Crafting Data - Augmenting results from Azure DevOps build/test pipelines
To understand the health of the code in QUBO algorithm, we needed to understand the performance of the algorithm. We ran a sanity test on each check-in and then a more comprehensive test suite each night there was a check-in. The reporting provided Azure DevOps Analytics for build / tests provided was not enough to evaluate the algorithm performance, so we augmented the information from the tests and created this report. information from a test runner point of view.
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- Silver Data Analytics
To understand the health of the code in QUBO algorithm, we needed to understand the
performance of the algorithm. We ran a sanity test on each check-in and then a more
comprehensive test suite each night there was a check-in. The reporting provided
Azure DevOps Analytics for build / tests provided was not enough to evaluate the
algorithm performance, so we augmented the information from the tests and created
this report.
- What is the health of the tests for each pipeline ?
- For each test, how long did the algorithm take to run ?
- What is the trend for each test run ?
- Did the algorithm find the correct answer for this test ?
- If a test failed, was it because of a incorrect result or from maximum time allowed for the test ?
- What is the history for a specific test (using Q&A) ?
- When did the last test suite fail (using Q&A) ?
the input to the algorithm, amount of time the algorithm is allowed to run, actual run time
for the algorithm, and the result provided by the algorithm.
test run information (.trx) into to an Azure blob. The files in the Azure Blob are organized
by the build id and the name of the pipeline.
and the updates the reports and dashboards.
- What is the environment for each test (cpu, memory, gpu characteristics) ?
- Integrate Azure Devops as a data source.
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