[EBPF] Minor fixes in KMT tests

[gjulianm]

What does this PR do?

This PR contains some minor fixes around the KMT local testing process:

• Fix path resolution in packages when symlinks are present
• Clearly show the final result of kmt.test: no test runs/failures/successes
• Fix cross-compilation setup being re-done every time due to the result of the command not being returned
• Improve information when copying files to remote instances and using the -e flag

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[gjulianm]

/trigger-ci

[dd-devflow[bot]]

:steam_locomotive: Gitlab pipeline started

Started pipeline #44304973

[agent-platform-auto-pr[bot]]

[Fast Unit Tests Report]

On pipeline 44311641 (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

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 450af780-19f4-48b1-81ef-430258a3b1db Metrics dashboard Target profiles

Baseline: 9faa31ba5d9760eba07bc29c66753f2539e648e1 Comparison: 58714e5add0fc3470b6623c63febb8fb677256fe

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.

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	basic_py_check	% cpu utilization	+0.85	[-1.89, +3.58]	1	Logs
➖	idle	memory utilization	+0.30	[+0.26, +0.34]	1	Logs
➖	tcp_syslog_to_blackhole	ingress throughput	+0.21	[+0.15, +0.27]	1	Logs
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.13	[-0.63, +0.89]	1	Logs
➖	file_tree	memory utilization	+0.11	[+0.01, +0.21]	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	[-0.00, +0.00]	1	Logs
➖	pycheck_lots_of_tags	% cpu utilization	-0.83	[-3.45, +1.78]	1	Logs
➖	otel_to_otel_logs	ingress throughput	-1.32	[-2.15, -0.49]	1	Logs

Bounds Checks

perf	experiment	bounds_check_name	replicates_passed
✅	idle	memory_usage	10/10

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".

[gjulianm]

/trigger-ci -v RUN_KMT_TESTS=on

[dd-devflow[bot]]

:steam_locomotive: Gitlab pipeline started

Started pipeline #44311641

[gjulianm]

/merge

[dd-devflow[bot]]

:steam_locomotive: MergeQueue: pull request added to the queue

The median merge time in main is 23m.

Use /merge -c to cancel this operation!