Speaker
Description
Data analytics platforms have become increasingly important in modern research,
enabling scientists to analyze large datasets and extract valuable insights.
Reproducible and open science is a crucial aspect of nowadays scientific research, ensuring
that results are transparent, verifiable, and can be reproduced by other
researchers. Workflow tools, Virtual Research Environments (VREs), and
computational notebooks are among the many tools that may help with this goal.
However, deploying these tools can be complex, time-consuming, and also not
successful in the end.
We provide a managed Kubernetes platform that can be used for reliable and
easy deployment. In this poster, we present several use cases including
Jupyter notebooks, Binder deployment with Kaniko builder, Dask
compute clusters, and S3 backend storage as success story of services
built on the managed Kubernetes platform.
| Key Topic | Data analytics platforms and reproducible open science |
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