[Logging] Add fuzz-related logs context to corpus pruning task #4774
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| if self == LogContextType.FUZZ: | ||
| try: | ||
| return FuzzLogStruct( | ||
| fuzzer=log_contexts.meta.get('fuzzer_name', 'null'), |
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WHy not return None instead of "null"?
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I'm not entirely sure how the gcp logging treats fields that are set to None, my guess is that it omits that field. IMO it's better to have this default value meaning that the information is missing/not applicable than omitting it, which could mean that something went wrong during logging.
( I also used this piece of code as reference: https://github.com/google/clusterfuzz/blob/master/src/clusterfuzz/_internal/metrics/logs.py#L420 )
| }, | ||
| }) | ||
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| def test_fuzz_logs_context(self): |
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This tests the log being emited within the log context. We do not have integration tests that go through pre/main/postprocess though, so we are not testing the actual task execution flow here.
Can we get some evidence of this running on a candidate release of some sort, to make sure nothing weird happens and we actually get the logs?
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Yeah, we have this gap of integration tests that hinders our testing capabilities for these kind of changes.
I will do a onebox deployment with candidate and paste the logs here.
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I executed the task preprocess stage locally and pasted the logs in the PR description (tyvm for the help on how to do this @vitorguidi 🤝)
Description
Differently from the tasks instrumented with logs context so far, corpus pruning (and fuzz task) is not based on a testcase. These two in particular operate on top of fuzzers, jobs and fuzz targets. This PR:
Tests
Since corpus pruning runs on batch, a onebox deployment with candidate was not viable. Thus, the test was done by running the task's preprocess locally with the debugger and sending the logs to GCP. Evidence from the logs:
