[EBPF] gpu: query k8s device -> container mapping

[gjulianm]

What does this PR do?

Motivation

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Additional Notes

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: a9465612-6573-4c68-a165-c3c7aceadbd5

Baseline: 7bab2dc
Comparison: e63f5b5
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_idle_all_features	memory utilization	+2.56	[+2.45, +2.67]	1	Logs bounds checks dashboard
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.78	[+0.05, +1.51]	1	Logs
➖	quality_gate_idle	memory utilization	+0.54	[+0.49, +0.58]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.23	[-0.53, +1.00]	1	Logs
➖	file_tree	memory utilization	+0.03	[-0.09, +0.15]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.11, +0.11]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.03	[-0.78, +0.73]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.04	[-0.85, +0.78]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.04	[-0.67, +0.59]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.04	[-0.82, +0.74]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.06	[-0.95, +0.84]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.22	[-0.99, +0.55]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.28	[-0.36, -0.21]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	-0.30	[-0.76, +0.16]	1	Logs
➖	otel_to_otel_logs	ingress throughput	-0.33	[-1.02, +0.36]	1	Logs
➖	quality_gate_logs	% cpu utilization	-0.72	[-3.65, +2.21]	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=50976943 --os-family=ubuntu

Note: This applies to commit e63f5b5

[agent-platform-auto-pr]

Package size comparison

Comparison with ancestor 7bab2dc3c32ab019b7e5a03c4a14d0fb439a69ed

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-amd64-deb	-0.02MB	✅	1271.31MB	1271.32MB	140.00MB
datadog-iot-agent-amd64-deb	0.00MB	✅	113.22MB	113.22MB	10.00MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	78.33MB	78.33MB	10.00MB
datadog-heroku-agent-amd64-deb	0.00MB	⚠️	526.49MB	526.49MB	70.00MB
datadog-agent-x86_64-rpm	-0.02MB	✅	1280.54MB	1280.56MB	140.00MB
datadog-agent-x86_64-suse	-0.02MB	✅	1280.54MB	1280.56MB	140.00MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	113.29MB	113.29MB	10.00MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	113.29MB	113.29MB	10.00MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	78.41MB	78.41MB	10.00MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	78.41MB	78.41MB	10.00MB
datadog-agent-arm64-deb	0.01MB	⚠️	1005.48MB	1005.47MB	140.00MB
datadog-iot-agent-arm64-deb	0.00MB	✅	108.71MB	108.71MB	10.00MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	55.60MB	55.60MB	10.00MB
datadog-agent-aarch64-rpm	0.01MB	⚠️	1014.69MB	1014.68MB	140.00MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	108.78MB	108.78MB	10.00MB

Decision

⚠️ Warning