[ABLD-387] bazelify proto generation: trace/idx

[rdesgroppes]

What does this PR do?

• migrate pkg/proto/datadog/trace from gazelle-excluded to gazelle-managed with:
  • proto_library + go_proto_library (standard),
  • write_pb_go in pkg/proto/pbgo/trace/idx: keeps span.pb.go and tracer_payload.pb.go in sync with the proto-generated output,
• add # gazelle:resolve in the root BUILD.bazel to disambiguate idx_go_proto (importpath = full module path) from the existing go_library in pkg/proto/pbgo/trace/idx,
• add # gazelle:write_pb_go off to pkg/proto/pbgo/trace to defer its write_pb_go until protoc-go-inject-tag and msgp can be plugged into //pkg/proto/datadog/trace:trace_go_proto,
• move trace/idx out of PROTO_PKGS in tasks/protobuf.py, delegating .pb.go generation to the topmost bazel command: bazel run //pkg/proto/pbgo/trace/idx:write_pb_go (left for didactic purposes).

Motivation

Enable bazel to verify that the committed span.pb.go and tracer_payload.pb.go in trace/idx stay in sync with their proto source, using the write_pb_go adapter introduced in #49770.

See precedent partially established by #49918 (languagedetection, partially because it missed the corresponding protobuf.py change - addressed by #50394).

Describe how you validated your changes

• bazel run //:gazelle produced no new warnings (stable),
• bazel test //pkg/proto/pbgo/trace/idx:write_pb_go_tests passes,
• dda inv protobuf.generate succeeds.

Additional Notes

The main trace/ package is deferred because its .pb.go files are post-processed by protoc-go-inject-tag and msgp, not yet wired into bazel.

[datadog-datadog-prod-us1]

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 50.26% (+0.00%)

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

The usual bazel style is one proto_library per .proto file.
My limited research says we could get that by adding # gazelle:proto file to make that happen.
Is there a specific reason we are not doing that?

[dd-octo-sts]

Files inventory check summary

File checks results against ancestor 762b1e43:

Results for datadog-agent_7.80.0~devel.git.517.d78350b.pipeline.111763570-1_amd64.deb:

No change detected

[rdesgroppes]

The usual bazel style is one proto_library per .proto file.

@aiuto you're right that the current state of affairs doesn't match a canonical bazel/gazelle/rules_go repo.

My limited research says we could get that by adding # gazelle:proto file to make that happen. Is there a specific reason we are not doing that?

Yes: to support the existing workflow, by adhering to the current structure: no file is moved (unless strictly necessary), gazelle directives are adjusted as per the de facto layout.
We'll of course revisit that once fully migrated to bazel.

[dd-octo-sts]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 762b1e4
📊 Static Quality Gates Dashboard
🔗 SQG Job

33 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	742.253 MiB
✅	agent_deb_amd64_fips	700.315 MiB
✅	agent_heroku_amd64	309.178 MiB
✅	agent_msi	608.038 MiB
✅	agent_rpm_amd64	742.236 MiB
✅	agent_rpm_amd64_fips	700.299 MiB
✅	agent_rpm_arm64	720.158 MiB
✅	agent_rpm_arm64_fips	681.323 MiB
✅	agent_suse_amd64	742.236 MiB
✅	agent_suse_amd64_fips	700.299 MiB
✅	agent_suse_arm64	720.158 MiB
✅	agent_suse_arm64_fips	681.323 MiB
✅	docker_agent_amd64	802.491 MiB
✅	docker_agent_arm64	805.257 MiB
✅	docker_agent_jmx_amd64	993.411 MiB
✅	docker_agent_jmx_arm64	984.955 MiB
✅	docker_cluster_agent_amd64	206.607 MiB
✅	docker_cluster_agent_arm64	220.634 MiB
✅	docker_cws_instrumentation_amd64	7.142 MiB
✅	docker_cws_instrumentation_arm64	6.689 MiB
✅	docker_host_profiler_amd64	301.579 MiB
✅	docker_host_profiler_arm64	313.059 MiB
✅	docker_dogstatsd_amd64	39.496 MiB
✅	docker_dogstatsd_arm64	37.690 MiB
✅	dogstatsd_deb_amd64	30.149 MiB
✅	dogstatsd_deb_arm64	28.279 MiB
✅	dogstatsd_rpm_amd64	30.149 MiB
✅	dogstatsd_suse_amd64	30.149 MiB
✅	iot_agent_deb_amd64	44.462 MiB
✅	iot_agent_deb_arm64	41.442 MiB
✅	iot_agent_deb_armhf	42.183 MiB
✅	iot_agent_rpm_amd64	44.462 MiB
✅	iot_agent_suse_amd64	44.462 MiB

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 862a1a2d-3b17-4529-bbd4-10573c4e2a52

Baseline: 575c384
Comparison: a00f465
Diff

Optimization Goals: ✅ No significant changes detected

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	docker_containers_cpu	% cpu utilization	-2.36	[-5.23, +0.51]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+1.91	[+0.93, +2.89]	1	Logs bounds checks dashboard
➖	ddot_metrics_sum_cumulative	memory utilization	+0.77	[+0.61, +0.93]	1	Logs
➖	otlp_ingest_logs	memory utilization	+0.69	[+0.59, +0.79]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.55	[+0.34, +0.76]	1	Logs
➖	quality_gate_security_idle	memory utilization	+0.37	[+0.29, +0.44]	1	Logs bounds checks dashboard
➖	otlp_ingest_metrics	memory utilization	+0.35	[+0.19, +0.51]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	+0.33	[+0.10, +0.57]	1	Logs
➖	quality_gate_security_no_fs_load	memory utilization	+0.23	[+0.11, +0.34]	1	Logs bounds checks dashboard
➖	quality_gate_security_mean_fs_load	memory utilization	+0.18	[+0.14, +0.22]	1	Logs bounds checks dashboard
➖	quality_gate_metrics_logs	memory utilization	+0.16	[-0.09, +0.40]	1	Logs bounds checks dashboard
➖	file_to_blackhole_100ms_latency	egress throughput	+0.05	[-0.09, +0.18]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.02	[-0.39, +0.43]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	+0.00	[-0.20, +0.21]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.09, +0.09]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.01	[-0.20, +0.19]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.01	[-0.45, +0.42]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-0.04	[-0.09, +0.02]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.07	[-0.61, +0.47]	1	Logs
➖	ddot_logs	memory utilization	-0.19	[-0.26, -0.12]	1	Logs
➖	quality_gate_idle	memory utilization	-0.26	[-0.30, -0.21]	1	Logs bounds checks dashboard
➖	ddot_metrics	memory utilization	-0.27	[-0.46, -0.08]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.29	[-0.34, -0.25]	1	Logs bounds checks dashboard
➖	ddot_metrics_sum_delta	memory utilization	-0.34	[-0.52, -0.16]	1	Logs
➖	docker_containers_memory	memory utilization	-0.50	[-0.59, -0.40]	1	Logs
➖	docker_containers_cpu	% cpu utilization	-2.36	[-5.23, +0.51]	1	Logs

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	docker_containers_cpu	simple_check_run	10/10	707 ≥ 26
✅	docker_containers_memory	memory_usage	10/10	243.17MiB ≤ 370MiB
✅	docker_containers_memory	simple_check_run	10/10	686 ≥ 26
✅	file_to_blackhole_0ms_latency	memory_usage	10/10	0.16GiB ≤ 1.20GiB
✅	file_to_blackhole_0ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10	0.21GiB ≤ 1.20GiB
✅	file_to_blackhole_1000ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_100ms_latency	memory_usage	10/10	0.17GiB ≤ 1.20GiB
✅	file_to_blackhole_100ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_500ms_latency	memory_usage	10/10	0.18GiB ≤ 1.20GiB
✅	file_to_blackhole_500ms_latency	missed_bytes	10/10	0B = 0B
✅	quality_gate_idle	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	140.88MiB ≤ 147MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 ≤ 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	468.93MiB ≤ 495MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	4 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	177.15MiB ≤ 195MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	352.47 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	4 ≤ 6	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	373.29MiB ≤ 430MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	24.94 ≤ 40	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	291.12MiB ≤ 330MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	54.32 ≤ 70	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	267.43MiB ≤ 320MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	22.56 ≤ 40	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	294.30MiB ≤ 320MiB	bounds checks dashboard

Explanation

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

• quality_gate_security_mean_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_mean_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
• quality_gate_security_no_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
• quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.