Update profile metadata structure

[NouhaManai96]

What does this PR do?

Motivation

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Additional Notes

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor f8da8a498f2836e70da3423d91a0a1519b446c29

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-aarch64-rpm	0.25MB	⚠️	944.49MB	944.24MB	140.00MB
datadog-agent-x86_64-rpm	0.24MB	⚠️	1200.21MB	1199.97MB	140.00MB
datadog-agent-x86_64-suse	0.24MB	⚠️	1200.21MB	1199.97MB	140.00MB
datadog-heroku-agent-amd64-deb	0.22MB	⚠️	505.33MB	505.11MB	70.00MB
datadog-agent-arm64-deb	0.19MB	⚠️	935.19MB	935.00MB	140.00MB
datadog-agent-amd64-deb	0.18MB	⚠️	1190.89MB	1190.71MB	140.00MB
datadog-iot-agent-x86_64-rpm	0.03MB	⚠️	113.44MB	113.41MB	10.00MB
datadog-iot-agent-x86_64-suse	0.03MB	⚠️	113.44MB	113.41MB	10.00MB
datadog-iot-agent-amd64-deb	0.03MB	⚠️	113.37MB	113.34MB	10.00MB
datadog-iot-agent-arm64-deb	0.03MB	⚠️	108.84MB	108.81MB	10.00MB
datadog-iot-agent-aarch64-rpm	0.03MB	⚠️	108.91MB	108.88MB	10.00MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	78.57MB	78.57MB	10.00MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	78.65MB	78.65MB	10.00MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	78.65MB	78.65MB	10.00MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	55.77MB	55.77MB	10.00MB

Decision

⚠️ Warning

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 50fd6624-26bf-4933-b2d0-40e5f81e1234

Baseline: f8da8a4
Comparison: 3c73ebc
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	+1.47	[-1.77, +4.71]	1	Logs
➖	quality_gate_idle	memory utilization	+1.18	[+1.14, +1.22]	1	Logs bounds checks dashboard
➖	tcp_syslog_to_blackhole	ingress throughput	+0.47	[+0.41, +0.53]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	+0.22	[-0.56, +0.99]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.15	[-0.32, +0.62]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.15	[+0.07, +0.23]	1	Logs bounds checks dashboard
➖	file_to_blackhole_100ms_latency	egress throughput	+0.05	[-0.67, +0.76]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	+0.03	[-0.61, +0.67]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	+0.01	[-0.76, +0.77]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.01, +0.01]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.01	[-0.11, +0.09]	1	Logs
➖	file_tree	memory utilization	-0.01	[-0.14, +0.11]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.03	[-0.83, +0.77]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.03	[-0.86, +0.79]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	-0.10	[-0.87, +0.67]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.85	[-1.53, -0.17]	1	Logs

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	links
✅	file_to_blackhole_0ms_latency	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http1	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency_http1	memory_usage	10/10
✅	file_to_blackhole_0ms_latency_http2	lost_bytes	10/10
✅	file_to_blackhole_0ms_latency_http2	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency	memory_usage	10/10
✅	file_to_blackhole_1000ms_latency_linear_load	memory_usage	10/10
✅	file_to_blackhole_100ms_latency	lost_bytes	10/10
✅	file_to_blackhole_100ms_latency	memory_usage	10/10
✅	file_to_blackhole_300ms_latency	lost_bytes	10/10
✅	file_to_blackhole_300ms_latency	memory_usage	10/10
✅	file_to_blackhole_500ms_latency	lost_bytes	10/10
✅	file_to_blackhole_500ms_latency	memory_usage	10/10
✅	quality_gate_idle	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_logs	lost_bytes	10/10
✅	quality_gate_logs	memory_usage	10/10

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_idle_all_features, 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_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
• quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.

[agent-platform-auto-pr]

Test changes on VM

Use this command from test-infra-definitions to manually test this PR changes on a VM:

inv aws.create-vm --pipeline-id=51944473 --os-family=ubuntu

Note: This applies to commit 94e2c5f