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Auto-scaling deadline-constrained workloads

Formale Metadaten

Titel
Auto-scaling deadline-constrained workloads
Untertitel
in containers in the cloud
Alternativer Titel
Automated Deadline-Based Scaling of Experiments in the Cloud with MiCADO
Serientitel
Anzahl der Teile
60
Autor
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Lizenz
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Inhaltliche Metadaten

Fachgebiet
Genre
Abstract
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