[AGENTRUN-673] Add mlx5_core network check metrics#40326
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| queueTag = "cpu:" + cpuNum | ||
| newKey = strings.Join(parts[1:], "_") | ||
| metricPrefix = ".cpu." | ||
| continueCase = false |
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We never told the parsing to halt when it found a matching queue name format
| // we already guard against parsing unsupported NICs | ||
| queueMetrics := ethtoolMetricNames[driverName] | ||
| // skip queues metrics we don't support for the NIC | ||
| if !slices.Contains(queueMetrics, newKey) { |
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we were only filtering global metrics but not queue metrics, this led to many additional metrics that the python check does not submit
nathan-b
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Seems generally reasonable to me, and I love all the extra testing! A couple of comments that you can take or ignore as you see fit :)
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 8846a8e Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | docker_containers_cpu | % cpu utilization | -0.20 | [-3.37, +2.96] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | quality_gate_metrics_logs | memory utilization | +1.63 | [+1.27, +1.98] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_logs | % cpu utilization | +1.36 | [-1.40, +4.12] | 1 | Logs bounds checks dashboard |
| ➖ | otlp_ingest_logs | memory utilization | +0.27 | [+0.13, +0.42] | 1 | Logs |
| ➖ | file_tree | memory utilization | +0.24 | [+0.21, +0.28] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | +0.14 | [+0.10, +0.18] | 1 | Logs bounds checks dashboard |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.12 | [-0.46, +0.69] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.09 | [-0.51, +0.68] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.06 | [-0.54, +0.66] | 1 | Logs |
| ➖ | ddot_metrics | memory utilization | +0.06 | [-0.14, +0.26] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.01 | [-0.08, +0.10] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | -0.00 | [-0.60, +0.59] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | -0.01 | [-0.16, +0.15] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.01 | [-0.05, +0.02] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.06 | [-0.13, +0.01] | 1 | Logs |
| ➖ | docker_containers_cpu | % cpu utilization | -0.20 | [-3.37, +2.96] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | -0.22 | [-0.26, -0.18] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.30 | [-0.33, -0.27] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_logs | memory utilization | -0.64 | [-0.74, -0.53] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | -0.64 | [-0.79, -0.49] | 1 | Logs |
Bounds Checks: ❌ Failed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ❌ | docker_containers_cpu | simple_check_run | 9/10 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | |
| ❌ | docker_containers_memory | simple_check_run | 8/10 | |
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_100ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | cpu_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_metrics_logs | memory_usage | 10/10 | bounds checks dashboard |
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:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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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.
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Its configuration does not mark it "erratic".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check cpu_usage: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_metrics_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
Static quality checks✅ Please find below the results from static quality gates Successful checksInfo
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### What does this PR do? The mlx5_core NIC metrics were added to the [python network check](DataDog/integrations-core#20481) after we had ported the ethtool parsing over so these were not being sent in our Azure staging clusters. This PR adds support for parsing those stats and comprehensive unit tests for the ethtool metrics in general. ### Motivation ### Describe how you validated your changes (if not by through tests) * Thorough unit tests * Will deploy on staging to confirm ### Possible Drawbacks / Trade-offs (cherry picked from commit decde86)
…40349) Backport decde86 from #40326. ___ ### What does this PR do? The mlx5_core NIC metrics were added to the [python network check](DataDog/integrations-core#20481) after we had ported the ethtool parsing over so these were not being sent in our Azure staging clusters. This PR adds support for parsing those stats and comprehensive unit tests for the ethtool metrics in general. ### Motivation ### Describe how you validated your changes (if not by through tests) * Thorough unit tests * Will deploy on staging to confirm ### Possible Drawbacks / Trade-offs Co-authored-by: Jeremy Hanna <[email protected]>
What does this PR do?
The mlx5_core NIC metrics were added to the python network check after we had ported the ethtool parsing over so these were not being sent in our Azure staging clusters.
This PR adds support for parsing those stats and comprehensive unit tests for the ethtool metrics in general.
Motivation
Describe how you validated your changes (if not by through tests)
Possible Drawbacks / Trade-offs