Add "upgrade available" filter to runners in admin area
Release notes
When looking a list of hundreds of runners, there is no way to see which ones have updates available easily at once. We have added an update available filter to the admin runners table to allow users to filter down their list of runners to only see runners with available updates.
Problem to solve
As described in the UX scorecard recommendations, it is difficult to know the following when looking at the runner admin list view:
- The most recent version of runners (where should my runners be?)
- Runners that are behind that version ^ (how many are behind? how many are more than 2 versions behind?)
- Runners that have updates available Having an overall view of this, without having to paginate through all the runners, is important for Priyanka to carry out her JTBDs.
In #339523 (closed), we were able to create an MVC for this, but it did not provide users with a way to filter down their list of runners to only see runners with updates available.
Intended users
User experience goal
Allow users to see only runners with updates available at once.
Proposal
Add a new filter in the admins runner table named upgrade available
with values of yes
no
.
Available Tier
This feature is available for customers in Ultimate as it is one foundational feature supporting the vision of providing enterprise customers a centralized view, configuration management capabilities, and predictive analytics to administer a fleet of GitLab Runners easily.
Customers in GitLab Free or Premium could also benefit from this feature set. However, based on customer feedback, customers in Ultimate, either on GitLab SaaS or Self-Managed, typically manage large fleets (100s to 1,000s) of Runners at the instance, group, or project level.
Therefore we have decided to make the backend API for the upgrade available filter available to all tiers. However, the UI features such as this one, which is essential to the centralized management vision for Runner Fleet is only available in Ultimate.
Feature Usage Metrics
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What does success look like, and how can we measure that?
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