specific PaaS platforms as well as on a cloud-enabling middleware. A document processing SaaS application has been instantiated on the middleware. Performance results have been collected for JBoss AS cluster, Google App Engine, and Red Hat OpenShift.

Developing and managing customizable Software as a Service using feature model conversion

In recent years, there has been a growing interest in cloud technologies. Using current cloud solutions, it is however difficult to create customizable multi-tenant applications, especially if the application must support varying Quality of Service (QoS) guarantees. Software Product Line Engineering (SPLE) and feature modeling techniques are commonly used to address these issues in non-cloud applications, but these techniques cannot be ported directly to a cloud context, as the common approaches are geared towards customization of on-premise deployed applications, and do not support multi-tenancy. In this paper, we propose an architecture for the development and management of customizable Software as a Service (SaaS) applications, built using SPLE techniques. In our approach, each application is a composition of services, where individual services correspond to specific application functionalities, referred to as features. A feature-based methodology is described to abstract and convert the application information required at different stages of the application life-cycle: development, customization and deployment. We specifically focus on how development feature models can be adapted ensuring a one-to-one correspondence between features and services exists, ensuring the composition of services yields an application containing the corresponding features. These runtime features can then be managed using feature placement techniques. The proposed approach enables developers to define significantly less features, while limiting the amount of automatically generated features in the application runtime stage. Conversion times between models are shown to be in the order of milliseconds, while execution times of management algorithms are shown to improve by 5 to 17% depending on the application case.

Feature placement algorithms for high-variability applications in cloud environments

While the use of cloud computing is on the rise, many obstacles to its adoption remain. One of the weaknesses of current cloud offerings is the difficulty of developing highly customizable applications while retaining the increased scalability and lower cost offered by the multi-tenant nature of cloud applications. In this paper we describe a Software Product Line Engineering (SPLE) approach to the modelling and deployment of customizable Software as a Service (SaaS) applications. Afterwards we define a formal feature placement problem to manage these applications, and compare several heuristic approaches to solve the problem. The scalability and performance of the algorithms is investigated in detail. Our experiments show that the heuristics scale and perform well for systems with a reasonable load.

Building a Customizable Business-Process-as-a-Service Application with Current State-of-Practice

Application-level multi-tenancy is an increasingly prominent architectural pattern in Software-as-a-Service (SaaS) applications that enables multiple tenants (customers) to share common application functionality and resources among each other. This has the disadvantage that multi-tenant applications are often limited in terms of customizability: one application should fit the needs of all customers.

Variability middleware for multi-tenant SaaS applications: a research roadmap for service lines

Software product line engineering (SPLE) and variability enforcement techniques have been applied to run-time adaptive systems for quite some years, also in the context of multi-tenant Software-as-a-Service (SaaS) applications. The focus has been mainly on (1) the pre-deployment phases of the development life cycle and (2) fine-grained (tenant-level), run-time activation of specific variants. However, with upcoming trends such as DevOps and continuous delivery and deployment, operational aspects become increasingly important. In this paper, we present our integrated vision on the positive interplay between SPLE and adaptive middleware for multi-tenant SaaS applications, focusing on the operational aspects of running and maintaining a successful SaaS offering. This vision, called Service Lines, is based on and motivated by our experience and frequent interactions with a number of Belgian SaaS providers. We concretely highlight and motivate a number of operational use cases that require advanced variability support in middleware and have promising added value for the economic feasibility of SaaS offerings. In addition, we provide a gap analysis of what is currently lacking from the perspectives of variability modeling and management techniques and middleware support, and as such sketch a concrete roadmap for continued research in this area.