[ AGNTLOG-210 ] Extend the logs agent to support a cardinality level config for the tagger - #38440
[ AGNTLOG-210 ] Extend the logs agent to support a cardinality level config for the tagger #38440ddrthall wants to merge 3 commits into
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 52c62b6 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 | +0.99 | [-2.12, +4.10] | 1 | Logs |
Fine details of change detection per experiment
| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +2.88 | [+1.52, +4.23] | 1 | Logs |
| ➖ | docker_containers_cpu | % cpu utilization | +0.99 | [-2.12, +4.10] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | +0.70 | [+0.63, +0.77] | 1 | Logs bounds checks dashboard |
| ➖ | ddot_logs | memory utilization | +0.54 | [+0.45, +0.63] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +0.44 | [+0.38, +0.50] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | +0.36 | [+0.31, +0.42] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.06 | [-0.53, +0.64] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.03 | [-0.56, +0.62] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | +0.01 | [-0.61, +0.64] | 1 | Logs |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | +0.01 | [-0.03, +0.05] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.03, +0.03] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.01 | [-0.34, +0.31] | 1 | Logs |
| ➖ | ddot_metrics | memory utilization | -0.10 | [-0.22, +0.01] | 1 | Logs |
| ➖ | otlp_ingest_logs | memory utilization | -0.11 | [-0.24, +0.01] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | -0.13 | [-0.27, +0.01] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | -0.14 | [-0.76, +0.48] | 1 | Logs |
| ➖ | file_tree | memory utilization | -0.16 | [-0.20, -0.13] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.48 | [-0.53, -0.44] | 1 | Logs bounds checks dashboard |
| ➖ | quality_gate_logs | % cpu utilization | -2.17 | [-4.93, +0.58] | 1 | Logs bounds checks dashboard |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | |
| ✅ | 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 |
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_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_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_logs, 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.
Static quality checks✅ Please find below the results from static quality gates Successful checksInfo
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rtrieu
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A minor suggestion but otherwise looks good.
gabedos
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Support for a LogCardinality in the tagger looks good to me.
Curious if your team has taken into consideration the CheckTagCardinality option that is attached to checks that are autodiscovered. These checks can emit both metrics and logs. This option also allows different checks to have different levels of cardinality. #29984. Traditionally it's only been relevant to metrics since we didn't have logs supporting a configurable cardinality. Backward compatibility is likely tricky here since the default values for CheckTagCardinality and LogCardinality are different. Just something to keep in mind in the future if we want to provide the same experience for log cardinality configuration as metric cardinality configuration
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What does this PR do?
Add support for tag cardinality configuration in the Logs Agent to mirror the same functionality present in Dogstatsd. This new configuration option will be named DD_LOGS_TAG_CARDINALITY to mirror the checks/dogstatsd equivalents.
Motivation
Describe how you validated your changes
In addition to automated testing expansion, all three levels ("high", "low", and "orchestrator") were tested in a kubernetes environment to confirm the appropriate set of tags were applied to each log.
Possible Drawbacks / Trade-offs
Additional Notes