apm: add version checking for stats obfuscation to avoid double obfus… #33765
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Test changes on VMUse this command from test-infra-definitions to manually test this PR changes on a VM: inv aws.create-vm --pipeline-id=57554088 --os-family=ubuntuNote: This applies to commit 0ee8482 |
Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: fbecaa3 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | file_to_blackhole_500ms_latency | egress throughput | +0.04 | [-0.75, +0.82] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | +0.02 | [-0.27, +0.31] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.02 | [-0.66, +0.70] | 1 | Logs |
| ➖ | file_to_blackhole_300ms_latency | egress throughput | +0.01 | [-0.61, +0.64] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.02, +0.03] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.00 | [-0.85, +0.86] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http1 | egress throughput | -0.00 | [-0.80, +0.80] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http2 | egress throughput | -0.01 | [-0.80, +0.77] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | -0.02 | [-0.07, +0.04] | 1 | Logs bounds checks dashboard |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | -0.10 | [-0.17, -0.04] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | -0.24 | [-0.71, +0.22] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.31 | [-1.09, +0.47] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | -0.41 | [-0.45, -0.38] | 1 | Logs bounds checks dashboard |
| ➖ | file_tree | memory utilization | -0.75 | [-0.81, -0.68] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -0.75 | [-1.64, +0.13] | 1 | Logs |
| ➖ | quality_gate_logs | % cpu utilization | -2.61 | [-5.47, +0.25] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency_linear_load | 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_300ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_300ms_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 | |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | |
| ✅ | quality_gate_logs | memory_usage | 10/10 |
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_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.
- 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.
Uncompressed package size comparisonComparison with ancestor Size reduction summary
Diff per package
Decision✅ Passed |
Static quality checks ✅Please find below the results from static quality gates Successful checksInfo
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Co-authored-by: DeForest Richards <56796055+drichards-87@users.noreply.github.com>
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…cating
What does this PR do?
Checks that incoming stats payloads have not already been obfuscated as double obfuscation leads to altered resource names that aren't as useful (and could result in unexpected changes breaking monitors/dashboards)
We will expose an "obfuscation" version via the /info endpoint that tracers can use to determine if it safe for them to obfuscate e.g. DataDog/dd-trace-go#3155
Motivation
A few points here:
Describe how you validated your changes
I updated relevant tests here and also performed a manual test using the PR here DataDog/dd-trace-go#3155 on the go tracer. I verified that an incoming redis stats payload will not be double obfuscated and appears correctly in the Datadog UI.
Possible Drawbacks / Trade-offs
This adds a bit of complexity around the choice to obfuscate, but should be non-breaking as it is only enabled by a new incoming header for these payloads.
Additional Notes