datadog-agent
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Direct call to gh data to decrease usage of API
What does this PR do?
Replace call to gh
cli by usage of the content of gh event.
Motivation
Reduce call to the API (rate limitation). Now possible because MQ is not adding labels anymore, so this workflow is triggered in label addition/deletion
Additional Notes
Possible Drawbacks / Trade-offs
Describe how to test/QA your changes
Bloop Bleep... Dogbot Here
Regression Detector Results
Run ID: 164f3692-f1d0-44da-8b01-bfc494a93843 Baseline: d980332f62316915eb0205ece9e8357bfcafa6d2 Comparison: f0ed17a8e33d03b346838efce403bfdde00eab58 Total CPUs: 7
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
Experiments with missing or malformed data
- basic_py_check
Usually, this warning means that there is no usable optimization goal data for that experiment, which could be a result of misconfiguration.
No significant changes in experiment optimization goals
Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%
There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.
Experiments ignored for regressions
Regressions in experiments with settings containing erratic: true
are ignored.
perf | experiment | goal | Δ mean % | Δ mean % CI |
---|---|---|---|---|
➖ | file_to_blackhole | % cpu utilization | -0.50 | [-7.08, +6.08] |
Fine details of change detection per experiment
perf | experiment | goal | Δ mean % | Δ mean % CI |
---|---|---|---|---|
➖ | file_tree | memory utilization | +0.75 | [+0.66, +0.83] |
➖ | otel_to_otel_logs | ingress throughput | +0.36 | [-0.27, +0.98] |
➖ | process_agent_standard_check_with_stats | memory utilization | +0.07 | [+0.04, +0.10] |
➖ | process_agent_real_time_mode | memory utilization | +0.04 | [+0.01, +0.07] |
➖ | trace_agent_msgpack | ingress throughput | +0.01 | [+0.01, +0.02] |
➖ | trace_agent_json | ingress throughput | +0.00 | [-0.03, +0.03] |
➖ | uds_dogstatsd_to_api | ingress throughput | +0.00 | [-0.00, +0.00] |
➖ | tcp_dd_logs_filter_exclude | ingress throughput | +0.00 | [-0.00, +0.00] |
➖ | idle | memory utilization | -0.23 | [-0.26, -0.21] |
➖ | process_agent_standard_check | memory utilization | -0.48 | [-0.52, -0.44] |
➖ | file_to_blackhole | % cpu utilization | -0.50 | [-7.08, +6.08] |
➖ | tcp_syslog_to_blackhole | ingress throughput | -0.93 | [-0.98, -0.87] |
➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | -1.13 | [-2.56, +0.29] |
Explanation
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.
-
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.
-
Its configuration does not mark it "erratic".
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