[EBPF] uprobes: ensure shared libraries are attached even if attaching to executable fails

[gjulianm]

What does this PR do?

This PR ensures that the uprobe attacher tries to attach to shared libraries of a process even when it fails to attach to the main executable. If we're trying to attach uprobes for a given function that is not present on the executable but it's present on a shared library, we cannot abort the search just because the executable failed to attach.

Motivation

Resolve a bug in GPU monitoring where we weren't attaching uprobes correctly to processes that were already started and had already opened libcudart.so.

Describe how you validated your changes

Added a unit test that reproduced the issue and is now passing.

Possible Drawbacks / Trade-offs

Additional Notes

This bug only affected GPU monitoring, as it's the only module that uses the attacher targeting both executables and shared libraries at the same time.

[agent-platform-auto-pr]

[Fast Unit Tests Report]

On pipeline 54584244 (CI Visibility). The following jobs did not run any unit tests:

Jobs:

• tests_deb-arm64-py3
• tests_deb-x64-py3
• tests_flavor_dogstatsd_deb-x64
• tests_flavor_heroku_deb-x64
• tests_flavor_iot_deb-x64
• tests_rpm-arm64-py3
• tests_rpm-x64-py3
• tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-devx-help

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor c68ee8d8d517d8e70559904ea19c7d91a0a68ca9

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-amd64-deb	0.00MB	✅	882.20MB	882.20MB	0.50MB
datadog-agent-x86_64-rpm	0.00MB	✅	891.94MB	891.94MB	0.50MB
datadog-agent-x86_64-suse	0.00MB	✅	891.94MB	891.94MB	0.50MB
datadog-agent-arm64-deb	0.00MB	✅	869.99MB	869.99MB	0.50MB
datadog-agent-aarch64-rpm	0.00MB	✅	879.71MB	879.71MB	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	✅	56.50MB	56.50MB	0.50MB
datadog-heroku-agent-amd64-deb	0.00MB	✅	461.46MB	461.46MB	0.50MB
datadog-iot-agent-amd64-deb	0.00MB	✅	93.81MB	93.81MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	93.88MB	93.88MB	0.50MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	93.88MB	93.88MB	0.50MB
datadog-iot-agent-arm64-deb	0.00MB	✅	89.87MB	89.87MB	0.50MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	89.94MB	89.94MB	0.50MB

Decision

✅ 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=54584918 --os-family=ubuntu

Note: This applies to commit 35c5514

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: b4b7fde1-7038-433b-9a32-218b73b24f2e

Baseline: c68ee8d
Comparison: 35c5514
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	+0.15	[+0.09, +0.22]	1	Logs bounds checks dashboard
➖	file_to_blackhole_500ms_latency	egress throughput	+0.10	[-0.68, +0.89]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	+0.07	[-0.78, +0.92]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	+0.07	[-0.77, +0.90]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.02	[-0.45, +0.50]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	+0.02	[-0.78, +0.82]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.01	[-0.26, +0.29]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.00	[-0.02, +0.02]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.01	[-0.78, +0.76]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	-0.01	[-0.64, +0.63]	1	Logs
➖	quality_gate_logs	% cpu utilization	-0.30	[-3.34, +2.74]	1	Logs
➖	file_tree	memory utilization	-0.41	[-0.48, -0.34]	1	Logs
➖	quality_gate_idle	memory utilization	-0.42	[-0.46, -0.38]	1	Logs bounds checks dashboard
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.55	[-1.35, +0.26]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	-0.92	[-0.99, -0.84]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-1.88	[-2.79, -0.97]	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, 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 intake_connections: 10/10 replicas passed. Gate passed.
• quality_gate_idle_all_features, bounds check memory_usage: 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.