Goal: Provide queryable metrics and telemetry for cluster routes and sharding in an OpenShift cluster.

Problem: Today we test OpenShift performance and scale with best-guess or anecdotal evidence for the number of routes that our customers use. Best practices for a large number of routes in a cluster is to shard, however we have no visibility with regard to if and how customers are using sharding.

Why is this important? These metrics will inform our performance and scale testing, documented cluster limits, and how customers are using sharding for best practice deployments.

Dependencies (internal and external):

Prioritized epics + deliverables (in scope / not in scope):

Not in scope:

Estimate (XS, S, M, L, XL, XXL):

Previous Work:

Open questions:

Acceptance criteria:

Epic Done Checklist:

• CI - CI Job & Automated tests: <link to CI Job & automated tests>
• Release Enablement: <link to Feature Enablement Presentation> 
• DEV - Upstream code and tests merged: <link to meaningful PR orf GitHub Issue>
• DEV - Upstream documentation merged: <link to meaningful PR or GitHub Issue>
• DEV - Downstream build attached to advisory: <link to errata>
• QE - Test plans in Polarion: <link or reference to Polarion>
• QE - Automated tests merged: <link or reference to automated tests>
• DOC - Downstream documentation merged: <link to meaningful PR>
• Notes for Done Checklist: 
  • Adding links to the above checklist with multiple teams contributing; select a meaningful reference for this Epic.
  • Checklist added to each Epic in the description, to be filled out as phases are completed - tracking progress towards “Done” for the Epic.