[CONTINT-3546] Check dd-agent UID and document doc update needed in case of change

[L3n41c]

What does this PR do?

Check if the dd-agent user inside the agent docker image is 100.

Motivation

The exact numeric value of the UID of the dd-agent user shouldn’t matter. But people that don’t want to let the agent run as root might want to explicitly set a non-root user in their k8s security context. And, in a k8s security context, we can only specify a numeric UID and not a username. So, if the UID of the dd-agent user happen to change again and cannot be forced to 100 (because of a conflict), we need to update

• the public documentation (see DataDog/documentation#21889)
• the internal documentation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[pr-commenter[bot]]

Test changes on VM

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

inv create-vm --pipeline-id=30111614 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 1ae93a2b-db07-4fdc-8f34-ad9fa80e6d71 Baseline: 760ecea30cc9902326f029fe7793b4d148f63fec Comparison: dbb8b4c95a0bc00b017657fd01035fb9c3b5c3af

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

No significant changes in experiment optimization goals

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

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

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

perf	experiment	goal	Δ mean %	Δ mean % CI
❌	file_to_blackhole	% cpu utilization	+55.88	[+47.48, +64.29]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
❌	file_to_blackhole	% cpu utilization	+55.88	[+47.48, +64.29]
➖	process_agent_standard_check_with_stats	memory utilization	+1.12	[+1.08, +1.16]
➖	pycheck_1000_100byte_tags	% cpu utilization	+0.47	[-4.78, +5.71]
➖	file_tree	memory utilization	+0.26	[+0.20, +0.32]
➖	idle	memory utilization	+0.10	[+0.07, +0.14]
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.19, +0.22]
➖	trace_agent_msgpack	ingress throughput	-0.00	[-0.00, +0.00]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.01, +0.00]
➖	trace_agent_json	ingress throughput	-0.02	[-0.05, -0.00]
➖	otel_to_otel_logs	ingress throughput	-0.04	[-0.49, +0.42]
➖	process_agent_standard_check	memory utilization	-0.15	[-0.19, -0.11]
➖	process_agent_real_time_mode	memory utilization	-0.31	[-0.34, -0.27]
➖	tcp_syslog_to_blackhole	ingress throughput	-1.18	[-1.28, -1.09]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-2.28	[-5.16, +0.59]
➖	basic_py_check	% cpu utilization	-2.85	[-5.08, -0.63]

Explanation

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".

[clamoriniere]

/merge

[dd-devflow[bot]]

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