Use nodetreemodel by default, instead of viper

[dustmop]

What does this PR do?

Use nodetreemodel by default, instead of viper

Reapplying #48242 after the e2e tests have been fixed

Motivation

Moving away from viper

Describe how you validated your changes

Additional Notes

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 36078defc1

ℹ️ About Codex in GitHub

Codex has been enabled to automatically 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".

If Codex has suggestions, it will comment; otherwise it will react with 👍.

When you sign up for Codex through ChatGPT, Codex can also answer questions or update the PR, like "@codex address that feedback".

[chatgpt-codex-connector]

Fall back to viper when version threshold is unparsable

With this change, any DD_CONF_NODETREEMODEL value that fails CompareTo parsing now falls through to the new default (nodetreemodel). That means a common threshold format like 7.80 (missing patch) will enable NTM even on older agents (for example 7.75.2), which defeats the documented "enable NTM only at or above this version" rollout behavior and can turn on NTM earlier than intended in production configs.

Useful? React with 👍 / 👎.

[dustmop]

This is intentional.

[agent-platform-auto-pr]

Files inventory check summary

File checks results against ancestor 4313ea30:

Results for datadog-agent_7.79.0~devel.git.361.e879195.pipeline.105539349-1_amd64.deb:

No change detected

[agent-platform-auto-pr]

Static quality checks

✅ Please find below the results from static quality gates
Comparison made with ancestor 4313ea3
📊 Static Quality Gates Dashboard
🔗 SQG Job
SOME SIZE DELTAS ARE N/A (ANCESTOR METRICS NOT YET AVAILABLE). RETRY JOB

Successful checks

Info

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	N/A	N/A → 752.921 → 753.380
✅	agent_deb_amd64_fips	N/A	N/A → 709.864 → 713.900
✅	agent_heroku_amd64	N/A	N/A → 313.293 → 320.580
✅	agent_msi	N/A	N/A → 604.837 → 651.440
✅	agent_rpm_amd64	N/A	N/A → 752.905 → 753.350
✅	agent_rpm_amd64_fips	N/A	N/A → 709.848 → 713.880
✅	agent_rpm_arm64	N/A	N/A → 731.337 → 735.290
✅	agent_rpm_arm64_fips	N/A	N/A → 691.301 → 696.840
✅	agent_suse_amd64	N/A	N/A → 752.905 → 753.350
✅	agent_suse_amd64_fips	N/A	N/A → 709.848 → 713.880
✅	agent_suse_arm64	N/A	N/A → 731.337 → 735.290
✅	agent_suse_arm64_fips	N/A	N/A → 691.301 → 696.840
✅	docker_agent_amd64	N/A	N/A → 813.225 → 815.700
✅	docker_agent_arm64	N/A	N/A → 816.426 → 821.970
✅	docker_agent_jmx_amd64	N/A	N/A → 1004.140 → 1006.580
✅	docker_agent_jmx_arm64	N/A	N/A → 996.120 → 1001.570
✅	docker_cluster_agent_amd64	N/A	N/A → 203.917 → 206.270
✅	docker_cluster_agent_arm64	N/A	N/A → 218.356 → 220.000
✅	docker_cws_instrumentation_amd64	N/A	N/A → 7.142 → 7.180
✅	docker_cws_instrumentation_arm64	N/A	N/A → 6.689 → 6.920
✅	docker_dogstatsd_amd64	N/A	N/A → 39.234 → 39.380
✅	docker_dogstatsd_arm64	N/A	N/A → 37.445 → 37.940
✅	dogstatsd_deb_amd64	N/A	N/A → 29.878 → 30.610
✅	dogstatsd_deb_arm64	N/A	N/A → 28.031 → 29.110
✅	dogstatsd_rpm_amd64	N/A	N/A → 29.878 → 30.610
✅	dogstatsd_suse_amd64	N/A	N/A → 29.878 → 30.610
✅	iot_agent_deb_amd64	N/A	N/A → 43.168 → 44.290
✅	iot_agent_deb_arm64	N/A	N/A → 40.227 → 41.920
✅	iot_agent_deb_armhf	N/A	N/A → 40.975 → 42.100
✅	iot_agent_rpm_amd64	N/A	N/A → 43.169 → 44.290
✅	iot_agent_suse_amd64	N/A	N/A → 43.169 → 44.290

On-wire sizes (compressed)

	Quality gate	Change	Size (prev → curr → max)
✅	agent_deb_amd64	N/A	N/A → 174.729 → 178.360
✅	agent_deb_amd64_fips	N/A	N/A → 165.354 → 172.790
✅	agent_heroku_amd64	N/A	N/A → 74.996 → 79.970
✅	agent_msi	N/A	N/A → 138.422 → 146.220
✅	agent_rpm_amd64	N/A	N/A → 177.568 → 181.830
✅	agent_rpm_amd64_fips	N/A	N/A → 167.632 → 173.370
✅	agent_rpm_arm64	N/A	N/A → 159.526 → 163.060
✅	agent_rpm_arm64_fips	N/A	N/A → 151.363 → 156.170
✅	agent_suse_amd64	N/A	N/A → 177.568 → 181.830
✅	agent_suse_amd64_fips	N/A	N/A → 167.632 → 173.370
✅	agent_suse_arm64	N/A	N/A → 159.526 → 163.060
✅	agent_suse_arm64_fips	N/A	N/A → 151.363 → 156.170
✅	docker_agent_amd64	N/A	N/A → 268.132 → 272.480
✅	docker_agent_arm64	N/A	N/A → 255.349 → 261.060
✅	docker_agent_jmx_amd64	N/A	N/A → 336.781 → 341.100
✅	docker_agent_jmx_arm64	N/A	N/A → 319.990 → 325.620
✅	docker_cluster_agent_amd64	N/A	N/A → 71.361 → 72.920
✅	docker_cluster_agent_arm64	N/A	N/A → 66.996 → 68.220
✅	docker_cws_instrumentation_amd64	N/A	N/A → 2.999 → 3.330
✅	docker_cws_instrumentation_arm64	N/A	N/A → 2.729 → 3.090
✅	docker_dogstatsd_amd64	N/A	N/A → 15.174 → 15.820
✅	docker_dogstatsd_arm64	N/A	N/A → 14.493 → 14.830
✅	dogstatsd_deb_amd64	N/A	N/A → 7.893 → 8.790
✅	dogstatsd_deb_arm64	N/A	N/A → 6.776 → 7.710
✅	dogstatsd_rpm_amd64	N/A	N/A → 7.904 → 8.800
✅	dogstatsd_suse_amd64	N/A	N/A → 7.904 → 8.800
✅	iot_agent_deb_amd64	N/A	N/A → 11.374 → 13.040
✅	iot_agent_deb_arm64	N/A	N/A → 9.679 → 11.450
✅	iot_agent_deb_armhf	N/A	N/A → 9.916 → 11.620
✅	iot_agent_rpm_amd64	N/A	N/A → 11.393 → 13.060
✅	iot_agent_suse_amd64	N/A	N/A → 11.393 → 13.060

[cit-pr-commenter-54b7da]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: fac9ebe0-1ba0-48fe-9bc1-40a6f3b97c39

Baseline: 28617db
Comparison: e879195
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	-0.21	[-3.27, +2.85]	1	Logs

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gate_logs	% cpu utilization	+2.93	[+1.28, +4.57]	1	Logs bounds checks dashboard
➖	tcp_syslog_to_blackhole	ingress throughput	+1.33	[+1.18, +1.47]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.04	[-0.35, +0.44]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.04	[-0.46, +0.53]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.18, +0.21]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.01	[-0.40, +0.43]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.01	[-0.12, +0.10]	1	Logs
➖	uds_dogstatsd_to_api_v3	ingress throughput	-0.01	[-0.21, +0.19]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.02	[-0.13, +0.09]	1	Logs
➖	docker_containers_cpu	% cpu utilization	-0.21	[-3.27, +2.85]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.95	[-0.99, -0.92]	1	Logs bounds checks dashboard
➖	file_tree	memory utilization	-0.95	[-1.01, -0.89]	1	Logs
➖	quality_gate_metrics_logs	memory utilization	-1.03	[-1.27, -0.79]	1	Logs bounds checks dashboard
➖	otlp_ingest_metrics	memory utilization	-1.05	[-1.21, -0.89]	1	Logs
➖	ddot_metrics	memory utilization	-1.22	[-1.41, -1.04]	1	Logs
➖	ddot_logs	memory utilization	-1.23	[-1.29, -1.17]	1	Logs
➖	ddot_metrics_sum_cumulativetodelta_exporter	memory utilization	-1.25	[-1.48, -1.02]	1	Logs
➖	otlp_ingest_logs	memory utilization	-1.28	[-1.40, -1.16]	1	Logs
➖	ddot_metrics_sum_delta	memory utilization	-1.28	[-1.47, -1.10]	1	Logs
➖	ddot_metrics_sum_cumulative	memory utilization	-1.42	[-1.56, -1.27]	1	Logs
➖	docker_containers_memory	memory utilization	-1.61	[-1.69, -1.53]	1	Logs
➖	uds_dogstatsd_20mb_12k_contexts_20_senders	memory utilization	-1.90	[-1.96, -1.84]	1	Logs
➖	quality_gate_idle	memory utilization	-1.94	[-1.99, -1.89]	1	Logs bounds checks dashboard

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	observed_value	links
✅	docker_containers_cpu	simple_check_run	10/10	681 ≥ 26
✅	docker_containers_memory	memory_usage	10/10	269.80MiB ≤ 370MiB
✅	docker_containers_memory	simple_check_run	10/10	710 ≥ 26
✅	file_to_blackhole_0ms_latency	memory_usage	10/10	0.19GiB ≤ 1.20GiB
✅	file_to_blackhole_0ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10	0.23GiB ≤ 1.20GiB
✅	file_to_blackhole_1000ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_100ms_latency	memory_usage	10/10	0.19GiB ≤ 1.20GiB
✅	file_to_blackhole_100ms_latency	missed_bytes	10/10	0B = 0B
✅	file_to_blackhole_500ms_latency	memory_usage	10/10	0.21GiB ≤ 1.20GiB
✅	file_to_blackhole_500ms_latency	missed_bytes	10/10	0B = 0B
✅	quality_gate_idle	intake_connections	10/10	3 = 3	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	172.54MiB ≤ 175MiB	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	3 = 3	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	487.26MiB ≤ 550MiB	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10	3 ≤ 6	bounds checks dashboard
✅	quality_gate_logs	memory_usage	10/10	202.17MiB ≤ 220MiB	bounds checks dashboard
✅	quality_gate_logs	missed_bytes	10/10	0B = 0B	bounds checks dashboard
✅	quality_gate_metrics_logs	cpu_usage	10/10	351.41 ≤ 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	412.93MiB ≤ 475MiB	bounds checks dashboard
✅	quality_gate_metrics_logs	missed_bytes	10/10	0B = 0B	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_logs, bounds check memory_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 intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, bounds check cpu_usage: 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 intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_metrics_logs, 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 memory_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.