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TRT-2350: Include additional OTE metadata in JUnit results #30431
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@stbenjam: This pull request references TRT-2350 which is a valid jira issue. Warning: The referenced jira issue has an invalid target version for the target branch this PR targets: expected the story to target the "4.21.0" version, but no target version was set. In response to this:
Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the openshift-eng/jira-lifecycle-plugin repository. |
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: stbenjam The full list of commands accepted by this bot can be found here. The pull request process is described here
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/test e2e-aws-ovn |
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/test e2e-aws-ovn |
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@neisw Updated to include additional info: <testcase
name="[Jira:config-operator][sig-api-machinery] sanity test should always pass [Suite:openshift/cluster-config-operator/conformance/parallel]"
time="0"
start-time="2025-11-12T20:06:48Z"
end-time="2025-11-12T20:06:48Z"
lifecycle="blocking"
source-image="cluster-config-operator"
source-binary="cluster-config-operator-tests-ext"
source-commit="347bebcc1"
/> |
Extend JUnit test case schema with OpenShift Test Extensions (OTE) metadata attributes. Metadata fields added: - Lifecycle classification (blocking/informing) - Test execution timestamps (start-time, end-time) - Source tracking (source-image, source-binary, source-url, source-commit) The source fields allow tracking which container image, binary, repository, and commit produced each test result, enabling better traceability and debugging of test failures across different builds.
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@stbenjam: all tests passed! Full PR test history. Your PR dashboard. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes-sigs/prow repository. I understand the commands that are listed here. |
This allows us to add additional important information into the JUnit BigQuery table for use in Component Readness, or AI tools for analysis (e.g. correlating test failures with intervals).