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flesh out an example multitenant strategy #243

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This is not intended to be merged as-is, but serve as a starting point for something demo-able. There are currently a number of limitations that make it decidedly not production ready.

Signed-off-by: Luke Steensen <luke.steensen@gmail.com>
@lukesteensen lukesteensen requested review from a team as code owners September 10, 2024 21:26
@github-actions github-actions bot added area/core Core functionality, event model, etc. area/components Sources, transforms, and destinations. source/dogstatsd DogStatsD source. labels Sep 10, 2024
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Regression Detector (Saluki)

Regression Detector Results

Run ID: 27b3b87e-e33a-4fa4-9399-f05d0c79b4ab

Baseline: 1c64a0e
Comparison: 7ed7d49

Regression Detector: ❌

Significant changes in experiment optimization goals

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

perf experiment goal Δ mean % Δ mean % CI trials links
dsd_uds_100mb_3k_contexts_distributions_only memory utilization +22.11 [+21.95, +22.27] 1
dsd_uds_1mb_50k_contexts_memlimit ingress throughput -18.75 [-21.59, -15.92] 1
dsd_uds_500mb_3k_contexts ingress throughput -38.49 [-38.57, -38.40] 1

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
dsd_uds_100mb_3k_contexts_distributions_only memory utilization +22.11 [+21.95, +22.27] 1
dsd_uds_10mb_3k_contexts ingress throughput +0.05 [+0.00, +0.09] 1
dsd_uds_50mb_10k_contexts_no_inlining_no_allocs ingress throughput +0.01 [-0.02, +0.04] 1
dsd_uds_50mb_10k_contexts_no_inlining ingress throughput +0.00 [-0.00, +0.00] 1
dsd_uds_1mb_3k_contexts ingress throughput +0.00 [-0.03, +0.03] 1
dsd_uds_512kb_3k_contexts ingress throughput +0.00 [-0.01, +0.01] 1
dsd_uds_100mb_3k_contexts ingress throughput -0.01 [-0.02, +0.01] 1
dsd_uds_1mb_50k_contexts ingress throughput -0.01 [-0.03, +0.01] 1
dsd_uds_100mb_250k_contexts ingress throughput -1.18 [-1.38, -0.97] 1
dsd_uds_1mb_50k_contexts_memlimit ingress throughput -18.75 [-21.59, -15.92] 1
dsd_uds_500mb_3k_contexts ingress throughput -38.49 [-38.57, -38.40] 1

Explanation

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".

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Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 86772dd3-ff01-47a9-aad2-13f676c19890

Baseline: 7.55.2
Comparison: 7.55.3

Regression Detector: ✅

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
dsd_uds_10mb_3k_contexts ingress throughput +0.04 [+0.02, +0.07] 1
dsd_uds_100mb_3k_contexts_distributions_only memory utilization +0.01 [-0.16, +0.17] 1
dsd_uds_100mb_3k_contexts ingress throughput +0.01 [-0.02, +0.04] 1
dsd_uds_1mb_50k_contexts ingress throughput +0.00 [-0.00, +0.00] 1
dsd_uds_1mb_3k_contexts ingress throughput +0.00 [-0.04, +0.04] 1
dsd_uds_1mb_50k_contexts_memlimit ingress throughput +0.00 [-0.00, +0.00] 1
dsd_uds_500mb_3k_contexts ingress throughput -0.00 [-0.01, +0.01] 1
dsd_uds_512kb_3k_contexts ingress throughput -0.01 [-0.04, +0.02] 1
dsd_uds_100mb_250k_contexts ingress throughput -0.01 [-0.05, +0.02] 1

Explanation

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".

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pr-commenter bot commented Sep 10, 2024

Regression Detector Links

Experiment Result Links

experiment link(s)
dsd_uds_100mb_250k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts_distributions_only [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_10mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts_memlimit [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_500mb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_512kb_3k_contexts [Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining (ADP only) [Profiling (ADP)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining_no_allocs (ADP only) [Profiling (ADP)] [SMP Dashboard]

Signed-off-by: Luke Steensen <luke.steensen@gmail.com>
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