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.

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Cloud Migration Research: A Systematic Review

A system is disclosed that includes components and features for enabling enterprise users to securely access enterprise resources (documents, data, application servers, etc.) using their mobile devices. An enterprise can use some or all components of the system to, for example, securely but flexibly implement a BYOD (bring your own device) policy in which users can run both personal applications and secure enterprise applications on their mobile devices. The system may, for example, implement policies for controlling mobile device accesses to enterprise resources based on device attributes (e.g., what mobile applications are installed), user attributes (e.g., the user's position or department), behavioral attributes, and other criteria. Client-side code installed on the mobile devices may further enhance security by, for example, creating a secure container for locally storing enterprise data, creating a secure execution environment for running enterprise applications, and/or creating secure application tunnels for communicating with the enterprise system.

Secure execution of enterprise applications on mobile devices

A system configured to facilitate brokering hybrid cloud services selects information requests for characterizing an information technology application. The system responses to the information requests and determines a plurality of sets of the responses each used for deriving a value of a respective one of a plurality of factor functions. The system determines a plurality of assessment results each derived using values for of a respective set of the factor functions. Each one of the assessment results characterizes a respective aspect of deploying the information technology application within a cloud environment.

Assessment of best fit cloud deployment infrastructures

This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to model their applications, data and infrastructure requirements in addition to their computational resource usage patterns. The tool can be used to compare the cost of different cloud providers, deployment options and usage scenarios. The second tool is a spreadsheet that outlines the benefits and risks of using IaaS clouds from an enterprise perspective, this tool provides a starting point for risk assessment. Two case studies were used to evaluate the tools. The tools were useful as they informed decision makers about the costs, benefits and risks of using the cloud.

Decision Support Tools for Cloud Migration in the Enterprise

Various aspects of the disclosure relate to providing secure containers or data vaults for data of one or more managed applications. In some embodiments, each managed application may be assigned its own private data vault and/or may be assigned a shared data vault that is accessible to at least one other managed application. As the managed application executes, calls for access to the data may be intercepted and redirected to the secure containers. Data stored in a secure container may be encrypted according to a policy. Other aspects relate to deleting data from a secure container, such as via a selective wipe of data associated with a managed application. Further aspects relate to configuring and creating the secure containers, retrieving key information required to encrypt/decrypt the data stored in the secure containers, and publishing the managed applications, policy information and key information for download to a mobile device.

Controlling mobile device access to secure data

The present invention describes a method and system for preparing a migration and consolidation of at least one source application to be migrated to or consolidated in at least one heterogeneous server device. A computing system selects at least one prospective target platform component based on an evaluation of at least one source platform component, a requirement of the at least one source application, and a compatibility and an affinity of the at least one prospective target platform component. The computing system collects first metadata of the at least one source platform component and the at least one prospective target platform component. The computing system collects second metadata associated with the migration and consolidation. The computing system groups the first metadata and the second metadata into a RFM (Request For Migration). The computing system prepares and configures a final target platform in accordance with the RFM.

Assisting server migration

Disclosed is a computer-implemented method, system and computer program(s) for migration of a source machine instance to a target machine instance of least one heterogeneous virtual server device managed within a cloud computing environment. The method includes discovering machine images of a cloud service provider and storing results in a computer-readable catalog containing cloud metadata comprised of machine image identifiers and information discovered about the machine images. The method further includes, in response to a request for migration document in a computer-readable form that comprises a specification of a required migration target machine instance, specifying weight/priority information for components to be included in the target machine instance, where the weight information indicates weights for operations comprising component installation, component removal and component upgrade in the target machine instance. The method also includes executing a best fit matching algorithm to examine the catalog in accordance with the weight/priority information to identify optimal machine images to be used for the migration of the source machine instance to the target machine instance.

Method, System and Computer Programs to Assist Migration to a Cloud Computing Environment

The steady drumbeat of Cloud as a disruptive influence for Infrastructure Service Providers (ISP’s) and the enablement vehicle for Software As A Service (SAAS)providers can be heard loud and clear in the industry today. In fact, Cloud is probably at the peak of the hype curve, and already there are identified challenges associated with effective deployment for business critical applications (so called Production Applications) in mature enterprises. One of these challenges is the smooth migration of workload from the previous environment to the new cloud enabled environment in a cost effective way, with minimal disruption and risk. In this paper we introduce extensions to an integrated automation capability called the Darwin framework that enables workload migration for this scenario and discuss the impact that automated migration has on the cost and risks normally associated with migration to clouds.

Workload Migration into Clouds Challenges, Experiences, Opportunities

Customers of Cloud Services are expected to choose specific machine images to instantiate in order to host their workloads. Unfortunately very little information is provided to the users to enable them to make intelligent choices. We believe that as the number of images proliferates it will become increasingly difficult for users to decide effectively. Cloud service providers often allow their customers to instantiate standard system images, to modify their instances, and to store images of these customized instances for public or private future use. Storing modified instances as images enables customers to avoid re-provisioning and re-configuration of required resources thereby reducing their future costs. However Cloud service providers generally do not expose details regarding the configurations of the images in a rigorous canonical fashion nor offer services that assist clients in the best target image selection to support client transformation objectives. Rather, they allow customers to enter a free-form description of an image based on client's best effort. This means in order to find a “best fit” image to instantiate, a human user must review potentially thousands of image descriptions, reading each description to evaluate its suitability as a platform to host their source application. Furthermore, the actual content of the selected image may differ greatly from its description. Finally, even images that have been customized and retained for future use may need additional provisioning and customization to accommodate specific needs. In this paper we propose a service that accumulates image configuration details in a canonical fashion and a further service that employs an algorithm to order images per best fit /least cost in conformance to user-specified policies. These services collectively facilitate workload transformation into enterprise cloud environments.

Karen Cheng

Papers

Assisting server migration

Method, System and Computer Programs to Assist Migration to a Cloud Computing Environment

Workload Migration into Clouds Challenges, Experiences, Opportunities

Image selection as a service for cloud computing environments