OxRSE Training

Learning about Docker Containers

The Australian Research Data Commons has produced a short introductory video about Docker containers that covers many of the points below. Watch it before or after you go through this section to reinforce your understanding!

How can software containers help your research?

Australian Research Data Commons, 2021. How can software containers help your research?. [video] Available at: https://www.youtube.com/watch?v=HelrQnm3v4g DOI: http://doi.org/10.5281/zenodo.5091260

Scientific Software Challenges

What's Your Experience?

Take a minute to think about challenges that you have experienced in using scientific software (or software in general!) for your research. Then, share with your neighbors and try to come up with a list of common gripes or challenges.

You may have come up with some of the following:

you want to use software that doesn't exist for the operating system (Mac, Windows, Linux) you'd prefer.
you struggle with installing a software tool because you have to install a number of other dependencies first. Those dependencies, in turn, require other things, and so on (i.e. combinatoric explosion).
the software you're setting up involves many dependencies and only a subset of all possible versions of those dependencies actually works as desired.
you're not actually sure what version of the software you're using because the install process was so circuitous.
you and a colleague are using the same software but get different results because you have installed different versions and/or are using different operating systems.
you installed everything correctly on your computer but now need to install it on a colleague's computer/campus computing cluster/etc.
you've written a package for other people to use but a lot of your users frequently have trouble with installation.
you need to reproduce a research project from a former colleague and the software used was on a system you no longer have access to.

A lot of these characteristics boil down to one fact: the main program you want to use likely depends on many, many, different other programs (including the operating system!), creating a very complex, and often fragile system. One change or missing piece may stop the whole thing from working or break something that was already running. It's no surprise that this situation is sometimes informally termed "dependency hell".

Software and Science

Again, take a minute to think about how the software challenges we've discussed could impact (or have impacted!) the quality of your work. Share your thoughts with your neighbors. What can go wrong if our software doesn't work?

Unsurprisingly, software installation and configuration challenges can have negative consequences for research:

you can't use a specific tool at all, because it's not available or installable.
you can't reproduce your results because you're not sure what tools you're actually using.
you can't access extra/newer resources because you're not able to replicate your software set up.
others cannot validate and/or build upon your work because they cannot recreate your system's unique configuration.

Thankfully there are ways to get underneath (a lot of) this mess: containers to the rescue! Containers provide a way to package up software dependencies and access to resources such as files and communications networks in a uniform manner.

What is a Container? What is Docker?

Docker is a tool that allows you to build what are called "containers." It's not the only tool that can create containers, but is the one we've chosen for this workshop. But what is a container?

To understand containers, let's first talk briefly about your computer.

Your computer has some standard pieces that allow it to work -- often what's called the hardware. One of these pieces is the CPU or processor; another is the amount of memory or RAM that your computer can use to store information temporarily while running programs; another is the hard drive, which can store information over the long-term. All these pieces work together to do the "computing" of a computer, but we don't see them because they're hidden from view (usually).

Instead, what we see is our desktop, program windows, different folders, and files. These all live in what's called the filesystem. Everything on your computer -- programs, pictures, documents, the operating system itself -- lives somewhere in the filesystem.

NOW, imagine you want to install some new software but don't want to take the chance of making a mess of your existing system by installing a bunch of additional stuff (libraries/dependencies/etc.). You don't want to buy a whole new computer because it's too expensive. What if, instead, you could have another independent filesystem and running operating system that you could access from your main computer, and that is actually stored within this existing computer?

Or, imagine you have two tools you want to use in your groundbreaking research on cat memes: PurrLOLing, a tool that does AMAZINGLY well at predicting the best text for a meme based on the cat species and WhiskerSpot, the only tool available for identifying cat species from images. You want to send cat pictures to WhiskerSpot, and then send the species output to PurrLOLing. But there's a problem: PurrLOLing only works on Ubuntu and WhiskerSpot is only supported for OpenSUSE so you can't have them on the same system! Again, we really want another filesystem (or two) on our computer that we could use to chain together WhiskerSpot and PurrLOLing in a "pipeline"...

Container systems, like Docker, are special programs on your computer that make it possible! The term "container" can be usefully considered with reference to shipping containers. Before shipping containers were developed, packing and unpacking cargo ships was time consuming and error prone, with high potential for different clients' goods to become mixed up. Just like shipping containers keep things together that should stay together, software containers standardize the description and creation of a complete software system: you can drop a container into any computer with the container software installed (the 'container host'), and it should "just work".

Virtualization

Containers are an example of what's called virtualization -- having a second "virtual" computer running and accessible from a main or host computer. Another example of virtualization are virtual machines or VMs. A virtual machine typically contains a whole copy of an operating system in addition to its own filesystem and has to get booted up in the same way a computer would. A container is considered a lightweight version of a virtual machine; underneath, the container is (usually) using the Linux kernel and simply has some flavour of Linux + the filesystem inside.

One final term: while the container is an alternative filesystem layer that you can access and run from your computer, the container image is the 'recipe' or template for a container. The container image has all the required information to start up a running copy of the container. A running container tends to be transient and can be started and shut down. The container image is more long-lived, as a definition for the container. You could think of the container image like a cookie cutter -- it can be used to create multiple copies of the same shape (or container) and is relatively unchanging, where cookies come and go. If you want a different type of container (cookie) you need a different container image (cookie cutter).

Putting the Pieces Together

Think back to some of the challenges we described at the beginning. The many layers of scientific software installations make it hard to install and re-install scientific software -- which ultimately, hinders reliability and reproducibility.

But now, think about what a container is -- a self-contained, complete, separate computer filesystem. What advantages are there if you put your scientific software tools into containers?

This solves several of our problems:

documentation -- there is a clear record of what software and software dependencies were used, from bottom to top.
portability -- the container can be used on any computer that has Docker installed -- it doesn't matter whether the computer is Mac, Windows or Linux-based.
reproducibility -- you can use the exact same software and environment on your computer and on other resources (like a large-scale computing cluster).
configurability -- containers can be sized to take advantage of more resources (memory, CPU, etc.) on large systems (clusters) or less, depending on the circumstances.

The rest of this workshop will show you how to download and run containers from pre-existing container images on your own computer, and how to create and share your own container images.

Use cases for containers

Now that we have discussed a little bit about containers -- what they do and the issues they attempt to address -- you may be able to think of a few potential use cases in your area of work. Some examples of common use cases for containers in a research context include:

Using containers solely on your own computer to use a specific software tool or to test out a tool (possibly to avoid a difficult and complex installation process, to save your time or to avoid dependency hell).
Creating a Dockerfile that generates a container image with software that you specify installed, then sharing a container image generated using this Dockerfile with your collaborators for use on their computers or a remote computing resource (e.g. cloud-based or HPC system).
Archiving the container images so you can repeat analysis/modelling using the same software and configuration in the future -- capturing your workflow.

Key Points

Almost all software depends on other software components to function, but these components have independent evolutionary paths.
Small environments that contain only the software that is needed for a given task are easier to replicate and maintain.
Critical systems that cannot be upgraded, due to cost, difficulty, etc. need to be reproduced on newer systems in a maintainable and self-documented way.
Virtualization allows multiple environments to run on a single computer.
Containerization improves upon the virtualization of whole computers by allowing efficient management of the host computer’s memory and storage resources.
Containers are built from ‘recipes’ that define the required set of software components and the instructions necessary to build/install them within a container image.
Docker is just one software platform that can create containers and the resources they use.

Introduction