Otlp log smp 3

[andrewqian2001datadog]

Summary

Change Type

• Bug fix
• New feature
• Non-functional (chore, refactoring, docs)
• Performance

How did you test this PR?

References

[pr-commenter]

Regression Detector (Agent Data Plane)

Regression Detector Results

Run ID: 698cd37a-9f4e-4668-abe4-706886585946

Baseline: e692e12
Comparison: 8ee687d
Diff

Optimization Goals: ❌ Regression(s) detected

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
❌	otlp_ingest_logs_adp_5con_5mib	memory utilization	+13.52	[+12.88, +14.16]	1
❌	otlp_ingest_logs_adp_1con_2mib	memory utilization	+5.51	[+5.24, +5.78]	1
✅	otlp_ingest_logs_adp_5con_2mib	memory utilization	-7.60	[-7.90, -7.30]	1
✅	otlp_ingest_logs_adp_1con_5mib	memory utilization	-17.14	[-17.88, -16.40]	1

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
❌	otlp_ingest_logs_adp_5con_5mib	memory utilization	+13.52	[+12.88, +14.16]	1
❌	otlp_ingest_logs_adp_1con_2mib	memory utilization	+5.51	[+5.24, +5.78]	1
➖	otlp_ingest_logs_adp_5con_1mib	memory utilization	+2.14	[+1.95, +2.34]	1
➖	otlp_ingest_logs_adp_1con_1mib	memory utilization	+1.00	[+0.76, +1.25]	1
✅	otlp_ingest_logs_adp_5con_2mib	memory utilization	-7.60	[-7.90, -7.30]	1
✅	otlp_ingest_logs_adp_1con_5mib	memory utilization	-17.14	[-17.88, -16.40]	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 (Agent Data Plane w/ Checks)

Regression Detector Results

Run ID: 3ae984d8-640b-4831-ac42-b12c0af2d180

Baseline: e692e12
Comparison: 8ee687d
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	quality_gates_rss_idle	memory utilization	+0.28	[+0.26, +0.30]	1
➖	quality_gates_rss_basic	memory utilization	-0.19	[-0.22, -0.16]	1

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	links
✅	quality_gates_rss_basic	memory_usage	10/10
✅	quality_gates_rss_idle	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".

[pr-commenter]

Regression Detector Links

ADP Experiment Result Links

experiment	link(s)
dsd_uds_100mb_3k_contexts_throughput	[Profiling] [SMP Dashboard]
dsd_uds_10mb_3k_contexts_throughput	[Profiling] [SMP Dashboard]
dsd_uds_1mb_3k_contexts_throughput	[Profiling] [SMP Dashboard]
dsd_uds_500mb_3k_contexts_throughput	[Profiling] [SMP Dashboard]
dsd_uds_512kb_3k_contexts_throughput	[Profiling] [SMP Dashboard]
otlp_ingest_logs_adp	[Profiling] [SMP Dashboard]
quality_gates_rss_dsd_heavy	[Profiling] [SMP Dashboard]
quality_gates_rss_dsd_low	[Profiling] [SMP Dashboard]
quality_gates_rss_dsd_medium	[Profiling] [SMP Dashboard]
quality_gates_rss_dsd_ultraheavy	[Profiling] [SMP Dashboard]
quality_gates_rss_idle	[Profiling] [SMP Dashboard]

ADP && Checks Experiment Result Links

experiment	link(s)
quality_gates_rss_basic	[Profiling] [SMP Dashboard]
quality_gates_rss_idle	[Profiling] [SMP Dashboard]