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enhancement(transforms): redundant clone in log_to_metric transform #21431

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jorgehermo9
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@jorgehermo9 jorgehermo9 commented Oct 5, 2024

Found this unused clone while working on #21429. Didn't add this in that PR because it seemed unrelated to me. If you want me to include this small change in #21429 I'll do it without problem.

I think a changelog entry is not necessary for this internal fix.

@jorgehermo9 jorgehermo9 requested a review from a team as a code owner October 5, 2024 09:43
@github-actions github-actions bot added the domain: transforms Anything related to Vector's transform components label Oct 5, 2024
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Nice 👍

@jszwedko jszwedko added the no-changelog Changes in this PR do not need user-facing explanations in the release changelog label Oct 6, 2024
@jszwedko jszwedko added this pull request to the merge queue Oct 6, 2024
@github-merge-queue github-merge-queue bot removed this pull request from the merge queue due to failed status checks Oct 6, 2024
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Failed due to missing changelog, although you added the label 😮

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@pront pront added this pull request to the merge queue Oct 7, 2024
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jszwedko commented Oct 7, 2024

Failed due to missing changelog, although you added the label 😮

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I think it actually failed due to the regression test workflow failing 🤔 This seems like it could be a flake though 🙏

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github-actions bot commented Oct 7, 2024

Regression Detector Results

Run ID: eab518cc-e6f0-4c84-9e27-7e9aa2150479 Metrics dashboard

Baseline: 51dcf8d
Comparison: 3a5947e

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.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf experiment goal Δ mean % Δ mean % CI links
file_to_blackhole egress throughput +5.08 [-2.07, +12.22]

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI links
file_to_blackhole egress throughput +5.08 [-2.07, +12.22]
syslog_splunk_hec_logs ingress throughput +2.12 [+2.02, +2.21]
syslog_humio_logs ingress throughput +1.81 [+1.67, +1.94]
datadog_agent_remap_datadog_logs_acks ingress throughput +1.66 [+1.48, +1.84]
syslog_regex_logs2metric_ddmetrics ingress throughput +1.63 [+1.47, +1.79]
http_to_s3 ingress throughput +1.21 [+0.93, +1.49]
syslog_loki ingress throughput +0.74 [+0.61, +0.87]
socket_to_socket_blackhole ingress throughput +0.69 [+0.64, +0.75]
otlp_http_to_blackhole ingress throughput +0.38 [+0.23, +0.53]
http_text_to_http_json ingress throughput +0.22 [+0.11, +0.33]
http_to_http_noack ingress throughput +0.16 [+0.08, +0.25]
http_to_http_json ingress throughput +0.03 [-0.01, +0.06]
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.07, +0.09]
splunk_hec_to_splunk_hec_logs_noack ingress throughput +0.01 [-0.09, +0.10]
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.11, +0.11]
splunk_hec_route_s3 ingress throughput -0.05 [-0.35, +0.25]
syslog_log2metric_splunk_hec_metrics ingress throughput -0.20 [-0.30, -0.10]
syslog_log2metric_tag_cardinality_limit_blackhole ingress throughput -0.28 [-0.36, -0.20]
otlp_grpc_to_blackhole ingress throughput -0.29 [-0.40, -0.18]
datadog_agent_remap_datadog_logs ingress throughput -0.53 [-0.72, -0.34]
http_elasticsearch ingress throughput -0.83 [-1.02, -0.64]
datadog_agent_remap_blackhole ingress throughput -0.97 [-1.08, -0.86]
datadog_agent_remap_blackhole_acks ingress throughput -1.26 [-1.36, -1.15]
syslog_log2metric_humio_metrics ingress throughput -1.42 [-1.60, -1.23]
fluent_elasticsearch ingress throughput -2.04 [-2.52, -1.56]
http_to_http_acks ingress throughput -2.88 [-4.08, -1.68]

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".

Merged via the queue into vectordotdev:master with commit 3a5947e Oct 7, 2024
67 of 69 checks passed
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