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Ability to run all tests in parallel #19
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I added a fourth requirement, which will allow us to run specific tests only. This, if I had to guess, will be how we run tests most of the time. |
So, what the |
Yep, have it run |
So you'd want a machine running each of https://github.com/timberio/vector-test-harness/tree/master/cases individually? Is it because these are quite long running tests? |
Test harness uses very few resources from the host on where it's executing. I think technically using build matrices is possible here, if we decouple vector building and test harness invocation - test harness itself doesn't create a lot of load either on the CPU nor on I/O side (on the host). We can alternatively implement parallel execution at the test harness level, rather than at the test harness action level - it'll give us even more flexibility, and overall should be a better option really. |
We're sharing a XL worker pool of about 80 with the Rust project right now, and when we talked to Joe we said we'd be doing around 100-200 jobs a day.
Agreed, I note we asked them for the XL runners on Vector itself, so we could possibly run the build step there and then have the harness go do its thing on small runners. |
This ticket's concerns are superseded by our soak testing infrastructure. Parallel running is accomplished there. |
WARNING: Github has asked up explicitly not to spin up a lot of parallel jobs on large instances. This task shold use regular/small instances.
It looks like Github Actions has the ability to run jobs as a matrix (do not use large instances!). I would like to run every test case in parallel unless otherwise specified. For example:
/test
runs all tests in parallel./test -t docker_partial_events_merging_correctness
run a single test./test -t docker_partial_events_merging_correctness -t disk_buffer_performance
runs only the tests specified./test -t *_performance
runs all tests ending with_performance
.All tests are designed to be namespaced, there should be no problem running them all in parallel. I am also not concerned about resource usage or cost. If we bump into AWS limits we can request an increase.
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