Time-critical applications, such as early warning systems or live event broadcasting, present particular challenges. They have hard limits on Quality of Service constraints that must be maintained, despite network fluctuations and varying peaks of load. Consequently, such applications must adapt elastically on-demand, and so must be capable of reconfiguring themselves, along with the underlying cloud infrastructure, to satisfy their constraints. Software engineering tools and methodologies currently do not support such a paradigm. In this paper, we describe a framework that has been designed to meet these objectives, as part of the EU SWITCH project. SWITCH offers a flexible co-programming architecture that provides an abstraction layer and an underlying infrastructure environment, which can help to both specify and support the life cycle of time-critical cloud native applications. We describe the architecture, design and implementation of the SWITCH components and describe how such tools are applied to three time-critical real-world use cases.
SummaryThe increasing volume of data being produced, curated, and made available by research infrastructures in the environmental science domain require services that are able to optimize the delivery and staging of data for researchers and other users of scientific data. Specialized data services for managing data life cycle, for creating and delivering data products, and for customized data processing and analysis all play a crucial role in how these research infrastructures serve their communities, and many of these activities are time‐critical—needing to be carried out frequently within specific time windows. We describe our experiences identifying the time‐critical requirements of environmental scientists making use of computational research support environments. We present a microservice‐based infrastructure optimization suite, the Dynamic Real‐Time Infrastructure Planner, used for constructing virtual infrastructures for research applications on demand. We provide a case study whereby our suite is used to optimize runtime service quality for a data subscription service provided by the Euro‐Argo using EGI Federated Cloud and EUDAT's B2SAFE services, and to consider how such a case study relates to other application scenarios.
The infrastructure-as-a-service (IaaS) model of cloud computing provides virtual infrastructure functions (VIFs), which allow application developers to flexibly provision suitable virtual machines' (VM) types and locations, and even configure the network connection for each VM. Because of the pay-as-you-go business model, IaaS provides an elastic way to operate applications on demand. However, in current cloud applications DevOps (software development and operations) lifecycle, the VM provisioning steps mainly rely on manually leveraging these VIFs. Moreover, these functions cannot be programmatically embedded into the application logic to control the infrastructure at runtime. Especially, the vendor lock-in issue, which different clouds provide different VIFs, also enlarges this gap between the cloud infrastructure management and application operation. To mitigate this gap, we designed and implemented a framework, CloudsStorm, which enables developers to easily leverage VIFs of different clouds and program them into their cloud applications. To be specific, CloudsStorm empowers applications with infrastructure programmability at design-level, infrastructure-level, and application-level. CloudsStorm also provides two infrastructure controlling modes, ie, active and passive mode, for applications at runtime. Besides, case studies about operating task-based and big data applications on clouds show that the monetary cost is significantly reduced through the seamless and on-demand infrastructure management provided by CloudsStorm. Finally, the scaling and recovery operation evaluations of CloudsStorm are performed to show its controlling performance. Compared with other tools, ie, "jcloud" and "cloudinit.d", the scaling and provisioning performance evaluations demonstrate that CloudsStorm can achieve at least 10% efficiency improvement in our experiment settings. KEYWORDS DevOps, federated clouds, infrastructure-as-a-service, networked virtual infrastructureThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. each individual VM instead of the entire infrastructure topology. In comparison, there are also some environment-centric 1 tools to help developers orchestrate their applications, which include Puppet, # Chef, ‖ etc. These tools more focus on the cluster management, ie, deployment and configuration, instead of provisioning and scaling automation. Some academic research studies also propose architectures for developing and orchestrating applications on clouds, eg, CometCloud 6 and mOSAIC. 7 However, most of these architectures themselves are platforms, which require manually to set up the cluster in advance and lack the ability of provisioning VM resources. (3) Application-level. Hadoop applications require application-level programmability to directly adjust the infrastructure to fit for the application constraints or workload. Because of the pay-as-you-go business ...
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