Container Camp

Take Reproducible Science to the Next Level

March 15–17, 2021

9:00AM–1:00PM US Pacific Time (11:00AM–3:00PM US Eastern Time)

This multi-day meet-up will teach you the basics of container technology, how to run containers, and how to build them. Check out the agenda.

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Container technologies are letting researchers easily share, scale, and reuse tools and workflows for all types of computational analyses.

Join us for an intensive three-day hands-on workshop to learn how to create, use, deploy and share software containers (e.g., Docker, Singularity) across a variety of computational systems from your laptop to cloud and HPC.

We will use a blend of practical theory and hands-on exercises where small groups deploy tools and workflows they bring to the workshop. Participants are encouraged to bring their own data and analyses for containerization – come with basic command line skills (required) and leave with a running container! No experience with container technology needed.

Who should attend?

Any researcher seeking to exploit container technology to make their computational analyses easier and more reproducible. Must enjoy a collaborative, innovative environment. Preference is given to NSF BIO-funded PIs and early career researchers.

What will I learn?

What is container technology and how to use it
How to containerize an application
How to use other containerized applications
How to build (or deploy) containerized workflows
How to scale out your computation: from laptop to cloud to HPC

What's new this year?

More hands-on time for your project (make sure to bring your own data!)
Using containers interactively

Did you know?

What are Containers?

A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably. They allow you to focus on your scientific analysis by making it easier to manage dependencies, sharing and reproducing analyses from other researchers with ease.

Real World Example

A 4-month undergraduate microbiology class at the University of British Columbia uses containers to teach the concepts and applications of bioinformatics research to biologists. The 85 students each had their own isolated container, protecting their individual work from each other, and access to a shared course folder provided by the instructor (source).

BYOD/BOYA

Bring your own data and analyses. Course participants are encouraged to bring their own data and analytical workflows for containerization.

Minimum experience required for attendees:

Using Linux command line, directory structures, shell commands
Using and running analysis tools from the command line
Logging into and using remote systems
Basic programming experience (language of your choice)

“The highlight of Camp was the moment where I got something to build faster from an existing repository than building a linux container from scratch and adding a few things.” - Anonymous Survey Participant

“I really liked the BYOD aspect of this camp and how hands-on it was. I was also impressed that there was still a lecture aspect to the camp.” - Anonymous Survey Participant

“The highlight of camp for me was being able to deploy containers on my personal computer on Day 1.” - Anonymous Survey Participant

“The trainers are helpful answering questions and helping around. The group project is very useful to apply what I learned to real problems.” - Anonymous Survey Participant

“The highlight for me was working hands on with a group on a project and the desire for other participants to help each other.” - Anonymous Survey Participant

“Container Camp was really well worth the time I spent there, thank you so much!” - Anonymous Survey Participant

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Container Camp

March 15–17, 2021

Who should attend?

What will I learn?

What's new this year?

What are Containers?

Real World Example

BYOD/BOYA

Minimum experience required for attendees:

Instructors

Nirav Merchant

Tyson Swetnam

Reetu Tuteja

Ryan Bartelme

Jason Williams

Amanda Cooksey

What Container Campers Are Saying...

An Open Science Workspace for Collaborative Data-driven Discovery