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Re-implement scheduling-throughput measurement #1027
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Issues go stale after 90d of inactivity. If this issue is safe to close now please do so with Send feedback to sig-testing, kubernetes/test-infra and/or fejta. |
/remove-lifecycle stale |
Issues go stale after 90d of inactivity. If this issue is safe to close now please do so with Send feedback to sig-testing, kubernetes/test-infra and/or fejta. |
/remove-lifecycle stale |
Issues go stale after 90d of inactivity. If this issue is safe to close now please do so with Send feedback to sig-testing, kubernetes/test-infra and/or fejta. |
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/assign |
Currently, new prometheus metric is already implemented and data is collected for all tests in master branch. |
Unless we start scraping metrics more/less often. We may consider scraping more often potentially too.
Which is the right decision :) |
Issues go stale after 90d of inactivity. If this issue is safe to close now please do so with Send feedback to sig-contributor-experience at kubernetes/community. |
/remove-lifecycle stale |
Issues go stale after 90d of inactivity. If this issue is safe to close now please do so with Send feedback to sig-contributor-experience at kubernetes/community. |
/remove-lifecycle stale |
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Currently, we have a very crude logic for computing scheduling-throughput. We list all pods every 5s and see how many new pod very scheduled in that time. It doesn't work well in small tests where number of pods is low as we only get 1-2 representative 5s windows.
We should rewrite it to make it more reliable and accurate, e.g. use prometheus query to monitor rate of pod bindings
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