ci: dogfood ddtest across riot test suites

[gnufede]

Summary

Extend ddtest dogfooding from the standalone internal pilot to opt-in riot test suites while preserving the existing two-stage plan/run CI design.

The generated GitLab pipeline now discovers each matching riot venv, creates one plan job per suite that loops over its venv hashes, and fans out run jobs by venv and CI node. The jobs reuse the prebuilt base venvs and a shared ddtest build artifact.

Implementation

• Add ddtest: true suite metadata for the selected suites and validate that every matching riot venv declares DDTEST_TESTS_LOCATION.
• Teach gen_gitlab_config.py to collect riot hashes, Python versions, test locations, and ddtest-specific pytest options, then emit the corresponding plan/run matrices.
• Use Riot's run --command override to prepare and execute each selected venv, removing the custom scripts/ddtest-riot.py bridge and its manual environment reconstruction.
• Preserve coverage handling, snapshot test-agent routing, CI Visibility options, and existing legacy Riot commands.

No ddtest source changes are included.

Testing

• Generated the complete GitLab CI configuration successfully.
• Passed the targeted generator tests (11 passed).
• Passed formatting/style, Riot, suitespec, spelling, shell syntax, and CI dependency validation checks.

Risks

• The new path is opt-in through suitespec metadata; legacy riot jobs remain unchanged.
• CI behavior depends on the generated configuration and the shared build artifacts; failures remain visible per suite and venv.

Additional Notes

The implementation intentionally avoids per-venv base-venv rebuilds and keeps ddtest's plan/run responsibilities separate from Riot's venv lifecycle management.

[cit-pr-commenter-54b7da]

Codeowners resolved as

Resolved from the full PR diff against main using the target branch CODEOWNERS file.
CODEOWNERS team requests not listed below are not required by the current file set.

No remaining files require a CODEOWNERS review.

[cit-pr-commenter-54b7da]

Circular import analysis

⚠️ Existing circular imports

There are 3 circular imports that already exist on the base branch and have not been changed by this PR.

ddtrace.errortracking._handled_exceptions.bytecode_injector -> ddtrace.errortracking._handled_exceptions.callbacks -> ddtrace.errortracking._handled_exceptions.collector -> ddtrace.errortracking._handled_exceptions.bytecode_reporting -> ddtrace.errortracking._handled_exceptions.bytecode_injector
ddtrace.llmobs -> ddtrace.llmobs._evaluators -> ddtrace.llmobs._evaluators.format -> ddtrace.llmobs._experiment -> ddtrace.llmobs
ddtrace.appsec._asm_request_context -> ddtrace.appsec._iast._iast_request_context_base -> ddtrace.appsec._iast._iast_env -> ddtrace.appsec._iast.reporter -> ddtrace.appsec._exploit_prevention.stack_traces -> ddtrace.appsec._asm_request_context

[cit-pr-commenter-54b7da]

Dependency direction analysis

⚠️ Existing dependency direction violations

There are 230 dependency direction violations that already exist on the base branch and have not been changed by this PR.

Show existing violations (showing 5 of 230 highest severity)

ddtrace.internal.tracemethods -×-> ddtrace.trace  (internal-core -> product:tracing, score=134)
ddtrace.debugging._signal.tracing -×-> ddtrace.trace  (product:debugging -> product:tracing, score=132)
ddtrace.llmobs._evaluators.runner -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=132)
ddtrace.llmobs._integrations.openai -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=132)
ddtrace.llmobs._integrations.mcp -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=132)

To see all violations, download the layers-base.json and layers-pr.json artifacts from this CI job and run:

uv run --script scripts/import-analysis/layers.py compare layers-base.json layers-pr.json

[datadog-official]

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 49780db | Docs | View more details | Give us feedback!}

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-09-03 14:35:21

Comparing candidate commit 49780db in PR branch gnufede/ddtest-dogfooding with baseline commit 8a2c6be in branch main.

📊 Benchmarking dashboard

Found 0 performance improvements and 6 performance regressions! Performance is the same for 580 metrics, 10 unstable metrics, 2 known flaky benchmarks, 16 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 ----------------------------------'

scenario:httppropagationextract-tracecontext_headers

• 🟥 execution_time [+2.387µs; +2.661µs] or [+7.147%; +7.966%]

scenario:httppropagationinject-ids_only

• 🟥 execution_time [+2.259µs; +2.395µs] or [+13.411%; +14.216%]

scenario:iastaspects-rstrip_aspect

• 🟥 execution_time [+83.045µs; +92.948µs] or [+22.085%; +24.719%]

scenario:iastaspectsospath-ospathbasename_aspect

• 🟥 execution_time [+107.861µs; +115.036µs] or [+27.062%; +28.862%]

scenario:telemetryaddmetric-1-count-metric-1-times

• 🟥 execution_time [+507.689ns; +541.012ns] or [+18.514%; +19.729%]

scenario:tracer-small

• 🟥 execution_time [+37.834µs; +39.670µs] or [+11.526%; +12.085%]

Unstable benchmarks

These benchmarks have a confidence interval too wide to call a change; treat them as noise rather than signal.

scenario:coreapiscenario-context_with_data_listeners

• unstable execution_time [-816.511ns; +661.164ns] or [-7.360%; +5.960%]

scenario:coreapiscenario-core_dispatch_1_listener

• unstable execution_time [-35.445ns; +30.622ns] or [-5.797%; +5.008%]

scenario:coreapiscenario-core_dispatch_50_listeners

• unstable execution_time [-1682.628ns; +1618.047ns] or [-9.887%; +9.507%]

scenario:coreapiscenario-core_dispatch_exception_listeners

• unstable execution_time [-1174.391ns; +1303.575ns] or [-9.074%; +10.072%]

scenario:coreapiscenario-core_dispatch_listeners

• unstable execution_time [-335.789ns; +313.389ns] or [-9.152%; +8.542%]

scenario:coreapiscenario-core_dispatch_no_args_listeners

• unstable execution_time [-297.237ns; +213.138ns] or [-10.133%; +7.266%]

scenario:coreapiscenario-core_dispatch_with_results_1_listener

• unstable execution_time [-159.648ns; -14.936ns] or [-13.235%; -1.238%]

scenario:coreapiscenario-core_dispatch_with_results_50_listeners

• unstable execution_time [-3660.788ns; +4370.953ns] or [-8.969%; +10.709%]

scenario:coreapiscenario-core_dispatch_with_results_listeners

• unstable execution_time [-742.674ns; +801.040ns] or [-9.176%; +9.897%]

scenario:packagesupdateimporteddependencies-import_many_stdlib_cached

• unstable execution_time [-55722.813ns; +54647.417ns] or [-9.659%; +9.473%]

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.

scenario:iastaspects-swapcase_aspect

• 🟥 execution_time [+46.002µs; +53.179µs] or [+16.734%; +19.345%]

scenario:span-start

• 🟥 execution_time [+1.413ms; +1.575ms] or [+9.925%; +11.069%]

Known flaky benchmarks without significant changes:

• scenario:errortrackingflasksqli-baseline
• scenario:flasksimple-iast-get
• scenario:iastaspects-casefold_aspect
• scenario:iastaspects-casefold_noaspect
• scenario:iastaspects-index_aspect
• scenario:iastaspects-ljust_noaspect
• scenario:iastaspects-lower_aspect
• scenario:iastaspects-replace_aspect
• scenario:iastaspects-title_noaspect
• scenario:iastaspects-translate_aspect
• scenario:iastaspects-translate_noaspect
• scenario:iastaspects-upper_noaspect
• scenario:packagespackageforrootmodulemapping-cache_off
• scenario:packagespackageforrootmodulemapping-cache_on
• scenario:sethttpmeta-all-enabled
• scenario:telemetryaddmetric-record-100-metrics

[gnufede]

@DataDog review

[datadog-official]

The ddtest switch does not keep each suite's discovery path or pytest selection. Matrix needs also combine plan artifacts from unrelated riot hashes, so some new jobs can skip required tests or use a plan for another environment.

_{Open Bits AI session}

_{🤖 Datadog Autotest · Commit 0f9bff1 · What is Autotest? · @DataDog review to ask questions · Any feedback? Reach out in #autotest}

[gnufede]

@DataDog review

[datadog-official]

More details

The specialist candidate refers to a file that this PR does not change. The effective three-dot diff has no reportable finding.

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[gnufede]

/merge -f --reason "merge queue failing on unrelated jobs"

[gh-worker-devflow-routing-ef8351]

View all feedbacks in Devflow UI.

2026-09-03 15:49:51 UTC ℹ️ Start processing command /merge -f --reason "merge queue failing on unrelated jobs"

---

2026-09-03 15:49:54 UTC ❌ MergeQueue

PR already in the queue with status in_progress

[gnufede]

/merge -f --reason "merge queue failing on unrelated jobs"

[gh-worker-devflow-routing-ef8351]

View all feedbacks in Devflow UI.

2026-09-03 15:50:48 UTC ℹ️ Start processing command /merge -f --reason "merge queue failing on unrelated jobs"

---

2026-09-03 15:50:54 UTC ℹ️ MergeQueue: pull request added to the queue

The expected merge time in main is approximately 0s (p90).

---

2026-09-03 15:51:04 UTC ℹ️ MergeQueue: This merge request was merged

Warning

This change was merged without running any pre merge CI checks

Reason: merge queue failing on unrelated jobs