chore: Add pull request template

[jszwedko]

Borrowed the one from vectordotdev/vector and adapted it.

[pr-commenter]

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: a4c35678-8a37-4c2e-ab78-4e040adb45a8

Baseline: 7.55.2
Comparison: 7.55.3

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	dsd_uds_1mb_3k_contexts	ingress throughput	+0.03	[-0.00, +0.07]	1
➖	dsd_uds_1mb_50k_contexts	ingress throughput	+0.02	[-0.00, +0.04]	1
➖	dsd_uds_1mb_50k_contexts_memlimit	ingress throughput	+0.02	[-0.01, +0.05]	1
➖	dsd_uds_100mb_250k_contexts	ingress throughput	+0.02	[-0.03, +0.06]	1
➖	dsd_uds_100mb_3k_contexts	ingress throughput	+0.01	[-0.02, +0.03]	1
➖	dsd_uds_500mb_3k_contexts	ingress throughput	-0.00	[-0.01, +0.00]	1
➖	dsd_uds_10mb_3k_contexts	ingress throughput	-0.01	[-0.03, +0.00]	1
➖	dsd_uds_512kb_3k_contexts	ingress throughput	-0.05	[-0.10, -0.00]	1
➖	dsd_uds_100mb_3k_contexts_distributions_only	memory utilization	-0.95	[-1.12, -0.77]	1

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".

[pr-commenter]

Regression Detector (Saluki)

Regression Detector Results

Run ID: cccd5d3e-6d3e-4781-86d0-35802fb00b8a

Baseline: 9f2b116
Comparison: d2c6cc9
Diff

❌ Experiments with missing or malformed data

This is a critical error. No usable optimization goal data was produced by the listed experiments. This may be a result of misconfiguration. Ping #single-machine-performance and we can help out.

• dsd_uds_100mb_250k_contexts
• dsd_uds_100mb_3k_contexts
• dsd_uds_100mb_3k_contexts_distributions_only
• dsd_uds_10mb_3k_contexts
• dsd_uds_1mb_3k_contexts
• dsd_uds_1mb_50k_contexts
• dsd_uds_1mb_50k_contexts_memlimit
• dsd_uds_500mb_3k_contexts
• dsd_uds_50mb_10k_contexts_no_inlining
• dsd_uds_50mb_10k_contexts_no_inlining_no_allocs
• dsd_uds_512kb_3k_contexts

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links

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".

[pr-commenter]

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]