Rosetta: a container-centric science platform for resource-intensive, interactive data analysis

TL;DR

Rosetta is a versatile science platform that leverages containerized microservices to enable resource-intensive, interactive data analysis across various scientific domains, supporting custom environments and multiple computing resources.

Contribution

It introduces a novel container-centric architecture based on microservices for flexible, reproducible, and resource-efficient interactive data analysis.

Findings

Supports a wide range of container engines and runtimes

Enables seamless integration with workload management systems

Applicable across multiple scientific disciplines

Abstract

Rosetta is a science platform for resource-intensive, interactive data analysis which runs user tasks as software containers. It is built on top of a novel architecture based on framing user tasks as microservices - independent and self-contained units - which allows to fully support custom and user-defined software packages, libraries and environments. These include complete remote desktop and GUI applications, besides common analysis environments as the Jupyter Notebooks. Rosetta relies on Open Container Initiative containers, which allow for safe, effective and reproducible code execution; can use a number of container engines and runtimes; and seamlessly supports several workload management systems, thus enabling containerized workloads on a wide range of computing resources. Although developed in the astronomy and astrophysics space, Rosetta can virtually support any science and technology domain where resource-intensive, interactive data analysis is required.