The 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, TORCH 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 prototypical 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

Tomarchio, O., Calcaterra, D., Di Modica, G., Mazzaglia, P. (2021). TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications. JOURNAL OF GRID COMPUTING, 19(1), 1-25 [10.1007/s10723-021-09549-z].

TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications

Di Modica, Giuseppe;
2021

Abstract

The 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, TORCH 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 prototypical 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
2021
Tomarchio, O., Calcaterra, D., Di Modica, G., Mazzaglia, P. (2021). TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications. JOURNAL OF GRID COMPUTING, 19(1), 1-25 [10.1007/s10723-021-09549-z].
Tomarchio, Orazio; Calcaterra, Domenico; Di Modica, Giuseppe; Mazzaglia, Pietro
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/810783
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