orchestration tools
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2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Orazio Tomarchio ◽  
Domenico Calcaterra ◽  
Giuseppe Di Modica ◽  
Pietro Mazzaglia

AbstractThe growth in the number and types of cloud-based services offered to IT customers is supported by the constant entry of new actors in the market and the consolidation of disruptive technologies such as AI, Big Data and Micro-services. From the customer’s perspective, in a market landscape where the cloud offer is highly diversified due to the presence of multiple competing service providers, picking the service that best accommodate their specific needs is a critical challenge. Once the choice is made, so called “cloud orchestration tools” (orchestrators) are required to take care of the customer application’s life-cycle. While big players offer their customers proprietary orchestrators, in the literature quite a number of open-source initiatives have launched multi-cloud orchestrators capable of transparently managing applications on top of the most representative cloud platforms. In this paper, we propose TORCH, a TOSCA-based framework for the deployment and orchestration of cloud applications, both classical and containerised, on multiple cloud providers. The framework assists the cloud customer in defining application requirements by using standard specification models. Unlike other multi-cloud orchestrators, adopts a strategy that separates the provisioning workflow from the actual invocation of proprietary cloud services API. The main benefit is the possibility to add support to any cloud platforms at a very low implementation cost. In the paper, we present a prototypal implementation of TORCH and showcase its interaction with two different container-based cluster platforms. Preliminary performance tests conducted on a small-scale test-bed confirm the potential of TORCH.


2019 ◽  
Vol 214 ◽  
pp. 07019 ◽  
Author(s):  
Mayank Sharma ◽  
Maarten Litmaath ◽  
Eraldo Silva Junior ◽  
Renato Santana

This article describes a new framework, called SIMPLE, for settingup and maintaining classic WLCG sites with minimal operational efforts and insights needed into the WLCG middleware. The framework provides a single common interface to install and configure any of its supported grid services, such as Compute Elements, Batch Systems, Worker Nodes and miscellaneous middleware packages. It leverages modern container orchestration tools like Kubernetes, Docker Swarm, and confiuration management tools like Puppet, Ansible, to automate deployment of the WLCG services on behalf of a site admin. The framework is modular and extensible by design. Therefore, it is easy to add support for more grid services as well as infrastructure automation tools to accommodate diverse scenarios at different sites. We provide insight into the design of the framework and our efforts towards development, release and deployment of its first implementation featuring CREAM E, TORQUE Batch System and TORQUE based Worker Nodes.


Author(s):  
Saurabh Garg ◽  
Siqi Wang ◽  
Rajiv Ranjan
Keyword(s):  
Big Data ◽  

2018 ◽  
Vol 5 (6) ◽  
pp. 38-47 ◽  
Author(s):  
Alessandro Carrega ◽  
Giancarlo Portomauro ◽  
Matteo Repetto ◽  
Giorgio Robino

Author(s):  
Saurabh Garg ◽  
Siqi Wang ◽  
Rajiv Ranjan
Keyword(s):  
Big Data ◽  

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