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Allow config leaf nodes to have complex types, remove ArrayNode #30746
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Test in config_test.go now passes since a leaf can be a slice or map
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 88a940f Optimization Goals: ❌ Significant changes detected
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perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
---|---|---|---|---|---|---|
➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +2.58 | [+1.84, +3.32] | 1 | Logs |
➖ | quality_gate_idle | memory utilization | +1.14 | [+1.08, +1.21] | 1 | Logs bounds checks dashboard |
➖ | idle_all_features | memory utilization | +1.03 | [+0.89, +1.16] | 1 | Logs bounds checks dashboard |
➖ | idle | memory utilization | +0.08 | [+0.02, +0.14] | 1 | Logs bounds checks dashboard |
➖ | file_to_blackhole_300ms_latency | egress throughput | +0.04 | [-0.14, +0.22] | 1 | Logs |
➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.01, +0.01] | 1 | Logs |
➖ | file_to_blackhole_100ms_latency | egress throughput | -0.00 | [-0.22, +0.22] | 1 | Logs |
➖ | uds_dogstatsd_to_api | ingress throughput | -0.01 | [-0.11, +0.10] | 1 | Logs |
➖ | file_to_blackhole_0ms_latency | egress throughput | -0.03 | [-0.36, +0.31] | 1 | Logs |
➖ | file_to_blackhole_500ms_latency | egress throughput | -0.07 | [-0.31, +0.18] | 1 | Logs |
➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.20 | [-0.68, +0.27] | 1 | Logs |
➖ | otel_to_otel_logs | ingress throughput | -0.32 | [-1.13, +0.49] | 1 | Logs |
➖ | file_tree | memory utilization | -0.37 | [-0.52, -0.22] | 1 | Logs |
➖ | tcp_syslog_to_blackhole | ingress throughput | -0.59 | [-0.63, -0.54] | 1 | Logs |
➖ | basic_py_check | % cpu utilization | -1.49 | [-5.36, +2.38] | 1 | Logs |
➖ | quality_gate_idle_all_features | memory utilization | -3.59 | [-3.70, -3.47] | 1 | Logs bounds checks dashboard |
✅ | pycheck_lots_of_tags | % cpu utilization | -5.88 | [-9.32, -2.43] | 1 | Logs |
Bounds Checks: ❌ Failed
perf | experiment | bounds_check_name | replicates_passed | links |
---|---|---|---|---|
❌ | quality_gate_idle | memory_usage | 4/10 | bounds checks dashboard |
❌ | idle | memory_usage | 9/10 | bounds checks dashboard |
✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | |
✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | |
✅ | file_to_blackhole_300ms_latency | memory_usage | 10/10 | |
✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | |
✅ | idle_all_features | memory_usage | 10/10 | bounds checks dashboard |
✅ | quality_gate_idle_all_features | 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".
Test changes on VMUse this command from test-infra-definitions to manually test this PR changes on a VM: inv create-vm --pipeline-id=48258524 --os-family=ubuntu Note: This applies to commit f52239f |
/merge |
🚂 MergeQueue: pull request added to the queue The median merge time in Use |
What does this PR do?
In NodeTreeModel, allow leaf nodes to have complex types like map or slice. This breaks an earlier assumption in the design: that leaf values must be scalar types. UnmarshalKey handles these leafs by constructing new nodes on demand, but not inserting those nodes into the config tree.
Motivation
Simplify the design, fix the bug where the config thinks leaf with map values contains more leafs within it.
Describe how to test/QA your changes
Tests cover the change in functionality.
Possible Drawbacks / Trade-offs
Additional Notes