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ARTs:

SRCnet
Benefit hypothesis:

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In this case, what we are looking for is that every time a new use case, or experiment, is included in the repository, we can launch the tests in the target infrastructures, providing at the end of the process the status of the tests in the different SRCs, and the execution metrics for the Endpoints features (CPU, etc...), for the use cases+data. All in an automated way (pipelines deployment, data loading, profiler execution and results obtaining).

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In this case, what we are looking for is that every time a new use case, or experiment, is included in the repository, we can launch the tests in the target infrastructures, providing at the end of the process the status of the tests in the different SRCs, and the execution metrics for the Endpoints features (CPU, etc...), for the use cases+data. All in an automated way (pipelines deployment, data loading, profiler execution and results obtaining).
Acceptance criteria:

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AC: When a new use case and data are entered into the repository, the CI/CD performs the process on the targets [SRCs], execution, etc. and returns the results for each target (with statistics, and hall of fame )

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AC: When a new use case and data are entered into the repository, the CI/CD performs the process on the targets [SRCs] , execution, etc. and returns the results for each target (with statistics, and hall of fame )
Story Point Burn-up:
Overdue:

The idea is to automate the profiling test battery, use cases and data we have in the repository: https://gitlab.com/ska-telescope/src/src-scientific-use-cases/ to deploy automatically on EndPoints within the SRC Net (i.e. SPSRC)

relates to

SP-2906 Profiling studies

Story Point Burn-up: (0%)

Feature Estimate: 0.0

CI/CD for the profiling of SRC scientific use cases.