DataDog / saluki

An experimental toolkit for building telemetry data planes in Rust.
Apache License 2.0
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[APR-208] fix: properly separate bucket width from flush interval in aggregate transform #215

Closed tobz closed 3 weeks ago

tobz commented 3 weeks ago

Context

In #210, we attempted to "fix" our observed issues with the amount of output data from ADP not matching DSD by changing the bucket width (window duration) from 10 seconds to 15 seconds. This did fix the output data discrepancy, but still wasn't actually correct.

In the Datadog Agent, the bucket width is in fact 10 seconds, while the flush interval is 15 seconds.

Solution

This PR introduces a standalone setting for flush interval -- defaulting to 15 seconds -- to bring this up to snuff. We had to rework a bit of the flush logic to properly account for zero-value counters when we may be flushing multiple buckets, but overall things are a bit simpler (I think, at least) and hopefully easier to understand.

There's still some temporary data structures we use to track our progress and so on, and maybe we can optimize or eliminate needing them in the future... but for now, things work.

pr-commenter[bot] commented 3 weeks ago

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: d49a3418-6a47-4e2a-8f9d-cc13ff16ad1d

Baseline: 7.52.0 Comparison: 7.52.1

Performance changes are noted in the perf column of each table:

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 | links | |------|----------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.06 | [+0.04, +0.09] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.02 | [-0.04, +0.07] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.01 | [-0.06, +0.08] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.00 | [-0.04, +0.04] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | -0.02 | [-0.04, +0.01] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.07 | [-0.13, -0.00] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | -1.76 | [-1.98, -1.55] | |

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".
pr-commenter[bot] commented 3 weeks ago

Regression Detector (Saluki)

Regression Detector Results

Run ID: f228157b-9ce6-43a2-8cb2-b260057a457e

Baseline: 6a70c394a927a215f047c470d57b5d3f50c64ad6 Comparison: c62120b5511668b3e73e839e789203710f893b09

Performance changes are noted in the perf column of each table:

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 | links | |------|-------------------------------------------------|--------------------|----------|----------------|-------| | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +4.98 | [+1.71, +8.25] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +4.19 | [+4.05, +4.34] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.05 | [+0.02, +0.08] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | +0.01 | [-0.04, +0.05] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | -0.00 | [-0.01, +0.01] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.00 | [-0.05, +0.04] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | -0.02 | [-0.29, +0.24] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | -0.02 | [-0.08, +0.03] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | -0.05 | [-0.10, +0.00] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -0.28 | [-0.37, -0.19] | |

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".
pr-commenter[bot] commented 3 weeks ago

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]