Case study

How CytoReason scaled computational multiomics research while keeping costs under control

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Benefits at a glance:

30 %

Improvement in researcher productivity

$ 100 k

Annual savings realized for DevOps work

The challenge

Initially a team of five, the CytoReason team developed their own internal tools for managing research. When the team grew to over thirty researchers, they quickly found that their tools didn’t scale and lacked critical functionality:

DevOps complexity

To compensate for managing multiple cloud-based machines, they compromised on one machine for multiple projects per researcher.

Research delays

With a higher project load, the internal framework for DevOps and preserving projects was more difficult to maintain, slowing down research and making results and data hard to find.

Limited IT bandwidth

Computational Biologists and algorithm developers were often frustrated, and internal IT and DevOps teams did not have the bandwidth to support them

They now have multiple cloud machines allocated to projects on an on-demand basis, and scaled back when not in use.

Compute Capsules have created a common standard while also supporting RStudio, Jupyter, and other popular tools.

All computational research is now available for straightforward sharing and collaboration thanks to integrated role-based access control.

CytoReason implemented Code Ocean by installing it on their AWS VPC instance:

The results

Productivity

15-30% increase in researcher productivity realized

Compute efficiency

Through use of built-in compute management features

DevOps cost reduction

$100,000 annual savings realized for DevOps work

“Code Ocean opens the door to automating and scaling major aspects of the research process. With the Code Ocean platform, our scientists can focus on their core competencies, do more, think bigger, and achieve higher goals.”