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Active storage
(2018)
In brief, Active Storage refers to an architectural hardware and software paradigm, based on collocation storage and compute units. Ideally, it will allow to execute application-defined data ... within the physical data storage. Thus Active Storage seeks to minimize expensive data movement, improving performance, scalability, and resource efficiency. The effective use of Active Storage mandates new architectures, algorithms, interfaces, and development toolchains.
While the recently emerged microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high costs and effort of a refactoring process which has several other implications, e.g. overall processes (DevOps) and team structure. Software architects facing this challenge are in need of selecting an appropriate strategy and refactoring technique. One of the most discussed aspects in this context is finding the right service granularity to fully leverage the advantages of a microservices architecture. This study first discusses the notion of architectural refactoring and subsequently compares 10 existing refactoring approaches recently proposed in academic literature. The approaches are classified by the underlying decomposition technique and visually presented in the form of a decision guide for quick reference. The review yielded a variety of strategies to break down a monolithic application into independent services. With one exception, most approaches are only applicable under certain conditions. Further concerns are the significant amount of input data some approaches require as well as limited or prototypical tool support.
A transaction is a demarcated sequence of application operations, for which the following properties are guaranteed by the underlying transaction processing system (TPS): atomicity, consistency, isolation, and durability (ACID). Transactions are therefore a general abstraction, provided by TPS that simplifies application development by relieving transactional applications from the burden of concurrency and failure handling. Apart from the ACID properties, a TPS must guarantee high and robust performance (high transactional throughput and low response times), high reliability (no data loss, ability to recover last consistent state, fault tolerance), and high availability (infrequent outages, short recovery times).
The architectures and workhorse algorithms of a high-performance TPS are built around the properties of the underlying hardware. The introduction of nonvolatile memories (NVM) as novel storage technology opens an entire new problem space, with the need to revise aspects such as the virtual memory hierarchy, storage management and data placement, access paths, and indexing. NVM are also referred to as storage-class memory (SCM).
Digital transformation has changed corporate reality and, with that, firms’ IT environments and IT governance (ITG). As such, the perspective of ITG has shifted from the design of a relatively stable, closed and controllable system of a self-sufficient enterprise to a relatively fluid, open, agile and transformational system of networked co adaptive entities. Related to this paradigm shift in ITG, this paper aims to clarify how the concept of an effective ITG framework has changed in terms of the demand for agility in organizations. Thus, this study conducted 33 qualitative interviews with executives and senior managers from the banking industry in Germany, Switzerland and Austria. Analysis of the interviews focused on the formation of categories and the assignment of individual text parts (codings) to these categories to allow for a quantitative evaluation of the codings per category. Regarding traditional and agile ITG dimensions, 22 traditional and 25 agile dimensions were identified. Moreover, agile strategies within the agile ITG construct and ten ITG patterns were identified from the interview data. The data show relevant perspectives on the implementation of traditional and new ITG dimensions and highlight ambidextrous aspects in ITG frameworks.