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Automated Deadline-Based Scaling of Experiments in the Cloud with MiCADO

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Automated Deadline-Based Scaling of Experiments in the Cloud with MiCADO
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60
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Many scientific applications require computation resources based on dynamically changing requirements. The H2020 COLA (project-cola.eu) set out to solve this with a generic framework (MiCADO) to support automated scalability of applications deployed to the cloud. MiCADO is open-source, cloud agnostic and uses widely applied technologies - Kubernetes, Occopus and Prometheus - to scale virtual machines and containers in the cloud. MiCADO has been tested on a range of small to large-scale research activities that saw simulations and other multi-job experiments queued, executed and scaled in containers on different public and private clouds. The talk will focus on MiCADO, its architecture, characteristics, and its benefits to the RSE community.