Size Estimation of Cloud Migration Projects with Cloud Migration Point (CMP)

Tran, Van Tuan; Lee, Kevin; Fekete, Alan; Liu, Anna; Keung, Jacky

doi:10.1109/esem.2011.35

Cited by 14 publications

(8 citation statements)

References 22 publications

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“…In contrast to this work, the study uses software metrics to calculate the estimated migration costs in man hours rather than making migration efforts explicit. Tran et al [27] define a metric, called cloud migration point (CMP), for effort estimation of cloud migrations derived from function points. Compared to our metrics, CMP estimates migration effort in an early phase of the development cycle, whereas we are evaluating factual changes after the implementation phase.…”

Section: Related Workmentioning

confidence: 99%

Application Migration Effort in the Cloud - The Case of Cloud Platforms

Kolb

Lenhard

Wirtz

2015

2015 IEEE 8th International Conference on Cloud Computing

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Over the last years, the utilization of cloud resources has been steadily rising and an increasing number of enterprises are moving applications to the cloud. A leading trend is the adoption of Platform as a Service to support rapid application deployment. By providing a managed environment, cloud platforms take away a lot of complex configuration effort required to build scalable applications. However, application migrations to and between clouds cost development effort and open up new risks of vendor lock-in. This is problematic because frequent migrations may be necessary in the dynamic and fast changing cloud market. So far, the effort of application migration in PaaS environments and typical issues experienced in this task are hardly understood. To improve this situation, we present a cloud-to-cloud migration of a real-world application to seven representative cloud platforms. In this case study, we analyze the feasibility of the migrations in terms of portability and the effort of the migrations. We present a Docker-based deployment system that provides the ability of isolated and reproducible measurements of deployments to platform vendors, thus enabling the comparison of platforms for a particular application. Using this system, the study identifies key problems during migrations and quantifies these differences by distinctive metrics. RQ 1: Is it possible to move a real-world application between different cloud platforms? RQ 2: What is the development effort involved in porting a cloud-native application between cloud platforms?The use case application, Blinkist, is a Ruby on Rails web application developed by Blinks Labs GmbH. The set of selected PaaS vendors includes IBM Bluemix, cloudControl, AWS Elastic Beanstalk, EngineYard, Heroku, OpenShift, and Pivotal Web Services. We analyze the feasibility of the migration in terms of portability and the effort for this task. Besides, we present a Docker-based deployment system that provides the ability of isolated and reproducible measurements of deployments to platform vendors, thus enabling the comparison of platforms for a particular application. Using this system, the study identifies key problems during migrations and quantifies these differences by distinctive metrics. In this study, we target implementation portability [3], [10] of the migration execution, i.e., the application transformation and the deployment. We focus on functional portability of the application. Data portability must be investigated separately, especially since popular NoSQL technologies impose substantial lock-in problems. With our results, we are able to compare migration effort between different cloud platforms and to identify existing portability problems.The remainder of the paper is structured as follows. In Section II, we describe our research methodology including 1 See the twelve-factor methodology at http://12factor.net.

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Section: Related Workmentioning

confidence: 99%

Application Migration Effort in the Cloud - The Case of Cloud Platforms

Kolb

Lenhard

Wirtz

2015

2015 IEEE 8th International Conference on Cloud Computing

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“…With our proposal of a step-by-step methodology, we provide detailed guidance and recommendation on both data migration and required application refactoring in order to minimise this overhead. Tran et al (2011) adapted the function point method in order to estimate the costs of cloud migration projects and classified the applications potentially migrated to the cloud. As our assumption is that the decision to migrate to the cloud has already been taken we do not consider aspects like costs.…”

Section: Related Workmentioning

confidence: 99%

Migrating enterprise applications to the cloud: methodology and evaluation

Strauch

Andrikopoulos

Karastoyanova

et al. 2014

IJBDI

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Migrating existing on-premise applications to the cloud is a complex and multi-dimensional task and may require adapting the applications themselves significantly. For example, when considering the migration of the database layer of an application, which provides data persistence and manipulation capabilities, it is necessary to address aspects like differences in the granularity of interactions and data confidentiality, and to enable the interaction of the application with remote data sources. In this work, we present a methodology for application migration to the cloud that takes these aspects into account. In addition, we also introduce a tool for decision support, application refactoring and data migration that assists application developers in realising this methodology. We evaluate the proposed methodology and enabling tool using a case study in collaboration with an IT enterprise.

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“…A promising solution to this challenge is to replace the cost with other steady factors for evaluation. For example, we may estimate the size of Cloud migration projects instead of directly evaluating the migration cost [38]. • There is still a lack of effective metrics for evaluating Cloud elasticity.…”

Section: Rq 4: What Metrics Have Been Used For Evaluation Of Commercimentioning

confidence: 99%

On evaluating commercial Cloud services: A systematic review

Zhang

O’Brien

et al. 2013

Journal of Systems and Software

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Background: Cloud Computing is increasingly booming in industry with many competing providers and services. Accordingly, evaluation of commercial Cloud services is necessary. However, the existing evaluation studies are relatively chaotic. There exists tremendous confusion and gap between practices and theory about Cloud services evaluation. Aim: To facilitate relieving the aforementioned chaos, this work aims to synthesize the existing evaluation implementations to outline the state-of-the-practice and also identify research opportunities in Cloud services evaluation. Method: Based on a conceptual evaluation model comprising six steps, the Systematic Literature Review (SLR) method was employed to collect relevant evidence to investigate the Cloud services evaluation step by step. Results: This SLR identified 82 relevant evaluation studies. The overall data collected from these studies essentially represent the current practical landscape of implementing Cloud services evaluation, and in turn can be reused to facilitate future evaluation work. Conclusions: Evaluation of commercial Cloud services has become a world-wide research topic. Some of the findings of this SLR identify several research gaps in the area of Cloud services evaluation (e.g., the Elasticity and Security evaluation of commercial Cloud services could be a long-term challenge), while some other findings suggest the trend of applying commercial Cloud services (e.g., compared with PaaS, IaaS seems more suitable for customers and is particularly important in industry). This SLR study itself also confirms some previous experiences and reveals new Evidence-Based Software Engineering (EBSE) lessons.

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Size Estimation of Cloud Migration Projects with Cloud Migration Point (CMP)

Cited by 14 publications

References 22 publications

Application Migration Effort in the Cloud - The Case of Cloud Platforms

Application Migration Effort in the Cloud - The Case of Cloud Platforms

Migrating enterprise applications to the cloud: methodology and evaluation

On evaluating commercial Cloud services: A systematic review

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