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#Modelio 3.3 download code

PaaS: Cloud Foundry, AWS RDS, AWS SQS, AWS Beanstalk.

IaaS: Amazon EC2, Flexiant, CloudSigma, Openstack, Azure plus.

Unavailability problems exist even when 99.9% up-time is.

Cloud performance can vary at any point in time.

Heterogeneity and lack of interoperability among different.

Infrastructure / platform virtualization.

Multi-Clouds with guaranteed Quality of Service (QoS).

#Modelio 3.3 download code

Source Integrated Development Environment (IDE) and Run-timeĮnvironment for the high-level design, early prototyping, semi-Īutomatic code generation, and automatic deployment of applications on MODAClouds provides methods, a decision support system, an open

MODAClouds will help us to support this.

What if any of these constraints change?.

Some need on premises ‘private cloud’ hosting.

Released in December 2013 Target with MODAClouds LINE and SPACE4Cloud allow developers to analyse the application performance, considering common causes of uncertainty in virtualizedĬonstellation: a Multi-Cloud Application Designed with the MODAClouds Integrated Modelling Environment

The run-time tool to enact the deployment and adaptation of cloud applications. The first tool, CLOUDML, provides abstractions to represent deployment models at design-time together with This paper focuses on three tools: CLOUDML, SPACE4Clouds and LINE. The environment supports the modelling of cloud applications using domain-specific UML extensions, integrating specialized toolsīy means of model transformations. In this paper we report how Softeam leveraged the MODAClouds model-driven methodologyĪnd environment to cloudify its collaborative modelling application called Constellation. The MODAClouds project developed an integrated modelling environment to cope with Two major sources of uncertainty challenge the development of cloud applications are : (i) the maintenanceĬost uncertainty caused by cloud APIs heterogeneity and vendor lock-in and (ii) the performance uncertaintyĬaused by virtualization.