Toward Customizable Multi-tenant SaaS Applications

abstract: Nowadays, Computing is so pervasive that it has become indeed the 5th utility (after water, electricity, gas, telephony) as Leonard Kleinrock once envisioned. Evolved from utility computing, cloud computing has emerged as a computing infrastructure that enables rapid delivery of computing resources as a utility in a dynamically scalable, virtualized manner. However, the current industrial cloud computing implementations promote segregation among different cloud providers, which leads to user lockdown because of prohibitive migration cost. On the other hand, Service-Orented Computing (SOC) including service-oriented architecture (SOA) and Web Services (WS) promote standardization and openness with its enabling standards and communication protocols. This thesis proposes a Service-Oriented Cloud Computing Architecture by combining the best attributes of the two paradigms to promote an open, interoperable environment for cloud computing development. Mutil-tenancy SaaS applicantions built on top of SOCCA have more flexibility and are not locked down by a certain platform. Tenants residing on a multi-tenant application appear to be the sole owner of the application and not aware of the existence of others. A multi-tenant SaaS application accommodates each tenant’s unique requirements by allowing tenant-level customization. A complex SaaS application that supports hundreds, even thousands of tenants could have hundreds of customization points with each of them providing multiple options, and this could result in a huge number of ways to customize the application. This dissertation also proposes innovative customization approaches, which studies similar tenants’ customization choices and each individual users behaviors, then provides guided semi-automated customization process for the future tenants. A semi-automated customization process could enable tenants to quickly implement the customization that best suits their business needs.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Tenant-centric Sub-Tenancy Architecture in Software-as-a-Service

AbstractMulti-tenancy architecture (MTA) is often used in Software-as-a-Service (SaaS) and the central idea is that multiple tenant applications can be developed using components stored in the SaaS infrastructure. Recently, MTA has been extended to allow a tenant application to have its own sub-tenants, where the tenant application acts like a SaaS infrastructure. In other words, MTA is extended to STA (Sub-Tenancy Architecture). In STA, each tenant application needs not only to develop its own functionalities, but also to prepare an infrastructure to allow its sub-tenants to develop customized applications. This paper applies Crowdsourcing as the core to STA component in the development life cycle. In addition, to discovering adequate fit tenant developers or components to help build and compose new components, dynamic and static ranking models are proposed. Furthermore, rank computation architecture is presented to deal with the case when the number of tenants and components becomes huge. Finally, experiments are performed to demonstrate that the ranking models and the rank computation architecture work as design

Cloud enterprise resource planning development model based on software factory approach

Literature reviews revealed that Cloud Enterprise Resource Planning (Cloud ERP) is significantly growing, yet from software developers’ perspective, it has succumbed to high management complexity, high workload, inconsistency software quality, and knowledge retention problems. Previous researches lack a solution that holistically addresses all the research problem components. Software factory approach was chosen to be adapted along with relevant theories to develop a model referred to as Cloud ERP Factory Model (CEF Model), which intends to pave the way in solving the above-mentioned problems. There are three specific objectives, those are (i) to develop the model by identifying the components with its elements and compile them into the CEF Model, (ii) to verify the model’s deployment technical feasibility, and (iii) to validate the model field usability in a real Cloud ERP production case studies. The research employed Design Science methodology, with a mixed method evaluation approach. The developed CEF Model consists of five components; those are Product Lines, Platform, Workflow, Product Control, and Knowledge Management, which can be used to setup a CEF environment that simulates a process-oriented software production environment with capacity and resource planning features. The model was validated through expert reviews and the finalized model was verified to be technically feasible by a successful deployment into a selected commercial Cloud ERP production facility. Three Cloud ERP commercial deployment case studies were conducted using the prototype environment. Using the survey instruments developed, the results yielded a Likert score mean of 6.3 out of 7 thus reaffirming that the model is usable and the research has met its objective in addressing the problem components. The models along with its deployment verification processes are the main research contributions. Both items can also be used by software industry practitioners and academician as references in developing a robust Cloud ERP production facility

Big SaaS: The Next Step Beyond Big Data

Software-as-a-Service (SaaS) is a model of cloud computing in which software functions are delivered to the users as services. The past few years have witnessed its global flourishing. In the foreseeable future, SaaS applications will integrate with the Internet of Things, Mobile Computing, Big Data, Wireless Sensor Networks, and many other computing and communication technologies to deliver customizable intelligent services to a vast population. This will give rise to an era of what we call Big SaaS systems of unprecedented complexity and scale. They will have huge numbers of tenants/users interrelated in complex ways. The code will be complex too and require Big Data but provide great value to the customer. With these benefits come great societal risks, however, and there are other drawbacks and challenges. For example, it is difficult to ensure the quality of data and metadata obtained from crowdsourcing and to maintain the integrity of conceptual model. Big SaaS applications will also need to evolve continuously. This paper will discuss how to address these challenges at all stages of the software lifecycle

Business process model customisation using domain-driven controlled variability management and rule generation

Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

Business process model customisation using domain-driven controlled variability management and rule generation

Business process models are abstract descriptions and as such should be applicable in different situations. In order for a single process model to be reused, we need support for configuration and customisation. Often, process objects and activities are domain-specific. We use this observation and allow domain models to drive the customisation. Process variability models, known from product line modelling and manufacturing, can control this customisation by taking into account the domain models. While activities and objects have already been studied, we investigate here the constraints that govern a process execution. In order to integrate these constraints into a process model, we use a rule-based constraints language for a workflow and process model. A modelling framework will be presented as a development approach for customised rules through a feature model. Our use case is content processing, represented by an abstract ontology-based domain model in the framework and implemented by a customisation engine. The key contribution is a conceptual definition of a domain-specific rule variability language

Product management in software as a service

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 69-71).Software product management within Software as a Service is key domain of interest given the recent advances in Cloud Computing. This thesis explores the product management challenges within this domain. It makes a contribution to understanding how factors such as architecture, customer experience measurement, customer driven feature prioritization, editorial action of product manager and development process affect product success in the SaaS domain. SaaS product management dictates different priorities from traditional software and product managers and organizations must adapt to these changes to innovate.by Karthikeyan Rajasekharan.S.M

When to Utilize Software as a Service

Cloud computing enables on-demand network access to shared resources (e.g., computation, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort. Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers. Software as a service (SaaS) is part of cloud computing. It is one of the cloud service models. SaaS is software deployed as a hosted service and accessed over the Internet. In SaaS, the consumer uses the provider‘s applications running in the cloud. SaaS separates the possession and ownership of software from its use. The applications can be accessed from any device through a thin client interface. A typical SaaS application is used with a web browser based on monthly pricing. In this thesis, the characteristics of cloud computing and SaaS are presented. Also, a few implementation platforms for SaaS are discussed. Then, four different SaaS implementation cases and one transformation case are deliberated. The pros and cons of SaaS are studied. This is done based on literature references and analysis of the SaaS implementations and the transformation case. The analysis is done both from the customer‘s and service provider‘s point of view. In addition, the pros and cons of on-premises software are listed. The purpose of this thesis is to find when SaaS should be utilized and when it is better to choose a traditional on-premises software. The qualities of SaaS bring many benefits both for the customer as well as the provider. A customer should utilize SaaS when it provides cost savings, ease, and scalability over on-premises software. SaaS is reasonable when the customer does not need tailoring, but he only needs a simple, general-purpose service, and the application supports customer‘s core business. A provider should utilize SaaS when it offers cost savings, scalability, faster development, and wider customer base over on-premises software. It is wise to choose SaaS when the application is cheap, aimed at mass market, needs frequent updating, needs high performance computing, needs storing large amounts of data, or there is some other direct value from the cloud infrastructure.Siirretty Doriast