Feature tracking guidance for PMs
Description
This merge request adds a new section to the handbook titled "Guidance for Instrumenting Feature Tracking." It provides a comprehensive guide for Product Managers on how to implement and track metrics for their features. The new content includes quick links to relevant resources, information about self-service feature tracking dashboards, and a step-by-step process for instrumenting feature tracking. It also covers special considerations for AI Gateway features and lists key contacts and resources. This addition aims to streamline the process of feature tracking and ensure consistent data collection across GitLab's product teams.
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Added a description to this MR explaining the reasons for the proposed change, per say why, not just what - Copy/paste the Slack conversation to document it for later, or upload screenshots. Verify that no confidential data is added, and the content is SAFE
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Commits
- Feature tracking guidance
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Activity
added HandbookContent label
assigned to @efergen
Previous linting failures have been resolved. Resolving this thread!
Edited by ****requested review from @cbraza
requested review from @tjayaramaraju
Resolved by Ankit Panchal@tjayaramaraju & @cbraza - I drafted up an MR to provide PMs with guidance on the process for feature tracking. If you could both review the process and technical details, I'd greatly appreciate it!
@tjayaramaraju I'd specifically love your feedback on if there are any other actions that need to be taken from an Analytics Instrumentation perspective that I didn't consider. I was particularly unsure on if any other actions were needed to track AI Gateway events via the unit primitive framework other than just creating a new unit primitive .yml.
All feedback is welcome.
Edited by Emma Fergen- Last reply by Ankit Panchal
Using combined codequality.json: vale-codequality.json new_broken_links.json
One of the linters has reported errors and as a result the pipeline has failed. Once the pipeline completes, you'll find the code quality report above which can link you to where the error is in your code. Additionally, below you'll find a table of the errors. The table has links to the lint rules so you can find more information on how to fix the issue(s).
Rule File Line Error Broken link (HugoLinkCheck) content/handbook/enterprise-data/programs/data-for-product-managers/index.md 116 Link destination "/handbook/product/groups/product-analysis/#team-member" does not exist Broken link (HugoLinkCheck) content/handbook/enterprise-data/programs/data-for-product-managers/index.md 370 Link destination "/handbook/enterprise-data/platform/#using-sheetload" does not exist If you need more help please reach out on Slack in #mr-buddies.
Edited by ****112 **Owner: Engineer** 113 - Perform [local testing](https://docs.gitlab.com/ee/development/internal_analytics/internal_event_instrumentation/local_setup_and_debugging.html) 114 - Request review from Analytics Instrumentation team member 115 - Verify test events match properties defined in the Issue 116 117 1. Create Analysis 118 119 **Owner: Product Analyst** 120 - Wait 1-2 weeks after MR merge for sufficient data collection 121 - Complete requirements specified in PDI Issue (if applicable) 122 123 ### Special Considerations for AI Gateway Features 124 125 For features routed through the AI Gateway: 126 127 - New distinct features should be represented as a [unit primitive](https://gitlab.com/gitlab-org/cloud-connector/gitlab-cloud-connector/-/tree/main/config/unit_primitives). This will enable AI features to be tracked automatically via a new AI Gateway events tracking system. AI Gateway events using the unit primitive framework cannot be blocked by users and are tracked at the event grain for all deployment types. -
Question: For a new feature, it's possible there might be a need for a new unit primitive. Should we also include the process of adding them with the help of groupcloud connector and instrumenting it in the AI Gateway?
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Absolutely @ankit.panchal! Do you have any specific recommendations on that? I haven't witnessed that process. I can include a general recommendation to reach out to a cloud connector slack channel if not.
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@sguyon Perhaps you have thoughts on this - This MR is intended to provide instructions for PMs on instrumenting feature tracking. There is a section for AI GW specific instructions. Trying to keep instructions as simple as possible but would love your thoughts.
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142 - New distinct features should be represented as a [unit primitive](https://gitlab.com/gitlab-org/cloud-connector/gitlab-cloud-connector/-/tree/main/config/unit_primitives). This will enable AI features to be tracked automatically via a new AI Gateway events tracking system. AI Gateway events using the unit primitive framework cannot be blocked by users and are tracked at the event grain for all deployment types. 142 - New distinct features should be represented as a [unit primitive](https://gitlab.com/gitlab-org/cloud-connector/gitlab-cloud-connector/-/tree/main/config/unit_primitives). This will enable AI features to be tracked automatically via a new AI Gateway events tracking system. AI Gateway events using the unit primitive framework cannot be blocked by users and are tracked at the event grain for all deployment types. 143 - If there is a requirement for adding a new unit primitive for the feature, reach out to ~"group::cloud connector" who can add the new unit primitive for the respective feature. To track the usage of the new unit primitive, reach out to ~"group::analytics instrumentation" with the necessary fields to be tracked. -
Thanks so much for your help on this @ankit.panchal ! I'll post to the analytics instrumentation slack channel when merged so that folks know this resource exists now!
changed this line in version 13 of the diff
@efergen Overall it's looking good! Great job. I added a few comments and suggestions inline.
Edited by Sacha Guyon-
Great thank you @sguyon ! I merged the first iteration of this handbook section earlier today, but am happy to open up another MR this week to add in your feedback. Very much appreciate you taking a peek!
added 1 commit
- 6a88f947 - Increasing clarity from suggested content and lint pipeline correction
requested review from @hsutor
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@hsutor tagging you in on this MR with instructions for PMs on instrumenting feature tracking as we discussed yesterday. Let me know if any of this content could be clarified from a PMs perspective.
Edited by Emma Fergen 
started a merge train
