A Model-Driven Architecture Approach to the Efficient Identification of Services on Service-oriented Enterprise Architecture

Service-Oriented Enterprise Architecture requires the efficient development of loosely-coupled and interoperable sets of services. Existing design approaches do not always take full advantage of the value and importance of the engineering invested in existing legacy systems. This paper proposes an approach to define the key services from such legacy systems effectively. The approach focuses on identifying these services based on a Model-Driven Architecture approach supported by guidelines over a wide range of possible service types

Management Challenges for DevOps Adoption within UK SMEs

The DevOps phenomenon is gathering pace as more UK organisations seek to leverage the benefits it can potentially bring to software engineering functions. However substantial organisational change is inherent to adopting DevOps, especially where there are prior and established methods. As part of a wider piece of doctoral research investigating the management challenges of DevOps adoption, we present early findings of a six month qualitative diary study following the adoption of DevOps within a UK based SME with over 200 employees. We find that within our case study organisation, the DevOps approach is being adopted for the development of a new system used both internally and by customers. DevOps, conceptually, appears to be generally well regarded, but in reality is proving difficult to fully adopt. This difficulty is down to a combination of necessity in maintaining a legacy system, lack of senior management buy-in, managerial structure and resistance. Additionally, we are finding evidence of job crafting, especially with the software developers. Taken together, we put forward the argument that DevOps is an interdisciplinary topic which would greatly benefit from further management and potentially psychology oriented research attention

HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges

High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources---steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR