Instructor Notes
Before Teaching This Lesson
[Docker][Docker] and its associated ecosystem is rapidly developing. While many core features will be stable, the overall environment changes regularly with version updates and new tools for interacting with Docker and running containers on different platforms.
In particular, there can be differences between macOS, Windows and Linux platforms. Updates and changes introduced in Docker releases are highlighted in the [Docker release notes][Docker release notes].
You are strongly advised to run through the lesson content prior to teaching the lesson to ensure that everything works as expected.
If you experience any issues, please [open an issue][open a lesson issue] in the lesson repository describing the problem and platform(s) affected. The lesson maintainers will aim to resolve the issue as soon as possible but we also welcome the opening of pull requests (linked to issues) that resolve anything that doesn’t work as expected with the lesson content.
Miscellaneous Tips
- Timing: With all the lesson episodes taken together, there’s way more than three hours of material in this lesson. Focusing on the earlier episodes (Introduction through the first half of Creating Container Images) will take just about three hours if you also include a brief general introduction and time to check your learners’ software installations.
-
Install Issues: From the feedback we have received
about past lessons, computers running Microsoft Windows have encountered
the largest number of challenges setting up Docker. Consider having
people check their install in advance at a separate time or come early.
In online workshops, consider using your video conferencing software’s
“breakout room” functionality to form smaller groups within which
participants can troubleshoot their installations. Note that you should
use a more complex command than
docker --versionto test the installation, as the simplestdockercommands to not connect to the Docker backend. -
Virtualization Illustration: When going through the
intro to containers, consider demonstrating what this might look like by
having two shells (or shell tabs) open, one on your host computer and
one into a container you started before the workshop. Then you can
demonstrate in a simple way that from the same (host) computer, you can
access two different types of environments – one via the shell on your
host computer and one via the shell into a running container. Sample
commands could include:
whoami-
pwdandls - something that shows the OS. On mac, this could be
sw_vers, on linuxcat /etc/os-release
- Reflection Exercise: At the beginning and end of the workshop, give participants time to reflect on what they want to get out of the workshop (at the beginning) and what they can apply to their work (at the end). Using the shared notes doc is a great way to do this and a good way to make sure that you’ve addressed specific concerns or goals of the participants.
Learner Profiles and Pathways
In this section we provide some details of example learner profiles and suggest some possible different pathways or technical focuses to consider when teaching or planning a lesson based around this Docker material. As such, the information in this section is not designed to define fixed approaches and structures for teaching this material. It is instead aimed to provide ideas and inspiration and to encourage you to think about your audience when preparing to teach this material. The information here is based on both discussions about the intended audiences for this material and on direct experiences of instructors who have taught it at workshops following different technical pathways.
Learner profiles
We begin by providing some example learner profiles to highlight the potential target audience and the types of different research and technical backgrounds that you may find among learners engaging with this material. With these profiles, we aim to encourage you to think about the learners attending your workshop(s) and which episodes it may be most useful to teach.
Nelson is a graduate student in microbiology. They have experience in running Unix shell commands and using libraries in R for the bioinformatics workflows they have developed. They are expanding their analysis to run on 3000 genomes in 200 samples and they have started to use the local cluster to run their workflows. The local research computing facilitator has advised them that Docker could be useful for running their workflows on the cluster. They’d like to make use of existing containers that other bioinformaticians have made so they want to learn how to use Docker. They would also be interested in creating their own Docker images for other lab members and collaborators to re-use their workflows.
Caitlin is a second year undergraduate in computer science examining Docker for the first time. She has heard about Docker but does not really know what it achieves or why it is useful. She is reasonably confident in using the Unix shell, having used it briefly in her first year modules. She is keen to find jump-off points to learn more about technical details and alternative technologies that are also popular, having heard that container technologies are widely used within industry.
Xu, a materials science researcher, wants to package her software for release with a paper to help ensure reproducibility. She has written some code that makes use of a series of Python libraries to undertake analysis of a compound. She wants to (or is required to) make her software available as part of the paper submission. She understands why Docker is important in helping to ensure reproducibility but not the process and low-level detail of preparing a container and archiving it to obtain a DOI for inclusion with the paper submission.
Bronwyn is a PhD student running Python/R scripts on her local laptop/workstation. She is having difficulty getting all the tools she needs to work because of conflicting dependencies and little experience with package managers. She is also keen to reduce the overhead of managing software so she can get on with her thesis research. She has heard that Docker might be able to help out but is not confident to start exploring this on her own and does not have access to any expertise in this within her local research group. She currently wants to know how to use preexisting Docker containers but may need to create her own containers in the future.
Virat is a grad student who is running an obscure bioinformatics tool (from a GitHub repo) that depends on a number of other tools that need to be pre-installed . He wants to be able to run on multiple resources and have his undergrad assistant use the same tools. Virat has command line experience and has struggled his way through complex installations but he has no formal CS background - he only knows to use containers because a departmental IT person suggested it. He is usually working from a Windows computer. He needs to understand how to create his own container, use it locally, and train his student to use it as well.
Considering things from a higher level, we also highlight three core groups of learners, based on job roles, who you may find attending lessons covering this material. While recognising that there are likely to be many learners who don’t fit into one of the following groups, or who span more than one of them, we hope that highlighting these groups helps to provide an example of the different types of skills and expertise that learners engaging with this material may have:
Researchers: For researchers, even those based in non-computational domains, software is an increasingly important element of their day-to-day work. Whether they are writing code or installing, configuring and/or running software to support their research, they will eventually need to deal with the complexities of running software on different platforms, handling complex software dependencies and potentially submitting their code and data to repositories to support the reproduction of research outputs by other researchers, or to meet the requirements of publishers or funders. Software container technologies are valuable to help researchers address these challenges.
RSEs: RSEs – Research Software Engineers – provide software development, training and technical guidance to support the development of reliable, maintainable, sustainable research software. They will generally have extensive technical skills but they may not have experience of working with or managing software containers. In addition to working with researchers to help build and package software, they are likely to be interested in how containers can help to support best practices for the development of research software and aspects such as software deployment.
Systems professionals: Systems professionals represent the more technical end of our spectrum of learners. They may be based within a central IT services environment within a research institution or within individual departments or research groups. Their work is likely to encompass supporting researchers with effective use of infrastructure and they are likely to need to know about managing and orchestrating multiple containers in more complex environments. For example, they may need to provide database servers, web application servers and other services that can be deployed in containerized environments to support more straightforward management, maintenance and upgradeability.
Learner Pathways
We now come to look at some ideas around learner pathways for learners interested in Docker, and container technologies more generally.
Containers involve a variety of different technologies, and teaching material about them can therefore encompass significant volumes of technical information. Depending on the domain they work in, and their motivation for taking a course covering this material, learners are likely to have various different reasons for wanting to learn about Docker, that may not necessarily all overlap. The material in this lesson covers a set of core concepts, introducing containers and then looking at the key features of Docker and how to use them.
Moving beyond the core features there are a number of topics that are likely to only be of interest to different sub-groups of learners. To support these different groups of learners we have developed a set of “learner pathways” that provide suggested routes through the material based on different use cases or areas of interest.
You are, of course, welcome to mix and match lesson content to offer a course that best suits your target audience but we are listing some different pathways or themes for covering this material to offer you some guidance and examples of the different routes through the material that you might want to consider. Each pathway will have a slightly different emphasis on specific sets of topics. We highlight learner different profiles that we believe map well to specific pathways.
Note that the material in this lesson continues to develop and experience of teaching the material is increasing. In due course we intend to offer more detailed pathway information including specific episode schedules that we think are most suited to the pathways highlighted.
Core content:
The Docker lesson contains a set of core content that we expect to be relevant for all learner pathways. This includes:
- Introducing container concepts and the Docker software
- Running through the basic use of Docker including:
- Core commands for listing and managing images and containers
- Obtaining container images from Docker Hub
- Running containers from container images
- Building container images
Beyond this, different pathways offer scope to bring in different episodes containing different lesson content to support different target audiences or areas of interest
Some suggested pathways include:
-
Reproducible research
- Common learner profiles: Researcher; RSE
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Cloud computing
- Common learner profiles: Sytems professional, RSE
-
High performance computing
- Common learner profiles: Researcher; RSE; Systems professional
Common Points of Confusion
- difference between a container and container image
- what it means for a container to be stopped (but not removed)
- differences in container behaviour between hosts that are running
Linux compared to hosts running macOS or Microsoft Windows
- on Linux hosts there is usually only one OS kernel shared between the host and the containers, so less separation than is typical when using macOS or Windows hosts. This can lead to effects such as volume mounts behaving differently, e.g., regarding filesystem permissions, user and group mappings between the host and the container.