otlp ingest: metrics: add infra_tags_as_tags to promote custom tags by agagniere · Pull Request #55622 · DataDog/datadog-agent

agagniere · 2026-08-29T14:54:54Z

What does this PR do?

Custom tagger-derived tags (e.g. from kubernetesResourcesLabelsAsTags / AnnotationsAsTags) are dropped from OTLP metrics ingested by the core Agent because the metrics translator keeps only an allowlist of known DD/OTel convention keys (OTELS-1131). The only existing lever, resource_attributes_as_tags, dumps ALL resource attributes (e.g. k8s.pod.uid), causing cardinality blowup.

This adds otlp_config.metrics.infra_attributes.as_tags (default false). When enabled, the infraattributes processor writes custom tags under the datadog.container.tag.<key> prefix, which the metrics translator (attributes.TagsFromAttributes -> ContainerTagsFromResourceAttributes) promotes into metric tags. This is selective: only tagger tags are promoted, no raw resource-attribute dump.

The promotion machinery is the same one the traces pipeline already uses (container_tag_promotion).
The metrics and logs pipelines share the infraattributes processor instance; the logs processor ignores this setting, so logs are unaffected.

Motivation

OTAGENT-1310, created to resolve OTELS-1131

Describe how you validated your changes

Manual tests to confirm the tags show up at the right place in the UI

Additional Notes

A complete config for user that want to capture certain labels/annotations as tags, for all 3 signals:

kubernetes_resources_labels_as_tags: '{"pods":{"foo":"my_label_foo"}}'
kubernetes_resources_annotations_as_tags: '{"pods":{"bar":"my_annotation_bar"}}'
otlp_config:
  traces:
    infra_attributes:
      container_tag_promotion: "rename"
  logs:
    infra_attributes:
      tags_as_ddtags: true
  metrics:
    infra_attributes:
      as_tags: true

…to metrics Custom tagger-derived tags (e.g. from kubernetesResourcesLabelsAsTags / AnnotationsAsTags) are dropped from OTLP metrics ingested by the core Agent because the metrics translator keeps only an allowlist of known DD/OTel convention keys (OTELS-1131). The only existing lever, resource_attributes_as_tags, dumps ALL resource attributes (e.g. k8s.pod.uid), causing cardinality blowup. This adds otlp_config.metrics.infra_attributes.infra_tags_as_tags (default false). When enabled, the infraattributes processor writes custom tags under the `datadog.container.tag.<key>` prefix, which the metrics translator (attributes.TagsFromAttributes -> ContainerTagsFromResourceAttributes) promotes into metric tags. This is selective: only tagger tags are promoted, no raw resource-attribute dump. The promotion machinery is the same one the traces pipeline already uses (container_tag_promotion). The metrics and logs pipelines share the infraattributes processor instance; the logs processor ignores infra_tags_as_tags, so logs are unaffected. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

github-actions

AI review by Codex (OpenAI) - workflow run

Patch is incorrect: the user-visible metric-tagging behavior lacks the required fakeintake E2E coverage.

github-actions · 2026-08-29T14:57:38Z

+			assert.Len(t, next.AllMetrics(), 1)
+			out := next.AllMetrics()[0].ResourceMetrics().At(0).Resource().Attributes().AsRaw()


This only verifies the processor’s resource attributes; it never exercises the metrics translator or confirms that test_tag:bar reaches intake. Add a new-e2e assertion against fakeintake, since this change specifically alters emitted metric tags and unit coverage cannot catch failures in the downstream translation/serialization path.

datadog-datadog-prod-us1 · 2026-08-29T15:16:42Z

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 52.74% (+0.01%)

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

🔗 Commit SHA: 27f3f97 | Docs | View more details | Give us feedback!}

dd-octo-sts · 2026-08-29T15:22:23Z

Files inventory check summary

File checks results against ancestor b9aea118:

Results for datadog-agent_7.84.0~devel.git.601.27f3f97.pipeline.134131766-1_amd64.deb:

No change detected

Results for datadog-iot-agent_7.84.0~devel.git.601.27f3f97.pipeline.134131766-1_amd64.deb:

No change detected

dd-octo-sts · 2026-08-29T15:30:49Z

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor b9aea11
📊 Static Quality Gates Dashboard
🔗 SQG Job

Successful checks

Info

	Quality gate	Change	Size (prev → curr → max)
✅	agent_msi	+3.01 KiB (0.00% increase, -0.02% of buffer)	648.383 → 648.385 → 661.050
✅	agent_rpm_arm64_fips	+4.74 KiB (0.00% increase, -0.40% of buffer)	693.177 → 693.182 → 694.350
✅	agent_suse_arm64_fips	+4.74 KiB (0.00% increase, -0.40% of buffer)	693.177 → 693.182 → 694.350

30 successful checks with minimal change (< 2 KiB)

	Quality gate	Current Size
✅	agent_deb_amd64	761.706 MiB
✅	agent_deb_amd64_fips	713.963 MiB
✅	agent_heroku_amd64	312.987 MiB
✅	agent_rpm_amd64	761.690 MiB
✅	agent_rpm_amd64_fips	713.947 MiB
✅	agent_rpm_arm64	737.583 MiB
✅	agent_suse_amd64	761.690 MiB
✅	agent_suse_amd64_fips	713.947 MiB
✅	agent_suse_arm64	737.583 MiB
✅	docker_agent_amd64	820.722 MiB
✅	docker_agent_arm64	821.652 MiB
✅	docker_agent_jmx_amd64	1011.635 MiB
✅	docker_agent_jmx_arm64	1001.344 MiB
✅	docker_cluster_agent_amd64	211.261 MiB
✅	docker_cluster_agent_arm64	224.398 MiB
✅	docker_cws_instrumentation_amd64	7.439 MiB
✅	docker_cws_instrumentation_arm64	6.877 MiB
✅	docker_dogstatsd_amd64	39.553 MiB
✅	docker_dogstatsd_arm64	37.623 MiB
✅	docker_host_profiler_amd64	306.871 MiB
✅	docker_host_profiler_arm64	318.166 MiB
✅	dogstatsd_deb_amd64	30.290 MiB
✅	dogstatsd_deb_arm64	28.302 MiB
✅	dogstatsd_rpm_amd64	30.290 MiB
✅	dogstatsd_suse_amd64	30.290 MiB
✅	iot_agent_deb_amd64	46.568 MiB
✅	iot_agent_deb_arm64	43.208 MiB
✅	iot_agent_deb_armhf	44.015 MiB
✅	iot_agent_rpm_amd64	46.568 MiB
✅	iot_agent_suse_amd64	46.567 MiB

cit-pr-commenter-54b7da · 2026-08-29T15:44:11Z

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Job ID: a0d1df6c-6f83-4ecc-b039-96f80bd76b63

Baseline: b9aea11
Comparison: 27f3f97
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+1.11	[+0.24, +1.99]	1	Logs bounds checks dashboard
➖	dsd_uds_10mb_3k_timestamped_contexts_cpu	% cpu utilization	+0.28	[+0.04, +0.53]	1	Logs
➖	quality_gate_private_action_runner	memory utilization	+0.09	[-0.03, +0.21]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	+0.06	[+0.02, +0.10]	1	Logs bounds checks dashboard
➖	quality_gate_idle_all_features	memory utilization	-0.05	[-0.08, -0.01]	1	Logs bounds checks dashboard
➖	quality_gate_security_mean_fs_load	memory utilization	-0.05	[-0.08, -0.02]	1	Logs bounds checks dashboard
➖	quality_gate_security_idle	memory utilization	-0.12	[-0.17, -0.07]	1	Logs bounds checks dashboard
➖	dsd_uds_10mb_3k_timestamped_contexts_memory	memory utilization	-0.22	[-0.44, +0.00]	1	Logs
➖	quality_gate_security_no_fs_load	memory utilization	-0.39	[-0.47, -0.31]	1	Logs bounds checks dashboard
➖	quality_gate_metrics_logs	memory utilization	-1.47	[-1.70, -1.24]	1	Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	quality_gate_idle	intake_connections	10/10	4 = 4	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	173.05MiB ≤ 179MiB	bounds checks dashboard
✅	quality_gate_idle	total_bytes_received	10/10	748.87KiB ≤ 819.20KiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	4 = 4	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	518.67MiB ≤ 537MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	total_bytes_received	10/10	1.14MiB ≤ 1.25MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	19 ≤ 40	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	210.95MiB ≤ 228MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_logs	total_bytes_received	10/10	263.49MiB ≤ 292MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	359.63 ≤ 2000	bounds checks dashboard
✅	quality_gate_metrics_logs	intake_connections	10/10	19 ≤ 40	bounds checks dashboard
✅	quality_gate_metrics_logs	memory_usage	10/10	416.57MiB ≤ 455MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	total_bytes_received	10/10	0.94GiB ≤ 1.04GiB	bounds checks dashboard
✅	quality_gate_private_action_runner	memory_usage	10/10	72.14MiB ≤ 75MiB	bounds checks dashboard
✅	quality_gate_security_idle	cpu_usage	10/10	37.13 ≤ 100	bounds checks dashboard
✅	quality_gate_security_idle	memory_usage	10/10	322.25MiB ≤ 355MiB	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	cpu_usage	10/10	60.91 ≤ 200	bounds checks dashboard
✅	quality_gate_security_mean_fs_load	memory_usage	10/10	303.62MiB ≤ 335MiB	bounds checks dashboard
✅	quality_gate_security_no_fs_load	cpu_usage	10/10	23.19 ≤ 100	bounds checks dashboard
✅	quality_gate_security_no_fs_load	memory_usage	10/10	313.73MiB ≤ 345MiB	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:

Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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.
Its configuration does not mark it "erratic".

CI Pass/Fail Decision

✅ Passed. All Quality Gates passed.

quality_gate_security_no_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_no_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 total_bytes_received: 10/10 replicas passed. Gate passed.
quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
quality_gate_security_mean_fs_load, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
quality_gate_security_mean_fs_load, bounds check memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_logs, bounds check total_bytes_received: 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_logs, bounds check missed_bytes: 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.
quality_gate_idle, bounds check total_bytes_received: 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 memory_usage: 10/10 replicas passed. Gate passed.
quality_gate_metrics_logs, bounds check total_bytes_received: 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_private_action_runner, bounds check memory_usage: 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.

agagniere and others added 2 commits August 28, 2026 22:09

Improve the naming

aaa5b6f

agagniere self-assigned this Aug 29, 2026

agagniere added the team/opentelemetry-agent label Aug 29, 2026

dd-octo-sts Bot added internal Identify a non-fork PR team/fleet-automation labels Aug 29, 2026

github-actions Bot added the medium review PR review might take time label Aug 29, 2026

github-actions Bot reviewed Aug 29, 2026

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Update testdata

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github-actions Bot added long review PR is complex, plan time to review it and removed medium review PR review might take time labels Aug 29, 2026

Merge branch 'main' into agagniere/dd-tags-otlp-ingest

27f3f97

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otlp ingest: metrics: add infra_tags_as_tags to promote custom tags - #55622

otlp ingest: metrics: add infra_tags_as_tags to promote custom tags #55622
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Fine details of change detection per experiment

Bounds Checks: ✅ Passed

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		assert.Len(t, next.AllMetrics(), 1)
		out := next.AllMetrics()[0].ResourceMetrics().At(0).Resource().Attributes().AsRaw()

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What does this PR do?

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Describe how you validated your changes

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Files inventory check summary

Results for datadog-agent_7.84.0~devel.git.601.27f3f97.pipeline.134131766-1_amd64.deb:

Results for datadog-iot-agent_7.84.0~devel.git.601.27f3f97.pipeline.134131766-1_amd64.deb:

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Static quality checks

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Regression Detector

Regression Detector Results

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

Bounds Checks: ✅ Passed

Explanation

CI Pass/Fail Decision

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