GitLab UX Scorecard, 10 Jan 2023

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From YouTube: UX Scorecard Fulfillment Utilization FY23 Q4 Determining where my storage is high in order to re

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A

Hi, my name is Matt nerens and I'm, a product designer at gitlab in the Fulfillment utilization group and I'm, going to walk you through my ux scorecard for determining where my storage is high in order to reduce it, and this will be for SAS group owners where this flow starts is in an email, so the group owner would receive an email telling them that their namespace has approximately five percent storage remaining, and we recommend that you buy additional storage to ensure that your service is not interrupted.

A

So purchasing storage is one way to uh fix storage issues, but they can also reduce their storage. So this user is probably thinking. How did this happen and the email doesn't give an indication of what happened instead of just purchasing storage, the user is going to investigate and they're going to go to the usage quotas page where they can see their storage usage, and the first thought here is what's causing. What's causing me to use. 117 megabytes of storage. I know, there's not a lot. These are just example: numbers.

A

um On this part of the UI, there's no indication of what has changed, there's no historical View and it's a little bit difficult to know where to start your investigation, but one place to start would be the table because there's lots of columns that break down the small multiples for each project, and so um this user is going to go in and just start sorting on different columns to see if they can identify a problem with one of their projects.

A

And the thought here is nothing stands out in particular, um the problems with this page is there's no way to dig into into a storage subtype to see. What's going on, you can go into different projects and visit their repos and check their container Registries and things like that. But there's no breakdown within this View um and there's no guarantee that what the user finds is actually causing the problem. So storage usage is super complex.

A

They could be running out of storage because of lots of factors and lots of usage across lots of projects, or they could be running out of storage, because somebody committed a large file or forgot to set up cleanup policies for their artifacts.

A

So there's there's really not a way in this view to determine what exactly is the problem, um and so some suggestions. Suggestions here are to link to some kind of historical view or breakdown of storage subtypes um and allow the historical view to identify uh spikes in different storage types. So that way, you could determine whether your problem was due to like, for example, committing a large file where your storage would spike, or you might just see, like gradual growth over time.

A

um So as they're sorting on different rows, they identify that their artifact storage is looking pretty high again incorrect example numbers. um So why is my store?

A

My artifact storage, so big um problems on this page is there's no onboarding for users to prevent problems before they happen, so this artifacts problem could be because they don't have uh cleanup policies in place or they don't know they don't understand how git lab works with artifacts and how long they're kept um and there's also no indication of how your your projects are configured from this page, and so my suggestion here was a guide or documentation to get all your settings in order from the get-go.

A

So the second, you create a project, some kind of onboarding experience that says: hey, let's make sure you're set up for success.

A

um This user, clicked on the question mark icon, to learn a little bit more about artifacts and found this page. This page suggests that some artifacts can be like the the preservation of the latest artifacts can be disabled.

A

Turning off this setting, so this user thinks okay I'm, going to turn off this setting and realizes that this doesn't necessarily fix their problem because there's a difference between pipeline artifacts and job artifacts and these documentation.

A

These instructions in the documentations are for one and not the other, and so this user will eventually realize that the other type is kept forever and they'll need to do other things to clean those up versus just changing the settings. So the documentation here is really insufficient, um and so my suggestions here are clarified job versus pipeline artifacts and how to clean up and potentially looking at a breakdown of artifact types within the artifact storage numbers.

A

um Whether in this view or in some kind of detail, View.