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Ensure profiling is fine-grained in the Regression Detector #20081

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merged 2 commits into from
Oct 12, 2023

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@blt blt commented Oct 12, 2023

What does this PR do?

This commit updates the environment flags on our experiments to ensure that profiling runs are fine grained through the whole of the run. Updated with reference to the ongoing investigation in #19990

REF SMPTNG-12

This commit updates the environment flags on our experiments to ensure that
profiling runs are fine grained through the whole of the run. Updated with
reference to the ongoing investigation in #19990

REF SMPTNG-12

Signed-off-by: Brian L. Troutwine <[email protected]>
@blt blt added changelog/no-changelog [deprecated] qa/skip-qa - use other qa/ labels [DEPRECATED] Please use qa/done or qa/no-code-change to skip creating a QA card team/single-machine-performance Single Machine Performance labels Oct 12, 2023
@blt blt added this to the 7.50.0 milestone Oct 12, 2023
@blt blt requested a review from a team as a code owner October 12, 2023 00:28
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Regression Detector Results

Run ID: 34af9565-fbbc-4c6e-9109-303efd80c342
Baseline: 6b37725
Comparison: fade466
Total datadog-agent CPUs: 7

Explanation

A regression test is an integrated performance test for datadog-agent in a repeatable rig, with varying configuration for datadog-agent. What follows is a statistical summary of a brief datadog-agent run for each configuration across SHAs given above. The goal of these tests are to determine quickly if datadog-agent performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
file_tree egress throughput +9.16 [+6.96, +11.37] 100.00%
tcp_syslog_to_blackhole ingress throughput +1.12 [+0.98, +1.26] 100.00%
otel_to_otel_logs ingress throughput +0.20 [-1.40, +1.80] 16.16%
uds_dogstatsd_to_api_nodist_200MiB ingress throughput +0.15 [+0.04, +0.26] 97.49%
trace_agent_msgpack ingress throughput +0.01 [-0.10, +0.13] 17.18%
tcp_dd_logs_filter_exclude ingress throughput +0.01 [-0.05, +0.07] 26.34%
uds_dogstatsd_to_api_nodist_32MiB ingress throughput +0.00 [-0.13, +0.13] 3.54%
trace_agent_json ingress throughput +0.00 [-0.13, +0.13] 0.33%
file_to_blackhole egress throughput +0.00 [-1.38, +1.38] 0.00%
uds_dogstatsd_to_api_nodist_100MiB ingress throughput -0.00 [-0.13, +0.13] 0.33%
uds_dogstatsd_to_api_nodist_64MiB ingress throughput -0.00 [-0.13, +0.13] 0.82%
uds_dogstatsd_to_api_nodist_16MiB ingress throughput -0.01 [-0.13, +0.12] 7.21%
uds_dogstatsd_to_api_nodist_1MiB ingress throughput -0.01 [-0.02, -0.00] 94.47%
uds_dogstatsd_to_api ingress throughput -1.10 [-3.17, +0.98] 61.59%

@blt blt merged commit 2a2ba63 into main Oct 12, 2023
@blt blt deleted the smp_profiling_flags branch October 12, 2023 15:25
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