[CWS] make the security-agent log-level dynamic and log event in trace level#48795
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Go Package Import DifferencesBaseline: 21276c4
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Files inventory check summaryFile checks results against ancestor 21276c47: Results for datadog-agent_7.79.0~devel.git.471.c03de45.pipeline.106444850-1_amd64.deb:No change detected |
Static quality checks✅ Please find below the results from static quality gates Successful checksInfo
16 successful checks with minimal change (< 2 KiB)
On-wire sizes (compressed)
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 27c8b34 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | +1.46 | [-1.57, +4.48] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | +1.46 | [-1.57, +4.48] | 1 | Logs |
| ➖ | quality_gate_metrics_logs | memory utilization | +0.78 | [+0.54, +1.01] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_metrics_sum_delta | memory utilization | +0.21 | [+0.03, +0.39] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulative | memory utilization | +0.21 | [+0.06, +0.35] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | +0.19 | [+0.13, +0.26] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.09 | [-0.48, +0.66] | 1 | Logs |
| ➖ | ddot_metrics_sum_cumulativetodelta_exporter | memory utilization | +0.08 | [-0.14, +0.30] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.01 | [-0.11, +0.14] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_v3 | ingress throughput | +0.01 | [-0.19, +0.21] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.01 | [-0.11, +0.13] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.20, +0.21] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.03 | [-0.45, +0.40] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.05 | [-0.44, +0.35] | 1 | Logs |
| ➖ | file_tree | memory utilization | -0.06 | [-0.12, -0.01] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.09 | [-0.12, -0.05] | 1 | Logs bounds checks dashboard |
| ➖ | docker_containers_memory | memory utilization | -0.11 | [-0.19, -0.03] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.29 | [-0.34, -0.24] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_metrics | memory utilization | -0.33 | [-0.52, -0.15] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | -0.46 | [-0.53, -0.39] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | -0.54 | [-2.19, +1.11] | 1 | Logs bounds checks dashboard |
| ➖ | otlp_ingest_logs | memory utilization | -0.56 | [-0.67, -0.45] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | -0.70 | [-0.86, -0.55] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -2.51 | [-2.68, -2.35] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | observed_value | links |
|---|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | 692 ≥ 26 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | 273.05MiB ≤ 370MiB | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | 690 ≥ 26 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | 0.19GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_0ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | 0.23GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_1000ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | 0.20GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_100ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | 0.21GiB ≤ 1.20GiB | |
| ✅ | file_to_blackhole_500ms_latency | missed_bytes | 10/10 | 0B = 0B | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | 3 = 3 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | 171.99MiB ≤ 181MiB | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | 3 = 3 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | 487.29MiB ≤ 550MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | 4 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | 203.85MiB ≤ 220MiB | bounds checks dashboard |
| ✅ | quality_gate_logs | missed_bytes | 10/10 | 0B = 0B | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | 366.02 ≤ 2000 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | 3 ≤ 6 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | memory_usage | 10/10 | 403.33MiB ≤ 475MiB | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | missed_bytes | 10/10 | 0B = 0B | bounds checks dashboard |
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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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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_metrics_logs, bounds check missed_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, 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 missed_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
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| rsa.reporter.ReportRaw(evt.GetData(), evt.Service, evt.Timestamp.AsTime(), evt.GetTags()...) | ||
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| log.Tracef("runtime message report : %s", string(evt.GetData())) |
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Avoid eager payload stringify on hot event path
This Tracef call eagerly evaluates string(evt.GetData()) for every non-SecInfo event, even when trace logging is disabled, because function arguments are computed before Tracef checks log level. On high event-rate workloads this adds avoidable allocation/CPU overhead in DispatchEvent; gate this behind a trace-level check (or use a lazy trace helper) so payload formatting only happens when the message will actually be logged.
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What does this PR do?
This aims to debug security-agent events.
Motivation
Describe how you validated your changes
Additional Notes