Split and Migrate: Resource-Driven Placement and Discovery of Microservices at the Edge

Microservices architectures combine the use of fine-grained and independently-scalable services with lightweight communication protocols, such as REST calls over HTTP. Microservices bring flexibility to the development and deployment of application back-ends in the cloud. Applications such as collaborative editing tools require frequent interactions between the front-end running on users\u27 machines and a back-end formed of multiple microservices. User-perceived latencies depend on their connection to microservices, but also on the interaction patterns between these services and their databases. Placing services at the edge of the network, closer to the users, is necessary to reduce user-perceived latencies. It is however difficult to decide on the placement of complete stateful microservices at one specific core or edge location without trading between a latency reduction for some users and a latency increase for the others. We present how to dynamically deploy microservices on a combination of core and edge resources to systematically reduce user-perceived latencies. Our approach enables the split of stateful microservices, and the placement of the resulting splits on appropriate core and edge sites. Koala, a decentralized and resource-driven service discovery middleware, enables REST calls to reach and use the appropriate split, with only minimal changes to a legacy microservices application. Locality awareness using network coordinates further enables to automatically migrate services split and follow the location of the users. We confirm the effectiveness of our approach with a full prototype and an application to ShareLatex, a microservices-based collaborative editing application

Migrating a Large Scale Legacy Application to SOA: Challenges and Lessons Learned

Abstract—This paper presents the findings of a case study of a large scale legacy to service-oriented architecture migration process in the payments domain of a Dutch bank. The paper presents the business drivers that initiated the migration, and describes a 4-phase migration process. For each phase, the paper details benefits of using the techniques, best practices that contribute to the success, and possible challenges that are faced during migration. Based on these observations, the findings are discussed as lessons learned, including the implications of using reverse engineering techniques to facilitate the migration process, adopting a pragmatic migration realization approach, emphasizing the organizational and business perspectives, and harvesting knowledge of the system throughout the system’s life cycle. I

Towards Process Support for Migrating Applications to Cloud Computing

Cloud computing is an active area of research for industry and academia. There are a large number of organizations providing cloud computing infrastructure and services. In order to utilize these infrastructure resources and services, existing applications need to be migrated to clouds. However, a successful migration effort needs well-defined process support. It does not only help to identify and address challenges associated with migration but also provides a strategy to evaluate different platforms in relation to application and domain specific requirements. This paper present a process framework for supporting migration to cloud computing based on our experiences from migrating an Open Source System (OSS), Hackystat, to two different cloud computing platforms. We explained the process by performing a comparative analysis of our efforts to migrate Hackystate to Amazon Web Services and Google App Engine. We also report the potential challenges, suitable solutions, and lesson learned to support the presented process framework. We expect that the reported experiences can serve guidelines for those who intend to migrate software applications to cloud computing.Muhammad Aufeef Chauhan, Muhammad Ali Baba

Factors Affecting Success in Migration of Legacy Systems to Service-Oriented Architecture (SOA) - Shared Experiences from Five Case Companies

Background: The term ‘legacy systems’ refers to existing Information Systems that have been deployed in the past and have been running critical business processes within an enterprise in its current IT architecture. Based on their important role, legacy systems are considered the heart of a company’s operating enterprise system and therefore are of significant business value to the company. Therefore IT architects have not neglected the value these existing assets can bring to the adoption of service-oriented architecture and have been studying different methods and factors to migrate the legacy investments into the new architecture and take advantage of their business value. However, not in all cases has the process of migrating legacy systems into SOA been successful. In fact, the level of success in adapting the legacy systems in a company with the new service-oriented architecture is dependant on some factors which vary from one legacy infrastructure and series of business processes to another. There is no quick fix to transforming the existing legacy assets which highlights the fact that considering the right factors to reach legacy system migration success in a specific company is of key value. Therefore, we hereby studied the factors influencing success of migrating these legacy investments into SOA in five different companies which include a Large European Bank, SAS, a Large globally-known Company in Sweden, Sandvik AB and a large UK Bank. Purpose: To identify factors affecting successful migration of legacy systems into SOA in five companies. Method: The main adopted research method in this study has been interviews for different case studies. Through separate interviews, critical success factors of migrating legacy systems into SOA have been collected and identified in each case. Finally collected results are analyzed and presented as the recognized factors affecting successful migration of legacy assets into SOA in five different enterprises with their own Information System infrastructures. Conclusion: The success factors identified include potential of legacy systems for being migrated, strategy of migration, SOA governance, the business process of the company, budgeting and resources, legacy architecture, close monitoring, dependence on commercial products, information architecture, testing and technical skills of the personnel. Out of all these factors, only three factors have been applied and mentioned by all the case companies in this study, which are the potential of legacy systems for being migrated into SOA, strategy of migration and SOA Governance