[EBPF] gpu: enable uprobe attacher debug endpoints

[gjulianm]

What does this PR do?

This PR adds debug endpoints for the GPU module, allowing us to query the state of the uprobe attacher and manually attaching to PIDs.

Motivation

Improve debugging capabilities, allow us to debug why are certain processes not being attached.

Describe how you validated your changes

Validated locally and in a staging cluster.

Possible Drawbacks / Trade-offs

Additional Notes

[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=54662339 --os-family=ubuntu

Note: This applies to commit ab723ad

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 9bca79acdf864311357661fc906f3007f2c18db3

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-arm64-deb	0.00MB	✅	864.98MB	864.97MB	0.50MB
datadog-agent-aarch64-rpm	0.00MB	✅	874.70MB	874.69MB	0.50MB
datadog-agent-amd64-deb	0.00MB	✅	877.18MB	877.18MB	0.50MB
datadog-agent-x86_64-rpm	0.00MB	✅	886.92MB	886.92MB	0.50MB
datadog-agent-x86_64-suse	0.00MB	✅	886.92MB	886.92MB	0.50MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	59.02MB	59.02MB	0.50MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	59.10MB	59.10MB	0.50MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	59.10MB	59.10MB	0.50MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	56.51MB	56.51MB	0.50MB
datadog-heroku-agent-amd64-deb	0.00MB	✅	456.45MB	456.45MB	0.50MB
datadog-iot-agent-amd64-deb	0.00MB	✅	93.84MB	93.84MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	93.91MB	93.91MB	0.50MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	93.91MB	93.91MB	0.50MB
datadog-iot-agent-arm64-deb	0.00MB	✅	89.89MB	89.89MB	0.50MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	89.96MB	89.96MB	0.50MB

Decision

✅ Passed

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 1a0f6aeb-ffa0-470d-aa54-6c04b30c5a30

Baseline: 9bca79a
Comparison: ab723ad
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	+1.45	[-1.60, +4.51]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	+0.81	[+0.74, +0.88]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	+0.20	[+0.17, +0.23]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.19	[-0.59, +0.97]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	+0.06	[-0.84, +0.96]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.05	[-0.78, +0.88]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.02, +0.03]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.27, +0.27]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.01	[-0.63, +0.61]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.03	[-0.67, +0.61]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.04	[-0.94, +0.86]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.15	[-0.23, -0.08]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	-0.16	[-0.63, +0.30]	1	Logs
➖	file_tree	memory utilization	-0.23	[-0.30, -0.16]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.73	[-1.50, +0.05]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.74	[-1.63, +0.15]	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	intake_connections	10/10	bounds checks dashboard
✅	quality_gate_idle	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	intake_connections	10/10	bounds checks dashboard
✅	quality_gate_idle_all_features	memory_usage	10/10	bounds checks dashboard
✅	quality_gate_logs	intake_connections	10/10
✅	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_all_features, bounds check intake_connections: 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 lost_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.

[gjulianm]

/merge

[dd-devflow]

Devflow running: /merge

View all feedbacks in Devflow UI.

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2025-01-31 15:36:20 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 27m.

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2025-01-31 17:27:43 UTC ℹ️ MergeQueue: Readding this merge request to the queue because another merge request processed with yours failed. No action is needed from your side.

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2025-01-31 17:38:51 UTC ❌ MergeQueue: The build pipeline contains failing jobs for this merge request

Build pipeline has failing jobs for 9349cf2:

• tests_ebpf_arm64

⚠️ Do NOT retry failed jobs directly (why?).

What to do next?

• Investigate the failures and when ready, re-add your pull request to the queue!
• If your PR checks are green, try to rebase/merge. It might be because the CI run is a bit old.
• Any question, go check the FAQ.

Details

Since those jobs are not marked as being allowed to fail, the pipeline will most likely fail.
Therefore, and to allow other builds to be processed, this merge request has been rejected and the pipeline got canceled.

[gjulianm]

/merge

[dd-devflow]

Devflow running: /merge

View all feedbacks in Devflow UI.

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2025-02-03 11:03:52 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 26m.

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2025-02-03 11:31:32 UTC ℹ️ MergeQueue: This merge request was merged