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[EBPF] docker testutils: store patternScanner in base config #31605

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val06
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@val06 val06 commented Nov 29, 2024

What does this PR do?

Hold patternScanner as a baseconfig field, getting it from the caller (actual UTs)

suggestion to review commit by commit

Motivation

Allow the caller to customize the required logs to monitor. Follow-up to this PR.

Describe how to test/QA your changes

All existing tests should pass

Possible Drawbacks / Trade-offs

Additional Notes

  • Encapsulated Done channel creation in PatternScanner ctor (to simplify the ctor)
  • After this PR, I will rebase gpu UTs flaky tests fix PR to use the new API

@val06 val06 added changelog/no-changelog team/ebpf-platform qa/done QA done before merge and regressions are covered by tests labels Nov 29, 2024
@val06 val06 requested review from a team as code owners November 29, 2024 12:27
@github-actions github-actions bot added component/system-probe long review PR is complex, plan time to review it labels Nov 29, 2024
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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=50144426 --os-family=ubuntu

Note: This applies to commit 9d082d8

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Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: 3d5cfe12-e596-4ad5-ae03-03d869b864d7

Baseline: bdf4917
Comparison: 9d082d8
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
basic_py_check % cpu utilization +3.14 [-0.81, +7.08] 1 Logs
quality_gate_idle_all_features memory utilization +2.27 [+2.16, +2.38] 1 Logs bounds checks dashboard
quality_gate_logs % cpu utilization +1.15 [-1.86, +4.17] 1 Logs
file_tree memory utilization +0.30 [+0.15, +0.45] 1 Logs
file_to_blackhole_1000ms_latency_linear_load egress throughput +0.12 [-0.35, +0.58] 1 Logs
file_to_blackhole_1000ms_latency egress throughput +0.07 [-0.72, +0.87] 1 Logs
file_to_blackhole_0ms_latency egress throughput +0.07 [-0.73, +0.87] 1 Logs
file_to_blackhole_300ms_latency egress throughput +0.07 [-0.57, +0.70] 1 Logs
quality_gate_idle memory utilization +0.03 [-0.02, +0.08] 1 Logs bounds checks dashboard
tcp_dd_logs_filter_exclude ingress throughput +0.00 [-0.01, +0.01] 1 Logs
uds_dogstatsd_to_api ingress throughput -0.02 [-0.12, +0.09] 1 Logs
file_to_blackhole_100ms_latency egress throughput -0.03 [-0.70, +0.64] 1 Logs
file_to_blackhole_500ms_latency egress throughput -0.07 [-0.84, +0.70] 1 Logs
uds_dogstatsd_to_api_cpu % cpu utilization -0.25 [-0.98, +0.47] 1 Logs
otel_to_otel_logs ingress throughput -0.51 [-1.19, +0.16] 1 Logs
tcp_syslog_to_blackhole ingress throughput -0.98 [-1.04, -0.92] 1 Logs
pycheck_lots_of_tags % cpu utilization -3.97 [-7.33, -0.62] 1 Logs

Bounds Checks: ❌ Failed

perf experiment bounds_check_name replicates_passed links
file_to_blackhole_0ms_latency lost_bytes 8/10
file_to_blackhole_0ms_latency 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 memory_usage 10/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
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_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
  • quality_gate_logs, bounds check memory_usage: 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 memory_usage: 10/10 replicas passed. Gate passed.

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val06 commented Nov 29, 2024

/merge

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dd-devflow bot commented Nov 29, 2024

Devflow running: /merge

View all feedbacks in Devflow UI.


2024-11-29 14:09:25 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 23m.

@dd-mergequeue dd-mergequeue bot merged commit 0471849 into main Nov 29, 2024
296 of 297 checks passed
@dd-mergequeue dd-mergequeue bot deleted the valeri.pliskin/embed-patternscanner-in-dockerconfig branch November 29, 2024 14:38
@github-actions github-actions bot added this to the 7.62.0 milestone Nov 29, 2024
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3 participants