The Design Of Cloud Workflow Systems
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The Design of Cloud Workflow Systems
Author: Xiao Liu
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-11-02
Cloud computing is the latest market-oriented computing paradigm which brings software design and development into a new era characterized by “XaaS”, i.e. everything as a service. Cloud workflows, as typical software applications in the cloud, are composed of a set of partially ordered cloud software services to achieve specific goals. However, due to the low QoS (quality of service) nature of the cloud environment, the design of workflow systems in the cloud becomes a challenging issue for the delivery of high quality cloud workflow applications. To address such an issue, this book presents a systematic investigation to the three critical aspects for the design of a cloud workflow system, viz. system architecture, system functionality and quality of service. Specifically, the system architecture for a cloud workflow system is designed based on the general four-layer cloud architecture, viz. application layer, platform layer, unified resources layer and fabric layer. The system functionality for a cloud workflow system is designed based on the general workflow reference model but with significant extensions to accommodate software services in the cloud. The support of QoS is critical for the quality of cloud workflow applications. This book presents a generic framework to facilitate a unified design and development process for software components that deliver lifecycle support for different QoS requirements. While the general QoS requirements for cloud workflow applications can have many dimensions, this book mainly focuses on three of the most important ones, viz. performance, reliability and security. In this book, the architecture, functionality and QoS management of our SwinDeW-C prototype cloud workflow system are demonstrated in detail as a case study to evaluate our generic design for cloud workflow systems. To conclude, this book offers a general overview of cloud workflow systems and provides comprehensive introductions to the design of the system architecture, system functionality and QoS management.
Workflows for e-Science
Author: Ian J. Taylor
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-12-31
This collection of articles on ‘Work?ows for e-Science’ is very timely and - portant. Increasingly, to attack the next generation of scienti?c problems, multidisciplinary and distributed teams of scientists need to collaborate to make progress on these new ‘Grand Challenges’. Scientists now need to access and exploit computational resources and databases that are geographically distributed through theuseof high speed networks. ‘Virtual Organizations’ or ‘VOs’ must be established that span multiple administrative domains and/or institutions and which can provide appropriate authentication and author- ation services and access controls to collaborating members. Some of these VOsmayonlyhavea?eetingexistencebutthelifetimeofothersmayrun into many years. The Grid community is attempting to develop both sta- ards and middleware to enable both scientists and industry to build such VOs routinely and robustly. This, of course, has been the goal of research in distributed computing for many years; but now these technologies come with a new twist service orie- ation. By specifying resources in terms of a service description, rather than allowing direct access to the resources, the IT industry believes that such an approach results in the construction of more robust distributed systems. The industry has therefore united around web services as the standard technology toimplementsuchserviceorientedarchitecturesandtoensureinteroperability between di?erent vendor systems.
Luigi Workflow Systems in Data Engineering
"Luigi Workflow Systems in Data Engineering" "Luigi Workflow Systems in Data Engineering" offers a comprehensive exploration of Luigi as a cornerstone for modern data pipeline orchestration. Beginning with the evolution of workflow management in data engineering, the book presents a nuanced discussion of the critical challenges posed by today’s complex, large-scale data systems and the necessity for robust orchestration. It sets Luigi within a diverse landscape of workflow systems, contrasting legacy architectures with current, maintainable solutions, and guiding readers through contemporary trends such as declarative pipeline definitions. The heart of the text delves deeply into Luigi’s architectural foundations, task modeling, and extensibility features. Readers gain in-depth knowledge of Luigi’s approach to dependency management, configuration, environment isolation, and security, all framed through practical design patterns and real-world implementation strategies. The book details how to develop, test, and maintain scalable and resilient pipelines, with a strong focus on reliability, modularity, auditability, and best practices for handling failures, complex dependencies, and parameter management. Moving beyond the fundamentals, "Luigi Workflow Systems in Data Engineering" illuminates Luigi’s vital role in the broader data engineering ecosystem. The volume describes powerful integrations with databases, filesystems, distributed compute frameworks, and cloud-native architectures. With chapters on observability, governance, and advanced use cases—such as machine learning pipelines, real-time analytics, and hybrid cloud deployments—the book concludes by envisioning Luigi’s future, examining innovations like serverless orchestration, AI-driven workflow optimization, and the ongoing evolution of Luigi’s vibrant open-source community. This is an essential resource for data engineers and architects seeking both foundational mastery and cutting-edge insight into orchestrated data workflows.