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DataDog / saluki

An experimental toolkit for building telemetry data planes in Rust.
Apache License 2.0
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[APR-207] chore: add basis for building converged Datadog Agent image in CI #207

Closed tobz closed 3 weeks ago

tobz commented 3 weeks ago

Context

This PR is a simple addition of CI bits to enable us to start building a "converged" Datadog Agent image that utilizes our internal Datadog Agent image and plops ADP on top. This is the bare minimum necessary change to give us something we can deploy internally, and specifically eschews any of the necessary init system tweaks needed to integrate with s6 for running the Datadog Agent image standalone in Docker.

pr-commenter[bot] commented 3 weeks ago

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 8aa7fabe-62c4-4336-ae54-6993818407ee

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_100mb_3k_contexts_distributions_only | memory utilization | +1.88 | [+1.66, +2.10] | | | ➖ | dsd_uds_1mb_50k_contexts_memlimit | ingress throughput | +0.03 | [-0.02, +0.09] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.03 | [+0.00, +0.06] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.03 | [-0.05, +0.11] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.02 | [+0.01, +0.03] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | +0.00 | [+0.00, +0.00] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | +0.00 | [-0.04, +0.04] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | +0.00 | [-0.03, +0.03] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.02 | [-0.08, +0.05] | |

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: 394c2666-0dfd-4aee-830c-df9161a40c02

Baseline: 3b9013668b0cc916a170de1dcf5dc7e489d93551 Comparison: 7ba2f647e8215d2731fd7ddf2bd024cced9dbeaf

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 | +0.84 | [-2.45, +4.13] | | | ➖ | dsd_uds_100mb_3k_contexts_distributions_only | memory utilization | +0.70 | [+0.54, +0.87] | | | ➖ | dsd_uds_10mb_3k_contexts | ingress throughput | +0.03 | [-0.10, +0.16] | | | ➖ | dsd_uds_1mb_3k_contexts | ingress throughput | +0.01 | [-0.05, +0.07] | | | ➖ | dsd_uds_100mb_3k_contexts | ingress throughput | +0.00 | [-0.02, +0.02] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining | ingress throughput | +0.00 | [-0.00, +0.00] | | | ➖ | dsd_uds_50mb_10k_contexts_no_inlining_no_allocs | ingress throughput | -0.00 | [-0.05, +0.05] | | | ➖ | dsd_uds_100mb_250k_contexts | ingress throughput | -0.00 | [-0.28, +0.28] | | | ➖ | dsd_uds_1mb_50k_contexts | ingress throughput | -0.00 | [-0.06, +0.05] | | | ➖ | dsd_uds_512kb_3k_contexts | ingress throughput | -0.03 | [-0.10, +0.03] | | | ➖ | dsd_uds_500mb_3k_contexts | ingress throughput | -1.62 | [-1.71, -1.53] | |

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]