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[AGENTRUN-162] Disable X25519Kyber768Draft00 in the agent #34626
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Uncompressed package size comparisonComparison with ancestor Diff per package
Decision✅ Passed |
Static quality checks ✅Please find below the results from static quality gates Successful checksInfo
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 0b4f8a7 Optimization Goals: ✅ No significant changes detected
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perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
---|---|---|---|---|---|---|
➖ | quality_gate_idle_all_features | memory utilization | +0.25 | [+0.19, +0.31] | 1 | Logs bounds checks dashboard |
➖ | file_tree | memory utilization | +0.25 | [+0.20, +0.30] | 1 | Logs |
➖ | tcp_syslog_to_blackhole | ingress throughput | +0.16 | [+0.10, +0.22] | 1 | Logs |
➖ | file_to_blackhole_500ms_latency | egress throughput | +0.13 | [-0.66, +0.92] | 1 | Logs |
➖ | quality_gate_logs | % cpu utilization | +0.04 | [-2.83, +2.91] | 1 | Logs |
➖ | file_to_blackhole_100ms_latency | egress throughput | +0.01 | [-0.67, +0.69] | 1 | Logs |
➖ | file_to_blackhole_0ms_latency_http2 | egress throughput | +0.01 | [-0.82, +0.84] | 1 | Logs |
➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.01, +0.02] | 1 | Logs |
➖ | file_to_blackhole_0ms_latency_http1 | egress throughput | +0.00 | [-0.79, +0.79] | 1 | Logs |
➖ | file_to_blackhole_0ms_latency | egress throughput | +0.00 | [-0.86, +0.86] | 1 | Logs |
➖ | file_to_blackhole_300ms_latency | egress throughput | -0.00 | [-0.63, +0.62] | 1 | Logs |
➖ | uds_dogstatsd_to_api | ingress throughput | -0.01 | [-0.29, +0.27] | 1 | Logs |
➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | -0.36 | [-0.83, +0.12] | 1 | Logs |
➖ | quality_gate_idle | memory utilization | -0.40 | [-0.43, -0.36] | 1 | Logs bounds checks dashboard |
➖ | file_to_blackhole_1000ms_latency | egress throughput | -0.56 | [-1.34, +0.21] | 1 | Logs |
➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -2.16 | [-3.11, -1.22] | 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:
-
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_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_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
/merge |
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The median merge time in
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What does this PR do?
Fix #34323.
#34481 added the
godebug
directive to disable tlskyber experiment by default, however it seems due to using ago.work
the directive in thego.mod
was ignored...Some local testing indicates that setting the directive in the
go.work
works as expected.Motivation
Fix issues with AWS Network Firewall.
Describe how you validated your changes
I don't have a setup with AWS Network Firewall at hand so I used a custom version of Go to check whether the GODEBUG directive was considered.
I also tried using delve, installing the agent, downloading debug symbols, setting up delve config to indicate the location of debug symbols, and finally attaching to the running agent to see the set of algorithms used.
dlv attach `pgrep -f '/opt/datadog-agent/bin/agent/agent run'`
Here are the delve instructions:
With 7.63.2:
With 7.63.3~rc.1:
Possible Drawbacks / Trade-offs
Additional Notes