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Strategy and procedures for Migration to the Cloud Computing
Abstract
The cost of enterprise IT is growing due to the
nonlinear expansion of IT resource’s requirements. Cloud
computing, a new paradigm of flexible and cost-effective
computing is being explored as the possible solution to make
enterprise IT sustainable. Cloud computing also offers new
cutting edge cloud native-platform to develop application
composed of microservices. This paper investigates the strategies
and procedures for migration to the cloud computing
environment. Literature has been reviewed to illustrate upon the
current state of the art strategies and procedures for cloud
computing migration including tools provided by cloud service
providers and application vendors. The tasks of cloud migration
and procedures have been grouped into five phases and five
generic strategies for migration have been identified. Future
research directions have also been proposed in this area. The
findings will help to stimulate the research in this direction and
help cloud adopting organizations to analyze various issues and
options for making informed decision for the cloud migration.
... También, se reportan prácticas que tienen una estrecha relación con una cultura DevOps; Continuous integration (CI) Fan & Ma, 2017;Fritzsch et al., 2019;Hassan et al., 2020;Idoughi et al., 2017;Premchand & Choudhry, 2018;Sousa et al., 2020;Zhang et al., 2019), Continuous delivery (CD), Continuous deployment Fan & Ma, 2017;Fritzsch et al., 2019;O'Connor et al., 2016;Premchand & Choudhry, 2018;Zhang et al., 2019), al ejecutar estas actividades las organizaciones pueden lograr la integración de diversos microservicios, software listo para ser entregado al usuario y el despliegue automatizado del sistema. Después, el monitoring y logging es mencionado en diversos estudios (Ahmad et al., 2018;Di Francesco et al., 2018;Fan & Ma, 2017;Garriga, 2018;Hassan et al., 2020;Zhang et al., 2019), debido a que los microservicios se comunican por la red mediante sus APIs, deben de estar en constante monitoreo para asegurar su funcionamiento correcto. Finalmente, existen organizaciones que se apegan al paradigma de computación en la nube (Ahmad et al., 2018;Bogner et al., 2019;Di Francesco et al., 2018;Garriga, 2018;Soldani et al., 2018), entregando sus microservicios en contenedores a un proveedor de servicios y existen otras que reportan un grado de automatización únicamente en la etapa de despliegue (Buchgeher et al., 2017;Fan & Ma, 2017;Luz et al., 2018;Premchand & Choudhry, 2018 ...
... Después, el monitoring y logging es mencionado en diversos estudios (Ahmad et al., 2018;Di Francesco et al., 2018;Fan & Ma, 2017;Garriga, 2018;Hassan et al., 2020;Zhang et al., 2019), debido a que los microservicios se comunican por la red mediante sus APIs, deben de estar en constante monitoreo para asegurar su funcionamiento correcto. Finalmente, existen organizaciones que se apegan al paradigma de computación en la nube (Ahmad et al., 2018;Bogner et al., 2019;Di Francesco et al., 2018;Garriga, 2018;Soldani et al., 2018), entregando sus microservicios en contenedores a un proveedor de servicios y existen otras que reportan un grado de automatización únicamente en la etapa de despliegue (Buchgeher et al., 2017;Fan & Ma, 2017;Luz et al., 2018;Premchand & Choudhry, 2018 ...
... Dicho modelo descentralizado va de la mano con los equipos autónomos que pueden tomar sus propias decisiones y la heterogeneidad tecnológica . En segundo lugar, se reportan modelos alrededor de conceptos del negocio y que se comuniquen a través de APIs (Ahmad et al., 2018;Di Francesco et al., 2018;Garriga, 2018;Gundelsby, 2018;Premchand & Choudhry, 2018), esto permite que los equipos tengan la responsabilidad de un conjunto de componentes y puedan comunicarse con otro mediante una API. Siguiendo esta línea se puede observar que los modelos que fomentan la independencia de los procesos son los más reportados: despliegue independiente (Soldani et al., 2018), ciclo de vida independiente (Buchgeher et al., 2017;Idoughi et al., 2017;Kalske et al., 2018;Lotz et al., 2019;Soldani et al., 2018;Srikaew & Kim, 2017;Zhang et al., 2019). ...
Debido a la creciente adopción de la Arquitectura de Microservicios, estilo que hace énfasis en la división de los sistemas en una colección de pequeños servicios con una sola responsabilidad, existe una necesidad de construir este tipo de sistemas con calidad y de adaptar las prácticas de los equipos de desarrollo para alcanzar una mejor escalabilidad, mantenibilidad, facilidad de despliegue así como una mayor agilidad y una clara separación de intereses. Al igual que con otro tipo de sistemas, el desarrollo de microservicios trae consigo diferentes retos que las organizaciones deben enfrentar. Dichos retos no solo tienen que ver con la parte técnica, sino que también implica un cambio en las prácticas y organización de los equipos de desarrollo. El objetivo de este estudio es analizar las prácticas de desarrollo que llevan a cabo los equipos, la forma en que estos se organizan y los retos que enfrentan durante el desarrollo de microservicios. Siguiendo un proceso de mapeo sistemático de la literatura se recopilaron 26 estudios primarios los cuales fueron analizados mediante una síntesis temática. Los resultados muestran que los equipos tienden a ser pequeños y multifuncionales, las prácticas que realizan están relacionadas con una cultura ágil y de independencia, lo que se complementa con los modelos de gobernanza descentralizada y ciclo de vida independiente. Los retos se relacionan con la complejidad del dominio, aspectos específicos de la organización y las habilidades que los desarrolladores deben de tener. Como conclusión se obtuvo la importancia de las características de una organización y sus equipos de desarrollo, la estrecha relación que tiene una cultura DevOps con el desarrollo de microservicios, la independencia y descomposición son aspectos clave que deben tomarse en cuenta y se detectaron diversos retos donde el factor humano juega un papel importante.
... Cloud migration methodologies help plan, design, and implement migrations of chosen applications and workloads to the cloud [22] [35]. Cloud actors provide their processes and tools for the migration process, which involves moving an application or computational workload into a cloud environment [21] [38]. ...
... Cloud actors provide their processes operating their services and tools. Each of the four major cloud providers, Amazon [28], Google [32] [22], IBM [29], and Microsoft [30], published their migration process. ...
With the development of the cloud offers, we observe a prominent trend of applications being migrated from private infrastructure to the cloud. Depending on the application’s complexity, the migration can be complex and needs to consider several dimensions, such as dependency issues, service continuity, and the service level agreement (SLA). Amadeus, the travel industry leader, had partnered with Microsoft to migrate its IT ecosystem to the Azure cloud. This work addresses the specificity of cloud-to-cloud migration and the multi-cloud constraints. In this paper, we summarise the Amadeus Migration process. The process aims to drive the migration from an initial private cloud environment to a target environment that can be a public or hybrid cloud. Further, the process focuses on a prediction phase that guides the migration process. This paper expects to provide an efficient decision-making process that guides managers and architects to optimise and secure their migration process while considering micro-servicesoriented applications targeting an efficient deployment over multi-cloud or hybrid cloud. The prediction relies on the network simulation to predict applications’ behaviour in the cloud and evaluate different scenarios and deployment topologies beforehand. The objective is to predict migrated applications’ behaviour and identify any issue related to the performance, the application’s dependency on other components, or the deployment in the cloud. The migration process proposed in this paper relies on SimGrid, a toolkit developed by INRIA[52] for distributed application modelling. This framework offers a generic process to model IT infrastructure and can assist cloud-to-cloud migration. Specific attention is given to predictive and reactive optimisations. The first results show predictive optimisation's impact on securing KPI and reactive optimisation to optimise the solution cost. Thus, we reach an average cost reduction of 40% in comparaison with the same deployment strategy while keeping the same SLA.
... The authors of [34] categorized the migration risks into security-related and general migration risks. The authors of [35] proposed a theoretical framework for migration strategies ...
... It allows to migrate the existing off-cloud mobile learning solutions to the cloud and provide support for mobile learning. The technological maturity requirement will increase from SaaS and PaaS to IaaS mode [35]. Moreover, the important cloud computing features such as cloud-native, microservices and multi-agent systems are best utilized in SaaS or PaaS mode [108]. ...
Education plays a very significant role in the context of sustainability. As the world population is growing, providing education through the traditional classroom setting is not sufficient and not feasible to extend learning in professional life. Therefore, modern technology-mediated learning paradigms such as mobile learning are becoming increasingly popular. Mobile learning is said to integrate multiple contexts, learning types, mobilities and communications. As information and communications technology (ICT) plays a vital role in the delivery of mobile learning services, it is very essential to adopt sustainable IT resources to keep it viable. Cloud computing offers a range of affordable, scalable and on-demand solutions. This paper attempts to model important critical success factors (CSFs) in the area of cloud-based mobile learning using the interpretive structural modeling (ISM) technique. ISM helps in identifying the hierarchical inter-relationships between the variables of study with the help of experts in the field. Finally, Matrice d’Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) analysis is employed to classify the variables into dependent and independent variables. Management support has been identified as most rudimentary among sixteen CSFs identified through a literature review to establish a distinguished relative advantage. Further, the paper discusses the theoretical underpinning of all the constructs. This study will help organizations to implement mobile learning in sustainable ways.
... Hence, different migration scenarios can be required [28]: on-premise to cloud; cloud to cloud; cloud to on-premise; or on-premise to on-premise. CRM platform providers often offer migration as part of their services by providing an integration server with prebuilt connectors to common on-premise applications or cloud-based CRM solutions [1,28]. However, those standard processes may not completely fit into the needs of the specific organization [10]. ...
CRM platforms heavily depend on high-quality data, where poor-quality data can negatively influence its adoption. Additionally, these platforms are increasingly interconnected and complex to meet the growing needs of customers. Hence, delivery and consultancy of CRM platforms becomes highly complex. In this study, we propose a CRM data quality management framework that supports CRM delivery and consultancy firms to improve data quality management practices within their CRM projects. We develop the framework by extracting best practices for CRM data quality management by means of a literature study on data quality definition and measurement, data quality challenges, and data quality management methods. In a case study at an IT consultancy company, we investigate how CRM delivery and consultancy projects can benefit from the incorporation of data quality management practices. The results translate into a framework that provides a high-level overview of data quality management practices incorporated in CRM delivery and consultancy projects. It includes the following components: Client profiling, project definition, preparation, migration/integration, data quality definition, assessment, and improvement. The framework is validated by means of confirmatory focus groups and a questionnaire.
... Having a good strategy help in solving security concern by ensuring there is a recovery plan in place to be used in case of any breach, leakage, or termination of data. Strategic planning helps in identifying critical workloads that need to be prioritized [Ahm18a]. Therefore, a strategic plan helps in considering important information before migrating, for example, the amount of data to be migrated, storage needed, and the best service providers. ...
Cloud computing is the on-demand delivery of computing resources over the Internet. Cloud services present one of the most progressive and rapidly growing areas in the IT sector, with projections showing that the demand for cloud computing services will reach approximately 791.48 billion dollars by 2028. However, whilst the sector shows massive potential and ben- efits such as scalability, cost efficiency, easy accessibility, flexibility, and Increased productivity, there are extensive risks and threats associated with it. The increasing amount of confidential data stored in multi-cloud environments leaves organizations more exposed to attacks. This is of significant concern to businesses including organizations still considering a migration to cloud computing, thereby posing a consequential threat to cloud-enabled business transfor- mation. Depending on several factors and business requirements, organizations may choose between different cloud computing deployment or service models. The choice of models de- termines the scope of control between the cloud service providers (CSPs) and cloud consumers and ultimately defines the security responsibilities between the two. By means of a systematic literature review (SLR), this research identifies 18 threats including Data breaches, loss, and leakage, Infrastructure vulnerabilities, Identity and access management, Insecure interfaces and APIs, Insider threats, External attacks, Cloud misconfiguration, etc., as the top security concerns of cloud migration that affects business transformation. This is followed by an extensive study of these identified threats and a case study on eBay, a leading online marketplace. To mitigate these established security concerns, security measures such as examining baseline security, es- tablishing an adequate cloud security strategy, utilizing proper setups, and establishing proper logging and monitoring measures are some good practices to adopt during the process of cloud migration. Other cloud migration protocols to consider include establishing a strategic plan, a definition of the migration scope, and identifying milestones and KPIs.
... The central feature of all ERP systems is a shared database that supports multiple functions used by different business units. Today, traditional on-premises ERP systems are gradually being eclipsed by the growing demand for cloud-based ERP systems [5] due to their lower costs and faster deployment. In this migration to cloud technology, the impact of the pervasive digital transformation of businesses is a true challenge. ...
Current ERPs are still limited by cost, customization, implementation time, and interoperability with other systems. Even if cloud-based ERPs attempt to overcome these limits, they do not completely answer all of them. Based on that postulate about recent ERPs, a conceptual architecture, technical architecture, and implementation architecture of an Enterprise Operating System (EOS) have been designed and proposed to address the services and functionality needed by Enterprise 4.0. This conceptual architecture describes the essential functions required in the EOS, while the technical architecture shows how these tasks cooperate to achieve the mission of the EOS. Among some implementation architectures proposed that benefited from the innovation and concept of the EOS, GreneOS has proposed a technical architecture motivated by EOS concepts. The purpose of this paper is to discuss the current interest, complementarity, and limitation of both the EOS conceptual architecture and its implementation into GreneOS to propose perspectives for the future developments of the EOS.
... Another widely used classification is the R-Patterns, first published by Gartner in 2010 [13]. These have been adopted by some authors [21] and by companies such as AWS [4,25,2,3] or Microsoft [8]. The categories are mostly similar and have been extended over time. ...
The trend of adopting container-based systems become increasingly
relevant for companies and their IT departments. Improved scalability and shorter deployment cycles in IT production are the most mentioned benefits of the technology. The adoption of container-based technologies in an existing IT system landscape requires a consideration of migration strategies. The paper at hand examines general migration patterns for the transition of virtual systems into container-based systems from a cloud computing perspectives. Several strategies are derived for a specific use case.
... Ahmad et al. [21] presented the strategies and methods for transformation to the cloud computing environment from a client-server-based environment. Also, the authors evaluated the existing cloud migration processes and software available from existing cloud system integrators and operators. ...
The Coronavirus pandemic and the work-from-anywhere has created a shift toward cloud-based services. The pandemic is causing an explosion in cloud migration, expected that by 2025, 95% of workloads will live in the cloud. One of the challenges of the cloud is data security. It is the responsibility of cloud service providers to protect user data from unauthorized access. Historically, a third-party auditor (TPA) is used to provide security services over the cloud. With the tremendous growth of demand for cloud-based services, regulatory requirements, there is a need for a semi to fully automated self sovereign identity (SSI) implementation to reduce cost. It's critical to manage cloud data strategically and extend the required protection. At each stage of the data migration process, such as data discovery, classification, and cataloguing of the access to the mission-critical data, need to be secured. Cloud storage services are centralized, which requires users must place trust in a TPA. With the SSI, this can become decentralized, reducing the dependency and cost. Our current work involves replacing TPA with SSI. A cryptographic technique for secure data migration to and from the cloud using SSI implemented. SSI facilitate peer-to-peer transactions, meaning that the in-between presence of TPA needs no longer be involved. The C2C migration performance is recorded and found the background or foreground replication scenario is achievable. Mathematically computed encrypted and decrypted ASCII values for a word matched with the output by the algorithm. The keys generated by the algorithm are validated with an online validator to ensure the correctness of the generated keys. RSA based mutual TLS algorithm is a good option for SSI based C2C migration. SSI is beneficial because of the low maintenance cost, and users are more and more using a cloud platform. The result of the implemented algorithm shows that the SSI based implementation can provide a 13.32 Kbps encryption/decryption rate which is significantly higher than the TPA method of 1 Kbps.
... Ahmad et al. [21] presented the strategies and methods for transformation to the cloud computing environment from a client-server-based environment. Also, the authors evaluated the existing cloud migration processes and software available from existing cloud system integrators and operators. ...
The Coronavirus pandemic and the work-from-anywhere has created a shift toward cloud-based services. The pandemic is causing an explosion in cloud migration, expected that by 2025, 95% of workloads will live in the cloud. One of the challenges of the cloud is data security. It is the responsibility of cloud service providers to protect user data from unauthorized access. Historically, a third-party auditor (TPA) is used to provide security services over the cloud. With the tremendous growth of demand for cloud-based services, regulatory requirements, there is a need for a semi to fully automated self sovereign identity (SSI) implementation to reduce cost. It’s critical to manage cloud data strategically and extend the required protection. At each stage of the data migration process, such as data discovery, classification, and cataloguing of the access to the mission-critical data, need to be secured. Cloud storage services are centralized, which requires users must place trust in a TPA. With the SSI, this can become decentralized, reducing the dependency and cost. Our current work involves replacing TPA with SSI. A cryptographic technique for secure data migration to and from the cloud using SSI implemented. SSI facilitate peer-to-peer transactions, meaning that the in-between presence of TPA needs no longer be involved. The C2C migration performance is recorded and found the background or foreground replication scenario is achievable. Mathematically computed encrypted and decrypted ASCII values for a word matched with the output by the algorithm. The keys generated by the algorithm are validated with an online validator to ensure the correctness of the generated keys. RSA based mutual TLS algorithm is a good option for SSI based C2C migration. SSI is beneficial because of the low maintenance cost, and users are more and more using a cloud platform. The result of the implemented algorithm shows that the SSI based implementation can provide a 13.32 Kbps encryption/decryption rate which is significantly higher than the TPA method of 1 Kbps.
... The commonly used migration strategies are mainly applied in cloud migration projects: lift-and-shift, re-platforming, refactoring [20]. Lift-and-shift is the most straightforward and cheapest strategy. ...
... Migration: migration refers to moving organizations ICT infrastructure to the cloud infrastructure. Migration may follow on of the approach namely rehost, re-platform, re-factor or rebuild [69,70]. Similarly, migration policy, methodology and framework need to be developed well in advance before migration process execution. ...
Cloud computing is a matured platform to host the information and communication technology (ICT) infrastructure and services. All the top leading companies have made investments in cloud infrastructure including US Department of Defence's contract of USD 10 Billion to Microsoft for cloud migration. Cloud computing helps in conserving the resources and improving the performance of ICT services, hence making the computing more sustainable. Migration to cloud needs careful planning, strong business case, credible migration strategy and robust migration frameworks. This research has reviewed the area of cloud computing migration to identify important factors. The author keywords of 299 research articles downloaded from the web of science database have been analyzed using co-word analysis and resulted in 10 most significant factors in the form of cloud migration tuple. This study applies the interpretive structural modeling (ISM) technique to study the interrelationship on these factors. Application of ISM followed by Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analysis has categorized these factors into independent and dependent sets. The resultant model demonstrates that organizations need to incorporate the dimensions of service orientation, virtualization, multi utilization, dynamic allocation and mobile support into their data, application and security stacks. Migration of these stacks with sound strategy, policy and frameworks will lead to post-migration performance improvements in a synergistic fashion. The adoption of cloud migration tuple with understanding of interrelationships will help organizations make strategies and plan to migrate to cloud in an efficient manner.
... It favors small, stateless, siloed components with clean interfaces to maximize horizontal scalability and concurrent development while minimizing downtimes. The most commonly published works about cloud-native transformation of legacy workloads cover stateless applications [15][16][17][18][19][20][21][22][23]. Facebook developed Turbine, which is a cloud native platform for managing their streaming applications on their Tupperware container platform [24]. ...
We present the architecture of a cloud native version of IBM Streams, with Kubernetes as our target platform. Streams is a general purpose streaming system with its own platform for managing applications and the compute clusters that execute those applications. Cloud native Streams replaces that platform with Kubernetes. By using Kubernetes as its platform, Streams is able to offload job management, life cycle tracking, address translation, fault tolerance and scheduling. This offloading is possible because we define custom resources that natively integrate into Kubernetes, allowing Streams to use Kubernetes' eventing system as its own. We use four design patterns to implement our system: controllers, conductors, coordinators and causal chains. Composing controllers, conductors and coordinators allows us to build deterministic state machines out of an asynchronous distributed system. The resulting implementation eliminates 75% of the original platform code. Our experimental results show that the performance of Kubernetes is an adequate replacement in most cases, but it has problems with oversubscription, networking latency, garbage collection and pod recovery.
... Migration: As the global information technology resources have been deployed on the premises, they now need to be migrated to cloud. Types of migration are an important topic such as re-host, re-platform, re-factor, or rebuild [27,28]. Similarly, migration policy, methodology, and framework need to be developed well in advance before migration process execution. ...
Cloud computing has come a long way to become an established platform to host the ICT infrastructure. Almost all of the Fortune 500 companies have cloud presence. And the latest announcement of Pentagon to offer a contract worth USD 10 billion to migrate to cloud shows the confidence level in the cloud infrastructure. Migration to cloud needs careful planning, strong business case, credible migration strategy, and robust migration frameworks. This paper reviews the area of cloud computing migration frameworks. It utilizes the co-word analysis technique of bibliometric or science mapping. The keywords of 299 research articles downloaded from the Web of science database have been analyzed. A 10 elements cloud migration tuple has been developed. Additionally, this paper gives cloud computing technology trends that have evolved to address the challenges of latency and jitter, context awareness, Internet of Things, voluminous data, and mobility support. The results of this paper will help in understanding the cloud computing and migration thereof.
The state of cloud security is evolving. Many organizations are migrating their on-premises data centers to cloud networks at a rapid pace due to the benefits like cost-effectiveness, scalability, reliability, and flexibility. Yet, cloud environments also raise certain security concerns that may hinder their adoption. Cloud security threats may include data breaches/leaks, data loss, access management, insecure APIs, and misconfigured cloud storage. The security challenges associated with cloud computing have been widely studied in previous literature and different research groups. This paper conducted a systematic literature review and examined the research studies published between 2010 and 2023 within popular digital libraries. The paper then proposes a comprehensive Secure Cloud Migration Strategy (SCMS) that organizations can adopt to secure their cloud environment. The proposed SCMS consists of three main repeatable phases/processes, which are preparation; readiness and adoption; and testing. Among these phases, the author addresses tasks/projects from the different perspectives of the three cybersecurity teams, which are the blue team (defenders), the red team (attackers), and the yellow team (developers). This can be used by the Cloud Center of Excellence (CCoE) as a checklist that covers defending the cloud; attacking and abusing the cloud; and applying the security shift left concepts. In addition to that, the paper addresses the necessary cloud security documents/runbooks that should be developed and automated such as incident response runbook, disaster recovery planning, risk assessment methodology, and cloud security controls. Future research venues and open cloud security problems/issues were addressed throughout the paper. The ultimate goal is to support the development of a proper security system to an efficient cloud computing system to help harden organizations’ cloud infrastructures and increase the cloud security awareness level, which is significant to national security. Furthermore, practitioners and researchers can use the proposed solutions to replicate and/or extend the proposed work.
Abstract: The state of cloud security is evolving. Many organizations are migrating their on-premises data centers to cloud networks at a rapid pace due to the benefits like cost-effectiveness, scalability, reliability, and flexibility. Yet, cloud environments also raise certain security concerns that may hinder their adoption. Cloud security threats may include data breaches/leaks, data loss, access management, insecure APIs, and misconfigured cloud storage. The security challenges associated with cloud computing have been widely studied in previous literature and different research groups. This paper conducted a systematic literature review and examined the research studies published between 2010 and 2023 within popular digital libraries. The paper then proposes a comprehensive Secure Cloud Migration Strategy (SCMS) that organizations can adopt to secure their cloud environment. The proposed SCMS consists of three main repeatable phases/processes, which are preparation; readiness and adoption; and testing. Among these phases, the author addresses tasks/projects from the different perspectives of the three cybersecurity teams, which are the blue team (defenders), the red team (attackers), and the yellow team (developers). This can be used by the Cloud Center of Excellence (CCoE) as a checklist that covers defending the cloud; attacking and abusing the cloud; and applying the security shift left concepts. In addition to that, the paper addresses the necessary cloud security documents/runbooks that should be developed and automated such as incident response runbook, disaster recovery planning, risk assessment methodology, and cloud security controls. Future research venues and open cloud security problems/issues were addressed throughout the paper. The ultimate goal is to support the development of a proper security system to an efficient cloud computing system to help harden organizations’ cloud infrastructures and increase the cloud security awareness level, which is significant to national security. Furthermore, practitioners and researchers can use the proposed solutions to replicate and/or extend the proposed work.
As IT infrastructure is increasingly rehosted to public clouds, IT system development must become more efficient. Traditionally, configuring and provisioning cloud services to meet the same requirements as on-premises systems is a time-consuming manual process that is prone to human error. Therefore, we define a cloud feature model based on rehosting requirements and propose an automatic provisioning method for cloud environments in which engineers select model elements from the same design perspective as on-premises cases. We evaluated our method’s effectiveness in two projects for rehosting to an AWS environment. The results show that our method reduced man-hours by 20% in the design process and by 60% in the construction process compared with the conventional method. In the design process, our method eliminated the trial-and-error consideration of cloud services. In the construction process, our method helped introduce Infrastructure as Code, and the automatic matching function immediately increased productivity after provisioning. Therefore, our method improved efficiency in IT system development associated with rehosting.
This is a survey article that explores six Cloud-based deployment archetypes for Cloud applications and the tradeoffs between them to achieve high availability, low end-user latency, and acceptable costs. These are (1) Zonal, (2) Regional, (3) Multi-regional, (4) Global, (5) Hybrid, and (6) Multi-cloud deployment archetypes. The goal is to classify cloud applications into a set of deployment archetypes and deployment models that tradeoff their needs around availability, latency, and geographical constraints with a focus on serving applications. This enables application owners to better examine the tradeoffs of each deployment model and what is needed for achieving the availability and latency goals for their application.
Abstract Texture is a term used to characterize the surface of objects and region and
represents main features in pattern recognition and image processing. The concept
of image or object, and is defined as a function of the brightness’s spatial fluctuation
intensity of pixel or shape, analysis of texturemay be classified into four distinct categories
(structural, statistical, transform, and a model-based approach). The purpose
of feature extraction is to convert an image to a matrix vector and to create a unique
representation of signal values. The term “feature extraction” refers to the process of
extracting features from an image without the use of any processing procedure. This
article presents the main texture strategies extracted such as co-occurrence matrix,
gradient, contrast, DCT, DWT, fractal, and PCA are used for analysis image skin
tumors and compare, combine these strategies to reach a high diagnostic accuracy
by computational complexity to reduce the challenge example (rotation, noise, etc.)
to become familiarwith themany sorts of features that may be utilized in DIA (digital
image analysis) for future researchers are provided.
Keywords Image processing · Feature extraction · Texture analysis · Skin cancer
Abstract Texture is a term used to characterize the surface of objects and region and
represents main features in pattern recognition and image processing. The concept
of image or object, and is defined as a function of the brightness’s spatial fluctuation
intensity of pixel or shape, analysis of texturemay be classified into four distinct categories
(structural, statistical, transform, and a model-based approach). The purpose
of feature extraction is to convert an image to a matrix vector and to create a unique
representation of signal values. The term “feature extraction” refers to the process of
extracting features from an image without the use of any processing procedure. This
article presents the main texture strategies extracted such as co-occurrence matrix,
gradient, contrast, DCT, DWT, fractal, and PCA are used for analysis image skin
tumors and compare, combine these strategies to reach a high diagnostic accuracy
by computational complexity to reduce the challenge example (rotation, noise, etc.)
to become familiarwith themany sorts of features that may be utilized in DIA (digital
image analysis) for future researchers are provided.
The most common cause of death among patients with cardiovascular diseases is myocardial infarction (MI). Identifying predictors for in-hospital mortality is an essential step toward MI prevention and consequent reduction in mortality. We aimed to develop machine learning (ML) methods for predicting in-hospital mortality in MI patients and apply novel techniques for models’ interpretability to detect the predictive importance of the variables. Random forest (RF) and extreme gradient boosting (XGB) are applied to a dataset of 2035 MI patients who underwent percutaneous coronary intervention. When comparing the models’ AUC (RF—0.9712 vs. XGB—0.9666) and accuracy (RF—97% versus XGB—98%), both techniques achieved similar performance. However, the RF model obtained a higher sensitivity (86%) than the XGBoost classifier (80%). Hypertension, cardiogenic shock, ejection fraction were identified as some of the main contributors to the outcome. Our paper contributes to the global effort of reducing mortality in patients with myocardial infarction by proposing two interpretable ML models that accurately predict in-hospital mortality in MI patients. These results are essential steps in improving current preventive strategies. However, future studies on larger datasets enriched with both categorical and continuous variables, and models validated on external data from other centers are needed to accurately assume generalizability in clinical practice.
It is common sense that cloud-native applications (CNA) are intentionally designed for the cloud. Although this understanding can be broadly used it does not guide and explain what a cloud-native application exactly is. The term "cloud-native" was used quite frequently in birthday times of cloud computing (2006) which seems somehow obvious nowadays. But the term disappeared almost completely. Suddenly and in the last years the term is used again more and more frequently and shows increasing momentum. This paper summarizes the outcomes of a systematic mapping study analyzing research papers covering "cloud-native" topics, research questions and engineering methodologies. We summarize research focuses and trends dealing with cloud-native application engineering approaches. Furthermore, we provide a definition for the term "cloud-native application" which takes all findings, insights of analyzed publications and already existing and well-defined terminology into account.
Many organizations migrate on-premise software applications to the cloud. However, current coarse-grained cloud migration solutions have made such migrations a non transparent task, an endeavour based on trial-and-error. This paper presents V-PAM (Variability-based, Pattern-driven Architecture Migration), a migration method based on (i) a catalogue of fine-grained service-based cloud architecture migration patterns that target multi-cloud, (ii) a situational migration process framework to guide pattern selection and composition, and (iii) a variability model to structure system migration into a coherent framework. The proposed migration patterns are based on empirical evidence from several migration projects, best practice for cloud architectures and a systematic literature review of existing research. V-PAM allows an organization to (i) select appropriate migration patterns, (ii) compose them to define a migration plan, and (iii) extend them based on the identification of new patterns in new contexts. The patterns are at the core of our solution, embedded into a process model, with their selection governed by a variability model.
While cloud computing has certainly gained attention, the potential for increased uptake of the technology is still large. As a consequence, how to move and migrate to the cloud is an unanswered question for many organisations. Gaining an understanding of cloud migration processes from on-premise architectures is our aim here. For this purpose, we look at three provider-driven case studies based on the common three layers of cloud computing: Infrastructure (IaaS), platform (PaaS) and software (SaaS) as a service. These shall be complemented by a fourth, independent systems integration perspective. We extract common migration process activities for the layer-specific processes and discuss commonalities, differences and open issues. The results presented are based on expert interviews and focus groups held with major international cloud solution providers and independent consultants.
Background--By leveraging cloud services, organizations can deploy their software systems over a pool of resources. However, organizations heavily depend on their business-critical systems, which have been developed over long periods. These legacy applications are usually deployed on-premise. In recent years, research in cloud migration has been carried out. However, there is no secondary study to consolidate this research. Objective--This paper aims to identify, taxonomically classify, and systematically compare existing research on cloud migration. Method--We conducted a systematic literature review (SLR) of 23 selected studies, published from 2010 to 2013. We classified and compared the selected studies based on a characterization framework that we also introduce in this paper. Results--The research synthesis results in a knowledge base of current solutions for legacy-to-cloud migration. This review also identifies research gaps and directions for future research. Conclusion--This review reveals that cloud migration research is still in early stages of maturity, but is advancing. It identifies the needs for a migration framework to help improving the maturity level and consequently trust into cloud migration. This review shows a lack of tool support to automate migration tasks. This study also identifies needs for architectural adaptation and self-adaptive cloud-enabled systems.
Cloud computing is an emerging computing paradigm whose benefits (such as high scalability, reduced IT costs, self-service on demand, and pay-as-you-go price models) have increasingly attracted the interest of the corporate world. Nevertheless, many organizations have found it difficult to adopt cloud-based solutions, particularly regarding the migration of their existing legacy applications to this new environment. One of the main obstacles faced by those organizations is the lack of a general process to help application developers not only in selecting the cloud models and services best suited for their application, but also in carefully assessing the various risks and benefits involved. To fill this gap, this paper presents Cloudstep, a step-by-step decision process aimed at supporting legacy application migration to the cloud. The process relies on the creation of template-based profiles characterizing the organization, the target legacy application and candidate cloud providers, which are then cross-analyzed to help identify and possibly resolve critical constraints (either technical or non technical) that may hinder migration to the cloud. The use of the process is illustrated through an analysis of key factors influencing the migration of a commercial medical application to different infrastructure-as-a-service cloud providers.
This case study illustrates the potential benefits and risks associated with the migration of an IT system in the oil & gas industry from an in-house data center to Amazon EC2 from a broad variety of stakeholder perspectives across the enterprise, thus transcending the typical, yet narrow, financial and technical analysis offered by providers. Our results show that the system infrastructure in the case study would have cost 37% less over 5 years on EC2, and using cloud computing could have potentially eliminated 21% of the support calls for this system. These findings seem significant enough to call for a migration of the system to the cloud but our stakeholder impact analysis revealed that there are significant risks associated with this. Whilst the benefits of using the cloud are attractive, we argue that it is important that enterprise decision-makers consider the overall organizational implications of the changes brought about with cloud computing to avoid implementing local optimizations at the cost of organization-wide performance. Comment: Submitted to IEEE CLOUD 2010
This book offers a comprehensive guide to implementing SAP and HANA on private, public and hybrid clouds. Cloud computing has transformed the way organizations run their IT infrastructures: the shift from legacy monolithic mainframes and UNIX platforms to cloud based infrastructures offering ubiquitous access to critical information, elastic provisioning and drastic cost savings has made cloud an essential part of every organization’s business strategy. Cloud based services have evolved from simple file sharing, email and messaging utilities in the past, to the current situation, where their improved technical capabilities and SLAs make running mission-critical applications such as SAP possible. However, IT professionals must take due care when deploying SAP in a public, private, or hybrid cloud environment. As a foundation for core business operations, SAP cloud deployments must satisfy stringent requirements concerning their performance, scale and security, while delivering measurable improvements in IT efficiency and cost savings.
The 2nd edition of “SAP on the Cloud” continues the work of its successful predecessor released in 2013, providing updated guidance for deploying SAP in public, private and hybrid clouds. To do so, it discusses the technical requirements and considerations necessary for IT professionals to successfully implement SAP software in a cloud environment, including best-practice architectures for IaaS, PaaS, and SaaS deployments. The section on SAP’s in-memory database HANA has been significantly extended to cover Suite on HANA (SoH) and the different incarnations of HANA Enterprise Cloud (HEC) and Tailored Datacenter Integration (TDI). As cyber threats are a significant concern, it also explores appropriate security models for defending SAP cloud deployments against modern and sophisticated attacks. The reader will gain the insights needed to understand the respective benefits and drawbacks of various deployment models, and how SAP on the cloud can be used to deliver IT efficiency and cost-savings in a secure and agile manner.
Purpose
– This paper aims to revisit the adoption reasons of enterprise systems (ES) and supply chain management systems (SCMS) and to explore the new dimensions of sustainability required to be added in the whole process of adoption of these systems. Moreover, it aims to explore the benefits of ES to organizations and to relate these benefits to the ES adoption in future sustainable city settings. Future cities will have micro-industries requiring dynamic interactions and will be dependent on efficient supply chains. The recent developments in information and communications technology (ICT) such as cloud computing through its dynamic, on-demand and service-based delivery are making it possible to achieve those goals for supply chains. The ES in general and more specifically SCMS have integrated organizations into one seamless mesh.
Design/methodology/approach
– This paper presents a framework for adoption of sustainable ES in a smart city setting. The framework, firstly, is presented at a macro-level, particularly incorporating the relative significance of motivational factors for sustainable ES adoption. Subsequently, The authors study the benefits of ES as perceived by large and small and medium enterprise (SME) organizations using 100 case studies and discuss how these benefits can be realized for smart cities by projecting the ES benefits onto the proposed framework. The benefits are estimated with the Shang and Seddon’s (2002) framework.
Findings
– The adoption of ES initiated with environmental factors and mediated with business and technical factors will bring benefits in all the dimensions of triple bottom line in addition to the firm’s performance. ES will have pivotal role in future smart city settings and will be able to offer social, environmental and economic sustainability in addition to traditional organizational performance indicators.
Originality/value
– The proposed framework for ES adoption will bring ES packages (particularly, the required relative significance of adoption reasons) into the perspective of sustainable development. Moreover, the study of its benefits in relation to the proposed sustainable ES adoption framework presented in this paper will help in motivating organizations to incorporate social, economic and environmental sustainability into their core business objectives.
This issue's "Cloud Tidbit" focuses on container technology and how it's emerging as an important part of the cloud computing infrastructure. It looks at Docker, an open source project that automates the faster deployment of Linux applications, and Kubernetes, an open source cluster manager for Docker containers.
Legacy system migration to the cloud brings both great challenges and benefits, so there exist various academic research and industrial applications on legacy system migration to the cloud. By analyzing the research achievements and application status, we divide the existing migration methods into three strategies according to the cloud service models integrally. Different processes need to be considered for different migration strategies, and different tasks will be involved accordingly. The similarities and differences between the migration strategies are discussed, and the challenges and future work about legacy system migration to the cloud are proposed. The aim of this paper is to provide an overall presentation for legacy system migration to the cloud and identify important challenges and future research directions.
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