datadog-agent
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[CWS] fileless files mount source and origin fix
What does this PR do?
Motivation
Describe how to test/QA your changes
Possible Drawbacks / Trade-offs
Additional Notes
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=47321484 --os-family=ubuntu
Note: This applies to commit aff3b10f
Regression Detector
Regression Detector Results
Run ID: d766f570-10aa-4191-b2b9-13745f23afdb Metrics dashboard Target profiles
Baseline: a5b503f11733ea3acdcac73353cab5d02a9ca7bf Comparison: aff3b10f381529b8a2c98616d07c2a7be3badc1c
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 |
|---|---|---|---|---|---|---|
| ➖ | pycheck_lots_of_tags | % cpu utilization | +0.82 | [-1.66, +3.31] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +0.53 | [-0.20, +1.26] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +0.52 | [+0.48, +0.57] | 1 | Logs |
| ➖ | basic_py_check | % cpu utilization | +0.43 | [-2.39, +3.24] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | +0.29 | [+0.25, +0.33] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.03 | [-0.20, +0.25] | 1 | Logs |
| ➖ | file_to_blackhole_300ms_latency | egress throughput | +0.02 | [-0.16, +0.20] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.00 | [-0.33, +0.34] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | Logs |
| ➖ | idle | memory utilization | -0.01 | [-0.05, +0.04] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.01 | [-0.26, +0.24] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.01 | [-0.12, +0.09] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.18 | [-0.67, +0.31] | 1 | Logs |
| ➖ | otel_to_otel_logs | ingress throughput | -0.47 | [-1.28, +0.33] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.57 | [-0.67, -0.47] | 1 | Logs bounds checks dashboard |
| ➖ | file_tree | memory utilization | -0.98 | [-1.11, -0.85] | 1 | Logs |
| ➖ | idle_all_features | memory utilization | -1.15 | [-1.25, -1.05] | 1 | Logs bounds checks dashboard |
Bounds Checks
| perf | experiment | bounds_check_name | replicates_passed |
|---|---|---|---|
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 |
| ✅ | file_to_blackhole_300ms_latency | memory_usage | 10/10 |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 |
| ✅ | idle | memory_usage | 10/10 |
| ✅ | idle_all_features | memory_usage | 10/10 |
| ✅ | quality_gate_idle | memory_usage | 10/10 |
| ✅ | quality_gate_idle_all_features | 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:
-
Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
-
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.
-
Its configuration does not mark it "erratic".
/merge
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