Cloud Computing Adoption: An Effective Tailoring Approach

Many organisations are currently moving their legacy systems to the cloud as it offers on-demand, elastic, and pay-as-you-go service models. However, different cloud migration scenarios can involve different activities during the migration process using one of many existing migration methods to make legacy cloud-compliant. There is no universally superior or applicable method for all cloud migration scenarios. In situations like this, designing situation-specific methods that fit several existing migration scenarios would be beneficial to the industry. The literature review reveals that issues surrounding the method tailoring for the cloud migration have not been addressed yet. To effectively harness this shortcoming, the idea of situational method engineering approach is applied to develop a framework for designing and maintaining bespoke methods for moving legacies to the cloud. The paper demonstrates the applicability of the framework via presenting two scenarios of creating, configuring, and sharing situational methods

Adaptive management of applications across multiple clouds:the SeaClouds approach

How to deploy and manage, in an efficient and adaptive way, complex applications across multiple heterogeneous cloud platforms is one of the problems that have emerged with the cloud revolution. In this paper we present context, motivations and objectives of the EU research project SeaClouds, which aims at enabling a seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and migration of application modules over multiple heterogeneous cloud platforms. After positioning SeaClouds with respect to related cloud initiatives, we present the SeaClouds architecture and discuss some of its aspect, such as the use of the OASIS standard TOSCA and the compatibility with the OASIS CAMP initiative

A look at cloud architecture interoperability through standards

Enabling cloud infrastructures to evolve into a transparent platform while preserving integrity raises interoperability issues. How components are connected needs to be addressed. Interoperability requires standard data models and communication encoding technologies compatible with the existing Internet infrastructure. To reduce vendor lock-in situations, cloud computing must implement universal strategies regarding standards, interoperability and portability. Open standards are of critical importance and need to be embedded into interoperability solutions. Interoperability is determined at the data level as well as the service level. Corresponding modelling standards and integration solutions shall be analysed

Evaluating Cloud Migration Options for Relational Databases

Migrating the database layer remains a key challenge when moving a software system to a new cloud provider. The database is often very large, poorly documented, and used to store business-critical information. Most cloud providers offer a variety of services for hosting databases and the most suitable choice depends on the database size, workload, performance requirements, cost, and future business plans. Current approaches do not support this decision-making process, leading to errors and inaccurate comparisons between database migration options. The heterogeneity of databases and clouds means organisations often have to develop their own ad-hoc process to compare the suitability of cloud services for their system. This is time consuming, error prone, and costly. This thesis contributes to addressing these issues by introducing a three-phase methodology for evaluating cloud database migration options. The first phase defines the planning activities, such as, considering downtime tolerance, existing infrastructure, and information sources. The second phase is a novel method for modelling the structure and the workload of the database being migrated. This addresses database heterogeneity by using a multi-dialect SQL grammar and annotated text-to-model transformations. The final phase consumes the models from the second and uses discrete-event simulation to predict migration cost, data transfer duration, and cloud running costs. This involved the extension of the existing CloudSim framework to simulate the data transfer to a new cloud database. An extensive evaluation was performed to assess the effectiveness of each phase of the methodology and of the tools developed to automate their main steps. The modelling phase was applied to 15 real-world systems, and compared to the leading approach there was a substantial improvement in: performance, model completeness, extensibility, and SQL support. The complete methodology was applied to four migrations of two real-world systems. The results from this showed that the methodology provided significantly improved accuracy over existing approaches

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja

Interoperabilnost uslužnog računarstva pomoću aplikacijskih programskih sučelja

Cloud computing paradigm is accepted by an increasing number of organizations due to significant financial savings. On the other hand, there are some issues that hinder cloud adoption. One of the most important problems is the vendor lock-in and lack of interoperability as its outcome. The ability to move data and application from one cloud offer to another and to use resources of multiple clouds is very important for cloud consumers.The focus of this dissertation is on the interoperability of commercial providers of platform as a service. This cloud model was chosen due to many incompatibilities among vendors and lack of the existing solutions. The main aim of the dissertation is to identify and address interoperability issues of platform as a service. Automated data migration between different providers of platform as a service is also an objective of this study.The dissertation has the following main contributions: first, the detailed ontology of resources and remote API operations of providers of platform as a service was developed. This ontology was used to semantically annotate web services that connect to providers remote APIs and define mappings between PaaS providers. A tool that uses defined semantic web services and AI planning technique to detect and try to resolve found interoperability problems was developed. The automated migration of data between providers of platform as a service is presented. Finally, a methodology for the detection of platform interoperability problems was proposed and evaluated in use cases.Zbog mogućnosti financijskih ušteda, sve veći broj poslovnih organizacija razmatra korištenje ili već koristi uslužno računarstvo. Međutim, postoje i problemi koji otežavaju primjenu ove nove paradigme. Jedan od najznačajnih problema je zaključavanje korisnika od strane pružatelja usluge i nedostatak interoperabilnosti. Za korisnike je jako važna mogućnost migracije podataka i aplikacija s jednog oblaka na drugi, te korištenje resursa od više pružatelja usluga.Fokus ove disertacije je interoperabilnost komercijalnih pružatelja platforme kao usluge. Ovaj model uslužnog računarstva je odabran zbog nekompatibilnosti različitih pružatelja usluge i nepostojanja postojećih rješenja. Glavni cilj disertacije je identifikacija i rješavanje problema interoperabilnosti platforme kao usluge. Automatizirana migracija podataka između različitih pružatelja platforme kao usluge je također jedan od ciljeva ovog istraživanja.Znanstveni doprinos ove disertacije je sljedeći: Najprije je razvijena detaljna ontologija resursa i operacija iz aplikacijskih programskih sučelja pružatelja platforme kao usluge. Spomenuta ontologija se koristi za semantičko označavanje web servisa koji pozivaju udaljene operacije aplikacijskih programskih sučelja pružatelja usluga, a sama ontologija definira i mapiranja između pružatelja platforme kao usluge. Također je razvijen alat koji otkriva i pokušava riješiti probleme interoperabilnosti korištenjem semantičkih web servisa i tehnika AI planiranja. Prikazana je i arhitektura za automatiziranu migraciju podataka između različitih pružatelja platforme kao usluge. Na kraju je predložena metodologija za otkrivanje problema interoperabilnosti koja je evaluirana pomoću slučajeva korištenja

A decision framework to mitigate vendor lock-in risks in cloud (SaaS category) migration.

Cloud computing offers an innovative business model to enterprise IT services consumption and delivery. However, vendor lock-in is recognised as being a major barrier to the adoption of cloud computing, due to lack of standardisation. So far, current solutions and efforts tackling the vendor lock-in problem have been confined to/or are predominantly technology-oriented. Limited studies exist to analyse and highlight the complexity of vendor lock-in problem existing in the cloud environment. Consequently, customers are unaware of proprietary standards which inhibit interoperability and portability of applications when taking services from vendors. The complexity of the service offerings makes it imperative for businesses to use a clear and well understood decision process to procure, migrate and/or discontinue cloud services. To date, the expertise and technological solutions to simplify such transition and facilitate good decision making to avoid lock-in risks in the cloud are limited. Besides, little research investigations have been carried out to provide a cloud migration decision framework to assist enterprises to avoid lock-in risks when implementing cloud-based Software-as-a-Service (SaaS) solutions within existing environments. Such decision framework is important to reduce complexity and variations in implementation patterns on the cloud provider side, while at the same time minimizing potential switching cost for enterprises by resolving integration issues with existing IT infrastructures. Thus, the purpose of this thesis is to propose a decision framework to mitigate vendor lock-in risks in cloud (SaaS) migration. The framework follows a systematic literature review and analysis to present research findings containing factual and objective information, and business requirements for vendor-neutral interoperable cloud services, and/or when making architectural decisions for secure cloud migration and integration. The underlying research procedure for this thesis investigation consists of a survey based on qualitative and quantitative approaches conducted to identify the main risk factors that give rise to cloud computing lock-in situations. Epistemologically, the research design consists of two distinct phases. In phase 1, qualitative data were collected using open-ended interviews with IT practitioners to explore the business-related issues of vendor lock-in affecting cloud adoption. Whereas the goal of phase 2 was to identify and evaluate the risks and opportunities of lock-in which affect stakeholders’ decision-making about migrating to cloud-based solutions. In synthesis, the survey analysis and the framework proposed by this research (through its step-by-step approach), provides guidance on how enterprises can avoid being locked to individual cloud service providers. This reduces the risk of dependency on a cloud provider for service provision, especially if data portability, as the most fundamental aspect, is not enabled. Moreover, it also ensures appropriate pre-planning and due diligence so that the correct cloud service provider(s) with the most acceptable risks to vendor lock-in is chosen, and that the impact on the business is properly understood (upfront), managed (iteratively), and controlled (periodically). Each decision step within the framework prepares the way for the subsequent step, which supports a company to gather the correct information to make a right decision before proceeding to the next step. The reason for such an approach is to support an organisation with its planning and adaptation of the services to suit the business requirements and objectives. Furthermore, several strategies are proposed on how to avoid and mitigate lock-in risks when migrating to cloud computing. The strategies relate to contract, selection of vendors that support standardised formats and protocols regarding data structures and APIs, negotiating cloud service agreements (SLA) accordingly as well as developing awareness of commonalities and dependencies among cloud-based solutions. The implementation of proposed strategies and supporting framework has a great potential to reduce the risks of vendor lock-in

Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

Many SaaS providers nowadays want to leverage the cloud's capabilities also for their existing applications, for example, to enable sound scalability and cost-effectiveness. This thesis provides the approach CloudMIG that supports SaaS providers to migrate those applications to IaaS and PaaS-based cloud environments. CloudMIG consists of a step-by-step process and focuses on two core components. (1) Restrictions imposed by specific cloud environments (so-called cloud environment constraints (CECs)), such as a limited file system access or forbidden method calls, can be validated by an automatic conformance checking approach. (2) A cloud deployment option (CDO) determines which cloud environment, cloud resource types, deployment architecture, and runtime reconfiguration rules for exploiting a cloud's elasticity should be used. The implied performance and costs can differ in orders of magnitude. CDOs can be automatically optimized with the help of our simulation-based genetic algorithm CDOXplorer. Extensive lab experiments and an experiment in an industrial context show CloudMIG's applicability and the excellent performance of its two core components