As infrastructure providers, we are often thrust into a user support role (as well as a teaching role). We should look at this as a good thing: support of top-level science requires an intimate connection to the tools to do that science. I see that as part of our plan.
This talk is about Aalto Scientific Computing’s user support. It is designed as much to explain our philosophy of user support as it is to talk about specific tools. It takes a critical view of some existing common practices, as discussed in CodeRefinery/NordicHPC channels.
What does “user support” even mean?
AaltoSciComp’s lines of user support
Strategic risks and considerations
We are Aalto Scientific Computing - Science-IT (HPC) - Department IT (CS, NBE, PHYS) - Close collaborations with Aalto ITS, CSC, FCCI
Our collaboration used to be called “Finnish Grid and Cloud Infrastructure”, now will be called “Finnish Computing Competence Infrastructure” so user support is clearly more important than ever.
We are proud of our user support, but it is a multi-faceted approach which requires the right mindset.
Role of user support in scientific computing
User support has a bad reputation
Customers often think it is really bad (the support staff hate me!)
Support staff often hate doing it (the customers don’t know anything!)
Our term “issue” or “ticket” implies it’s a discrete task that you want to end as soon as possible.
Technology is hard
Users usually don’t give enough information to solve the issue.
… Users don’t even know how to give enough information.
We often pick up slack when something isn’t otherwise taught
We are disconnected from the user community
User support may be some forced extra thing on top of our “real” job.
Types of support
How do we even answer questions people may have? Some issues are system bugs that are our action items, but when the user themself needs help we can make some hierarchy of support strategies:
“read the manual: <link>”
tell them what to do
give them a live demo
pair program working example, you lead
do the task for them, no need to teach
Lower letters are faster to answer and traditional support. Higher letters are much more time-consuming, and approach mentoring or Research Software Engineering services.
Why is support hard?
“Crisis of computing”: most users skills are much less than needed.
User interfaces are usually bad
Lots of hidden internal state
People ask for what they think they need (X)
They are given X
X isn’t even a good way of doing what they actually want (Y), but we spend a huge amount of time doing X, when the right way Z→Y is much simpler.
XY problem (wikipedia): people don’t ask for the end goal, but some intermediate step.
XY solution (my term): Support person wants to answer X because it requires less investigation and you can close the ticket and move on, even though they get the feeling it’s not a good idea.
“How to help someone use a computer” by Phil Agre: https://www.librarian.net/stax/4965/how-to-help-someone-use-a-computer-by-phil-agre/
Hanlon’s razor: “never attribute to malice that which is adequately explained by stupidity”
In our case, this is never attribute to malice or stupidity that which is adequately explained by having never been told something obvious
Avoid expressing unhappiness, displeasure, a condescending attitude, expectation that they should have known better, “damage”, etc.
Resist the temptation to blame the user. If they actually can do something that harms others, it’s the system’s fault. If they don’t know something, the UI is bad or society’s preparation is not enough. Etc.
SciComp`s user support tools
Our general guidelines
“help page”, scicomp.aalto.fi/help
Describes what to do in general, key points to mention when making a request.
It links to a longer “how to ask for help”
Both can be a bit patronizing to link to during an issue, so we have to be careful.
Gitlab issue tracker
We use Aalto Gitlab (version.aalto.fi) as issue tracker
University single-sign on
“Internal” permissions (anyone who can log in)
Common interface, reasonably powerful labelling, searching, etc.
When is an issue closed? As soon as possible, or when you are sure they are happy?
We are too much “when we are sure they are happy”, which often is “never”
Closing too soon discourages asking for help.
Is issue the right term here, or is conversation the right term?
Email is a bad medium, advanced issues should be public so that users can learn from each other and we don’t have to type the same thing over and over.
Low threshold to direct to the issue tracker instead of email.
Most users know this and we get few emails
Aalto IT services uses Efecte, CS uses its own RT (much nicer).
Three groups: scicomp, scip (teaching), rse-group (RSE services).
Online “office hours” via Zoom
Every day, 13-14. If no one comes, it’s admin chat time.
Amazingly good for keeping a community going.
Is chat a good idea or does it get out of hand? Remains to be seen
Current philosophy: we need to build community. Chat is not for issues, but chat and determining if something should be an issue or not.
Uses Aalto-hosted Zulipchat. Believe us, just don’t use Slack.
Not done in pandemic time, obviously
Mostly replaced by “daily garage” which is better anyway
Our offices are spread around the departments we serve, and we accept drop-ins anytime we are there.
This keeps us closely connected to the community.
Most of us came from the departments we serve now
Our existing networks are a good way of contacting us
I (rkdarst) really discourage this and always direct people to one of the tracked means.
My phrasing “If you send it to me personally, I am almost certain to eventually forget to reply, and I may not be the person who can best answer you anyway.” Then I usually try to give some sort of an attempt at an answer, since I have to give the appearance that I really care.
Strategic vision of support
Support ↔ teaching ↔ RSE
Support: one-to-one answering questions
Teaching: one-to-many improving skills
Research Software Engineering: one-to-few “I will do it for you” or “Let me get you started”
The middle layer of science always gets cut first: when funding goes down, support will get cut and researchers left more alone.
Our load increases, and our funding doesn’t
We become unhappy, support level goes down
Emphasis increases on speed of closing tickets
Strategic benefits of good support
These can be used to argue for good funding of our teams:
Without good user skills, people can’t make their computational work reproducible or shareable.
We need to claim our place in this problem, rather than let it go to administrative Open Science staff.
Exercise: problematic situations
Someone emails you privately about something they have clearly not even tried yet.
A new researcher is trying to use Triton to do some machine learning. They are trying to use Python+Jupyter, but minimal experience managing a Python environment.
What do you think?
Do we have too many lines of support?
SciComp’s User help page
Richard Darst’s talk on Support services vs diversity
How to ask for help with supercomputers, the counterpoint of this from the user perspective.
#NordicHPC threads on CodeRefinery chat, which has provided many ideas
How to write good support requests, by Sigma2 (Norway)
Author/editor: Richard Darst
Thanks to Radovan Bast, Anne Fouilloux, and others in the CodeRefinery NordicHPC channel for good discussions.