feat(openfeature): support immediate per-subject experimentation opt-out by leoromanovsky · Pull Request #21112 · DataDog/dd-trace-py

leoromanovsky · 2026-10-20T03:24:46Z

Motivation

Customers need to exclude selected subjects from experimentation without blocking ordinary feature delivery.

Changes and Decisions

Add DD_FEATURE_FLAGS_EXPERIMENTATION_OPT_OUT_MODE, defaulting to disabled. Explicit provider configuration takes precedence.
In immediate mode, validate the subject's timestamp and skip experiment allocations before targeting. Continue through ordinary allocations.
Return the application default with INVALID_CONTEXT for invalid timestamps. Keep evaluation telemetry and exposure deduplication unchanged.
Use the shared Rust evaluator's existing allocation timestamp parser and the merged fixture capability contract.
Preserve invalid object and array opt-out attributes at the native boundary without changing the customer's context.

export DD_FEATURE_FLAGS_EXPERIMENTATION_OPT_OUT_MODE=immediate

from ddtrace.openfeature import DataDogProvider
from openfeature import api
from openfeature.evaluation_context import EvaluationContext

api.set_provider(DataDogProvider())
attributes = {}
if athlete.experimentation_opt_out_at is not None:
    attributes["dd_experimentation_opt_out_at"] = (
        athlete.experimentation_opt_out_at.isoformat()
    )
enabled = api.get_client().get_boolean_value(
    "new-route-planner",
    False,
    EvaluationContext(targeting_key=athlete.id, attributes=attributes),
)

The timestamp must include its time zone. A future timestamp also takes effect immediately.

Dependency: The shared libdatadog evaluator change must land and receive an approved dependency version before this draft can merge. This draft pins DataDog/libdatadog@020004781291bd9178cd91868f53291bfed550f7.

Validation

Tested commit	Validation	Result
`DataDog/dd-trace-py@ac6a36954750d31fb423d42d562200797b8db865`	System tests: environment modes, ordinary fallback, invalid-context defaults, and exposure deduplication; Linux/arm64	Not rerun. Local Docker storage reports filesystem I/O errors. The new object/array provider tests have not run locally.
`DataDog/dd-trace-py@f460cd9276f220d1c4f33cf36b6472c87bfc84dc`	Previous-head system tests: environment modes, ordinary fallback, invalid-context defaults, and exposure deduplication; Linux/arm64	3/3 passed. This does not validate the current head. Evaluation-event delivery was not validated.

FFE reviewer selection

Reviewers: @vjfridge, @btthomas

Why: server py — Adds a per-subject experimentation opt-out mode to the Python OpenFeature provider. Reviewers come from the matched pod.

_{🤖 Automated selection.}

Selection details

Initiative: fallback / server-py

Why this match: Adds a per-subject experimentation opt-out mode to the Python OpenFeature provider. In immediate mode it validates dd_experimentation_opt_out_at, skips experiment allocations and returns INVALID_CONTEXT for invalid timestamps. It does not suppress evaluation or exposure events: the PR keeps telemetry and exposure deduplication unchanged, so ufc-compliance does not fit. It adds no layers, mutual exclusion, holdouts or bandits. No catalog project matches this behavior, so it falls to the Python Feature Flags/OpenFeature subject pod.

@vjfridge — primary (server-python): Matched pod member. Review requested.
@btthomas — floating (server-python): Coverage and knowledge sharing. Review requested.

The PR author was excluded. Existing reviewers and teams were preserved.

Debug or fix a problem

Workflow run · Bits Code session

Wrong project or pod? Clarify this PR’s purpose, or correct the reviewer registry and publish the change. Sheet edits take effect after publication.
Need another reviewer now? Request them in GitHub. This workflow only adds requests and keeps existing reviewers.
Stuck beyond five minutes or failed? Inspect the run’s failed step and available Bits session. After fixing the cause, rerun the workflow with this PR URL and dry_run=false. Unchanged completed runs are skipped. If the receipt says needs_reconciliation or a write outcome is uncertain, ask the workflow owner to reconcile GitHub and the receipt before retrying; do not delete the lock blindly.
Report a problem: Comment on the reviewer-routing skill PR with this PR URL, the workflow run link, and the expected initiative or reviewer correction.

Evidence and run details

✅ Complete — reviewer coverage verified. The workflow checked pending requests or submitted reviews on the evaluated head.

Generated asynchronously by the FFE reviewer-routing workflow.

Changed paths: ddtrace/internal/openfeature/_experimentation_opt_out.py, ddtrace/internal/openfeature/_provider.py, ddtrace/internal/openfeature/_native.py, ddtrace/internal/settings/openfeature.py, ddtrace/openfeature/__init__.py, tests/openfeature/test_experimentation_opt_out.py, tests/openfeature/test_provider_fixtures.py

Evaluated head: ac6a36954750d31fb423d42d562200797b8db865

Registry revision: revision:1946aa2a-530e-487a-84a7-83aff44a1089

Pinned skill source: d214cfc65ae154b97d39af5cf32caf48aaec9bf0

Instructions: workflow-injected snapshot (no plugin loaded)

Instruction snapshot SHA-256: f23b2a88c13c0da90e2dd58246a14f257af91e2195c555039bd555b52e6f3516

cit-pr-commenter-54b7da · 2026-10-20T03:26:17Z

Dependency direction analysis

⚠️ Existing dependency direction violations

There are 135 dependency direction violations that already exist on the base branch and have not been changed by this PR.

Show existing violations (showing 5 of 135 highest severity)

ddtrace.internal.tracemethods -×-> ddtrace.trace  (internal-core -> product:tracing, score=121)
ddtrace.llmobs._integrations.langgraph -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=119)
ddtrace.llmobs._integrations.litellm -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=119)
ddtrace.llmobs._integrations.bedrock_agents -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=119)
ddtrace.llmobs._integrations.bedrock -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=119)

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

cit-pr-commenter-54b7da · 2026-10-20T03:26:23Z

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.

ddtrace/internal/native/_native.pyi                                     @DataDog/apm-core-python
ddtrace/internal/openfeature/_experimentation_opt_out.py                @DataDog/feature-flagging-and-experimentation-sdk
ddtrace/internal/openfeature/_native.py                                 @DataDog/feature-flagging-and-experimentation-sdk
ddtrace/internal/openfeature/_provider.py                               @DataDog/feature-flagging-and-experimentation-sdk
ddtrace/internal/settings/_supported_configurations.py                  @DataDog/apm-python
ddtrace/internal/settings/openfeature.py                                @DataDog/feature-flagging-and-experimentation-sdk
ddtrace/openfeature/__init__.py                                         @DataDog/feature-flagging-and-experimentation-sdk
docs/configuration.rst                                                  @DataDog/python-guild
releasenotes/notes/feature-flags-experimentation-opt-out-549474088d1582eb.yaml  @DataDog/apm-python
src/native/Cargo.lock                                                   @DataDog/apm-core-python
src/native/Cargo.toml                                                   @DataDog/apm-core-python
src/native/ffe.rs                                                       @DataDog/feature-flagging-and-experimentation-sdk
supported-configurations.json                                           @DataDog/apm-python
tests/openfeature/ffe-system-test-data/SOURCE.md                        @DataDog/feature-flagging-and-experimentation-sdk
tests/openfeature/ffe-system-test-data/evaluation-cases/test-case-experimentation-opt-out.json  @DataDog/feature-flagging-and-experimentation-sdk
tests/openfeature/test_experimentation_opt_out.py                       @DataDog/feature-flagging-and-experimentation-sdk
tests/openfeature/test_provider_fixtures.py                             @DataDog/feature-flagging-and-experimentation-sdk

pr-commenter · 2026-10-20T03:57:24Z

Benchmarks

Benchmark execution time: 2026-10-20 22:49:26

Comparing candidate commit ac6a369 in PR branch leoromanovsky/experimentation-opt-out-immediate with baseline commit ef12f0a in branch main.

📊 Benchmarking dashboard

Found 0 performance improvements and 8 performance regressions! Performance is the same for 543 metrics, 10 unstable metrics, 6 known flaky benchmarks, 18 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 [+3.158µs; +3.396µs] or [+10.094%; +10.855%]

scenario:iastaspects-add_aspect

🟥 execution_time [+10.169µs; +11.952µs] or [+11.373%; +13.366%]

scenario:iastaspects-capitalize_noaspect

🟥 execution_time [+36.884µs; +41.521µs] or [+19.276%; +21.699%]

scenario:iastaspects-ljust_aspect

🟥 execution_time [+147.169µs; +152.879µs] or [+30.311%; +31.488%]

scenario:iastaspectsremodule-re_expand_aspect

🟥 execution_time [+96.877µs; +103.759µs] or [+15.592%; +16.699%]

scenario:msgpackencoderscenario-simple_one_span

🟥 execution_time [+345.504ns; +431.268ns] or [+8.632%; +10.774%]

scenario:otelspan-start

🟥 execution_time [+2.447ms; +3.309ms] or [+9.280%; +12.546%]

scenario:recursivecomputation-shallow

🟥 execution_time [+51.217µs; +54.833µs] or [+7.380%; +7.901%]

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 [-689.545ns; +785.486ns] or [-6.464%; +7.363%]

scenario:coreapiscenario-core_dispatch_1_listener

unstable execution_time [-38.022ns; +39.792ns] or [-5.582%; +5.842%]

scenario:coreapiscenario-core_dispatch_50_listeners

unstable execution_time [-1847.358ns; +1985.131ns] or [-9.285%; +9.977%]

scenario:coreapiscenario-core_dispatch_exception_listeners

unstable execution_time [-1850.048ns; +2125.408ns] or [-9.578%; +11.004%]

scenario:coreapiscenario-core_dispatch_listeners

unstable execution_time [-350.737ns; +408.033ns] or [-8.227%; +9.571%]

scenario:coreapiscenario-core_dispatch_no_args_listeners

unstable execution_time [-232.954ns; +226.117ns] or [-8.640%; +8.386%]

scenario:coreapiscenario-core_dispatch_with_results_1_listener

unstable execution_time [-42.287ns; +153.629ns] or [-3.025%; +10.992%]

scenario:coreapiscenario-core_dispatch_with_results_50_listeners

unstable execution_time [-4347.049ns; +5335.444ns] or [-8.748%; +10.736%]

scenario:coreapiscenario-core_dispatch_with_results_listeners

unstable execution_time [-998.462ns; +951.101ns] or [-9.464%; +9.015%]

scenario:packagesupdateimporteddependencies-import_many_stdlib_cached

unstable execution_time [-54.399µs; +57.681µs] or [-9.435%; +10.005%]

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:httppropagationinject-ids_only

🟥 execution_time [+2.500µs; +2.653µs] or [+18.239%; +19.354%]

scenario:iastaspectsospath-ospathbasename_aspect

🟥 execution_time [+134.232µs; +139.837µs] or [+35.367%; +36.844%]

scenario:iastaspectssplit-rsplit_aspect

🟥 execution_time [+30.072µs; +33.271µs] or [+19.083%; +21.113%]

scenario:span-start

🟥 execution_time [+1.034ms; +1.328ms] or [+9.072%; +11.652%]

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

🟥 execution_time [+410.554ns; +455.593ns] or [+21.131%; +23.449%]

scenario:tracer-small

🟥 execution_time [+43.256µs; +44.727µs] or [+18.544%; +19.174%]

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-rstrip_aspect
scenario:iastaspects-swapcase_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

…entation-opt-out-immediate

datadog-prod-us1-5 · 2026-10-20T22:24:54Z

🎉 All green!

🧪 All tests passed
❄️ No new flaky tests detected

_{This comment will be updated automatically if new data arrives.

🔗 Commit SHA: ac6a369 | Docs | View more details | Give us feedback!}

chatgpt-codex-connector · 2026-10-20T22:28:55Z

Codex Review Summary

This comment shows the latest Codex review activity on this pull request.

Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-10-20T22:32:02.360199Z	`ac6a369`	Draft marked ready
🔒 Security Review	✅ Completed 2026-10-20T22:32:32.486443Z	`ac6a369`	Draft marked ready

ℹ️ About Codex in GitHub

Your team has set up Codex to review pull requests in this repo. Reviews are triggered when you

Open a pull request for review
Mark a draft as ready
Comment "@codex review" or "@codex security review".

Codex reacts with 👀 while any review is running, comments if it has suggestions, and reacts with 👍 once all reviews finish with no findings.

datadog-prod-us1-5

More details

No concrete defect was identified in configuration precedence, invalid-context handling, or ordinary-allocation fallback. Native and system runtime behavior remains unverified.

Was this helpful? React 👍 or 👎

_{Open Bits AI session}

_{🤖 Bits Code Review · Commit ac6a369}

brettlangdon

nit about keeping Cargo.toml crates all in sync on an actual libdatadog version, otherwise config/release note changes lgtm

brettlangdon · 2026-10-21T01:11:51Z

 smallvec = "1"
 tokio = "1"
-libdd-ffe = { git = "https://github.com/DataDog/libdatadog", rev = "v46.0.0", optional = true, features = ["pyo3"] }
+libdd-ffe = { git = "https://github.com/DataDog/libdatadog", rev = "020004781291bd9178cd91868f53291bfed550f7", optional = true, features = ["pyo3"] }


I'd prefer to keep this on a synced release across the other crates... if we can.

Ok I'll wait for a release.

leoromanovsky · 2026-10-29T01:21:31Z

FFE reviewer selection

Reviewers: @btthomas, @sameerank

Why: server py — Adds an immediate per-subject experimentation opt-out mode to the Python OpenFeature DataDogProvider. Reviewers come from the matched pod and the required specialist pods.

_{🤖 Automated selection.}

Selection details

Initiative: fallback / server-py

Why this match: Adds an immediate per-subject experimentation opt-out mode to the Python OpenFeature DataDogProvider. A new setting and constructor option control it. When it is on, the provider skips experiment allocations for opted-out subjects and returns INVALID_CONTEXT for invalid timestamps. Evaluation telemetry and exposure handling stay the same. Experiment-allocation eligibility is explicitly excluded from ufc-compliance, and no other registered project fits, so the Python OpenFeature SME owns this.

Why these owners: Eligible reviewers have already approved the current head; no additional reviewers are needed for the responsibilities those approvals cover.

@btthomas — floating (server-python): Coverage and knowledge sharing. Existing review coverage preserved.
@sameerank — specialist (openfeature-architecture): Additional subject expertise. Covers: openfeature-architecture. Existing review coverage preserved.

Additional review: openfeature-architecture — Changes the contract at the native evaluator boundary. The PyO3 resolve_value now takes an experimentation_opt_out_immediate option and calls the shared libdatadog eval_flag_with_options with EvaluationOptions in place of get_assignment. It maps the new EvaluationError::InvalidContext to the INVALID_CONTEXT error code. The Python wrapper now replaces invalid object or array opt-out attributes with null before they reach the native layer. Coverage: @sameerank. Evidence: src/native/ffe.rs, ddtrace/internal/openfeature/_native.py, ddtrace/internal/native/_native.pyi

The PR author was excluded. Existing reviewers and teams were preserved.

Debug or fix a problem

Workflow run · Bits Code session

Wrong project or pod? Clarify this PR’s purpose, or correct the reviewer registry and publish the change. Sheet edits take effect after publication.
Need another reviewer now? Request them in GitHub. This workflow only adds requests and keeps existing reviewers.
Stuck beyond five minutes or failed? Inspect the run’s failed step and available Bits session. After fixing the cause, rerun the workflow with this PR URL and dry_run=false. Unchanged completed runs are skipped. If the receipt says needs_reconciliation or a write outcome is uncertain, ask the workflow owner to reconcile GitHub and the receipt before retrying; do not delete the lock blindly.
Report a problem: Comment on the reviewer-routing skill PR with this PR URL, the workflow run link, and the expected initiative or reviewer correction.

Evidence and run details

✅ Complete — reviewer coverage verified. The workflow checked pending requests or submitted reviews on the evaluated head.

Generated asynchronously by the FFE reviewer-routing workflow.

Changed paths: ddtrace/internal/openfeature/_provider.py, ddtrace/internal/openfeature/_experimentation_opt_out.py, ddtrace/internal/openfeature/_native.py, ddtrace/internal/settings/openfeature.py, ddtrace/openfeature/__init__.py, tests/openfeature/test_experimentation_opt_out.py, tests/openfeature/test_provider_fixtures.py

Evaluated head: ac6a36954750d31fb423d42d562200797b8db865

Registry revision: revision:5067899c-c8bf-4370-84a0-3e0cb0c89e02

Pinned skill source: 7e3283c602f6b18a7e3e623eecb52d3a9c091a2e

Instructions: workflow-injected snapshot (no plugin loaded)

Instruction snapshot SHA-256: 52ed8cb68675dde1a47addaefe4a9500891c24014abf7dade6dfe38cf836c1d2

feat(openfeature): support immediate per-subject experimentation opt-out

f460cd9

leoromanovsky mentioned this pull request Oct 20, 2026

feat(ffe): support subject experimentation opt-out modes DataDog/libdatadog#2698

Merged

leoromanovsky added 4 commits October 20, 2026 11:07

Merge remote-tracking branch 'origin/main' into leoromanovsky/experim…

02c5887

…entation-opt-out-immediate

chore(openfeature): update native opt-out revision after main merge

82d6637

Merge remote-tracking branch 'origin/main' into leoromanovsky/experim…

a8200e7

…entation-opt-out-immediate

fix(openfeature): align immediate opt-out with canonical fixtures

ac6a369

leoromanovsky marked this pull request as ready for review October 20, 2026 22:28

leoromanovsky requested review from a team as code owners October 20, 2026 22:28

leoromanovsky requested review from Yun-Kim and brettlangdon and removed request for a team October 20, 2026 22:28

datadog-prod-us1-5 Bot reviewed Oct 20, 2026

View reviewed changes

brettlangdon approved these changes Oct 21, 2026

View reviewed changes

leoromanovsky requested review from btthomas, greghuels, sameerank and vjfridge October 27, 2026 03:39

greghuels removed their request for review October 27, 2026 10:33

btthomas approved these changes Oct 27, 2026

View reviewed changes

Conversation

leoromanovsky commented Oct 20, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Motivation

Changes and Decisions

Validation

FFE reviewer selection

Uh oh!

cit-pr-commenter-54b7da Bot commented Oct 20, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Dependency direction analysis

⚠️ Existing dependency direction violations

Uh oh!

cit-pr-commenter-54b7da Bot commented Oct 20, 2026

Codeowners resolved as

Uh oh!

pr-commenter Bot commented Oct 20, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Benchmarks

Explanation

More details about the CI and significant changes

scenario:httppropagationextract-tracecontext_headers

scenario:iastaspects-add_aspect

scenario:iastaspects-capitalize_noaspect

scenario:iastaspects-ljust_aspect

scenario:iastaspectsremodule-re_expand_aspect

scenario:msgpackencoderscenario-simple_one_span

scenario:otelspan-start

scenario:recursivecomputation-shallow

Unstable benchmarks

scenario:coreapiscenario-context_with_data_listeners

scenario:coreapiscenario-core_dispatch_1_listener

scenario:coreapiscenario-core_dispatch_50_listeners

scenario:coreapiscenario-core_dispatch_exception_listeners

scenario:coreapiscenario-core_dispatch_listeners

scenario:coreapiscenario-core_dispatch_no_args_listeners

scenario:coreapiscenario-core_dispatch_with_results_1_listener

scenario:coreapiscenario-core_dispatch_with_results_50_listeners

scenario:coreapiscenario-core_dispatch_with_results_listeners

scenario:packagesupdateimporteddependencies-import_many_stdlib_cached

Known flaky benchmarks

scenario:httppropagationinject-ids_only

scenario:iastaspectsospath-ospathbasename_aspect

scenario:iastaspectssplit-rsplit_aspect

scenario:span-start

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

scenario:tracer-small

Uh oh!

datadog-prod-us1-5 Bot commented Oct 20, 2026 • edited by datadog-prod-us1-3 Bot Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

chatgpt-codex-connector Bot commented Oct 20, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Codex Review Summary

Uh oh!

datadog-prod-us1-5 Bot left a comment

Choose a reason for hiding this comment

Uh oh!

brettlangdon left a comment

Choose a reason for hiding this comment

Uh oh!

brettlangdon Oct 21, 2026

Choose a reason for hiding this comment

Uh oh!

leoromanovsky Oct 21, 2026

Choose a reason for hiding this comment

Uh oh!

leoromanovsky commented Oct 29, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

FFE reviewer selection

Uh oh!

Reviewers

Uh oh!

Assignees

Labels

Projects

Milestone

Development

Uh oh!

3 participants

leoromanovsky commented Oct 20, 2026 •

edited

Loading

cit-pr-commenter-54b7da Bot commented Oct 20, 2026 •

edited

Loading

pr-commenter Bot commented Oct 20, 2026 •

edited

Loading

datadog-prod-us1-5 Bot commented Oct 20, 2026 •

edited by datadog-prod-us1-3 Bot

Loading

chatgpt-codex-connector Bot commented Oct 20, 2026 •

edited

Loading

leoromanovsky commented Oct 29, 2026 •

edited

Loading