feat(ci): pilot native Datadog test instrumentation

[darccio]

What does this PR do?

Tightens Datadog CI test uploads and adds a native Test Optimization pilot in one workflow lane.

Summary

Improve reliability and signal quality of Datadog CI test data by narrowing JUnit upload scope, fixing inconsistent tags, and introducing a low-risk native instrumentation pilot while keeping the existing JUnit upload path as fallback.

Changes

• Updated .github/workflows/multios-unit-tests.yml to:
  • write JUnit output into a dedicated /tmp/test-results directory
  • create the test-results directory before running tests
  • upload only ${{ env.TEST_RESULT_PATH }} to Datadog instead of scanning ./
  • add a pilot Datadog native instrumentation step (datadog/test-visibility-github-action@v2) right before the test step for ubuntu-latest runs when API key credentials are available
  • set JOB_ID: ${{ job.check_run_id }} on the test step for native instrumentation correlation
• Updated .github/workflows/appsec.yml (AppSec disabled job) to send go:stable instead of an empty go: tag when uploading JUnit results.
• Kept existing datadog-ci junit upload-based reporting in place during the pilot to avoid regressions and allow comparison.

Motivation

Current uploads included weak points:

• multios-unit-tests used path: ./, which is broader than necessary and can pick up unrelated files.
• One AppSec workflow branch emitted an empty go: tag, reducing Datadog filtering/grouping quality.
• CI data was JUnit-upload only for this workflow, which can still show the “Unlock Advanced Features with Native Instrumentation” banner.

This change keeps uploads focused, normalizes tags, and starts a controlled native instrumentation rollout for one lane.

Testing

• Ran make lint/action successfully after each workflow edit set.
• Verified workflow diffs remain scoped to Datadog test upload and pilot instrumentation behavior in:
  • .github/workflows/multios-unit-tests.yml
  • .github/workflows/appsec.yml

Reviewer's Checklist

• Changed code has unit tests for its functionality at or near 100% coverage.
• System-Tests covering this feature have been added and enabled with the va.b.c-dev version tag.
• There is a benchmark for any new code, or changes to existing code.
• If this interacts with the agent in a new way, a system test has been added.
• New code is free of linting errors. You can check this by running make lint locally.
• New code doesn't break existing tests. You can check this by running make test locally.
• Add an appropriate team label so this PR gets put in the right place for the release notes.
• All generated files are up to date. You can check this by running make generate locally.
• Non-trivial go.mod changes, e.g. adding new modules, are reviewed by @DataDog/dd-trace-go-guild. Make sure all nested modules are up to date by running make fix-modules locally.

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Bits Code status: ✅ Done

CI Auto-fix: Disabled | Enable

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⚠️ Warnings

🚦 3 Pipeline jobs failed

Pull Request Tests | multios-unit-tests (ubuntu-latest, 1.25) / test-multi-os-instrumented     

Pull Request Tests | multios-unit-tests (ubuntu-latest, 1.26) / test-multi-os-instrumented     

Check Pull Request CI Status | all-jobs-are-green     

ℹ️ Info

No other issues found (see more)

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 62.76% (+10.56%)

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Benchmarks

Benchmark execution time: 2026-06-29 16:09:08

Comparing candidate commit 084643d in PR branch dd/ci/tighten-dd-test-upload-paths with baseline commit 20e44bc in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 321 metrics, 2 unstable metrics, 1 flaky benchmarks without significant changes.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

Known flaky benchmarks

These benchmarks are marked as flaky and will not trigger a failure. Modify FLAKY_BENCHMARKS_REGEX to control which benchmarks are marked as flaky.

Known flaky benchmarks without significant changes:

• scenario:BenchmarkOTLPTraceWriterFlush

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