fix(tracer): only set _dd.p.ksr after agent rates are received

[bm1549]

What does this PR do?

Fixes _dd.p.ksr (Knuth Sampling Rate) to only be set on spans when the agent has provided sampling rates via readRatesJSON(). Previously, ksr was unconditionally set in prioritySampler.apply(), including when the rate was the initial client-side default (1.0) before any agent response arrived.

Also refactors prioritySampler to consolidate lock acquisitions: extracts getRateLocked() so apply() acquires ps.mu.RLock only once to read both the rate and agentRatesLoaded.

Motivation

Cross-language consistency: Python, Java, PHP, and other tracers only set ksr when actual agent rates or sampling rules are applied, not for the default fallback. This aligns Go with that behavior.

See RFC: "Transmit Knuth sampling rate to backend"

Additional Notes

• Added agentRatesLoaded bool field to prioritySampler, set to true in readRatesJSON()
• apply() now gates ksr behind agentRatesLoaded check
• Extracted getRateLocked() to avoid double lock acquisition in apply()
• Rule-based sampling path (applyTraceRuleSampling in span.go) unchanged — correctly always sets ksr
• Tests added: ksr-not-set-without-agent-rates and ksr-set-after-agent-rates-received

Related PRs across tracers:

• Java: Add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-java#10802
• .NET: Add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-dotnet#8287
• Ruby: Add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-rb#5436
• Node.js: Add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-js#7741
• PHP: Add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-php#3701
• Rust: feat: add _dd.p.ksr propagated tag for Knuth sampling rate dd-trace-rs#180
• C++: fix: _dd.p.ksr formatting to use 6 significant digits without trailing zeros dd-trace-cpp#288
• System tests: Activate _dd.p.ksr tests for all languages system-tests#6466

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.

Unsure? Have a question? Request a review!

🤖 Generated with Claude Code

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 59.98%. Comparing base (c1389f4) to head (2b0e03a).

Additional details and impacted files

Files with missing lines	Coverage Δ
ddtrace/tracer/sampler.go	94.04% <100.00%> (+0.37%)	⬆️

... and 259 files with indirect coverage changes

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[datadog-prod-us1-6]

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 59.39% (+3.63%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: cfbe029 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-03-19 20:28:20

Comparing candidate commit cfbe029 in PR branch brian.marks/fix-ksr-default with baseline commit 2d3b985 in branch main.

Found 10 performance improvements and 0 performance regressions! Performance is the same for 146 metrics, 8 unstable metrics.

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 ----------------------------------'

scenario:BenchmarkOTelApiWithCustomTags/datadog_otel_api-25

• 🟩 allocated_mem [-440 bytes; -431 bytes] or [-11.585%; -11.346%]
• 🟩 allocations [-1; -1] or [-3.704%; -3.704%]
• 🟩 execution_time [-156.030ns; -121.570ns] or [-3.850%; -3.000%]

scenario:BenchmarkOTelApiWithCustomTags/otel_api-25

• 🟩 allocated_mem [-433 bytes; -418 bytes] or [-8.454%; -8.163%]
• 🟩 allocations [-1; -1] or [-2.381%; -2.381%]
• 🟩 execution_time [-148.877ns; -124.923ns] or [-2.637%; -2.213%]

scenario:BenchmarkStartSpanConfig/scenario_WithStartSpanConfig-25

• 🟩 allocations [-1; -1] or [-5.263%; -5.263%]
• 🟩 execution_time [-158.308ns; -144.492ns] or [-6.214%; -5.672%]

scenario:BenchmarkStartSpanConfig/scenario_none-25

• 🟩 allocations [-1; -1] or [-4.762%; -4.762%]
• 🟩 execution_time [-164.156ns; -148.244ns] or [-6.098%; -5.507%]

[hannahkm]

Can we resolve the conflicts with main? There's been some changes to the sampling rate functions since you last pulled.

[genesor]

Looks great, one comment about lock

[genesor]

We're now getting the locking twice in this PR.

We could acquire the lock in this function get the rate and the loaded state in the same lock and release it.

Adding a function getRateLocked would help us do that (leveraging the /internal/locking/assert package)

func (ps *prioritySampler) getRate(spn *Span) float64 {
	ps.mu.RLock()
	defer ps.mu.RUnlock()
	return ps.getRateLocked()
}

func (ps *prioritySampler) getRateLocked(spn *Span) float64 {
	assert.RWMutexLocked(&ps.mu)
	key := serviceEnvKey{service: spn.service, env: spn.meta[ext.Environment]}
	if rate, ok := ps.rates[key]; ok {
		return rate
	}
	return ps.defaultRate
}

func (ps *prioritySampler) apply(spn *Span) {
	ps.mu.RLock()
	rate := ps.getRateLocked(spn)
	loaded := ps.agentRatesLoaded
	ps.mu.RUnlock()
...

[mtoffl01]

Left some improvements otherwise LGTM