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feat(dependabot): Simplify dependabot configuration #33063

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@chouetz chouetz commented Jan 17, 2025

What does this PR do?

Remove the duplicate entries for the gomod package ecosystem (except for internal/tools for security reason according to the comment)

Motivation

Improve the capacity from dependabot to keep our dependencies up-to-date with a simpler configuration.

Describe how you validated your changes

Possible Drawbacks / Trade-offs

Additional Notes

@chouetz chouetz requested a review from a team as a code owner January 17, 2025 11:16
@chouetz chouetz added changelog/no-changelog qa/no-code-change No code change in Agent code requiring validation labels Jan 17, 2025
@github-actions github-actions bot added the short review PR is simple enough to be reviewed quickly label Jan 17, 2025
@chouetz chouetz force-pushed the nschweitzer/dependabot_rules branch from 676ef23 to 65b996a Compare January 17, 2025 11:17
@github-actions github-actions bot added medium review PR review might take time and removed short review PR is simple enough to be reviewed quickly labels Jan 17, 2025
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[Fast Unit Tests Report]

On pipeline 53296177 (CI Visibility). The following jobs did not run any unit tests:

Jobs:
  • tests_deb-arm64-py3
  • tests_deb-x64-py3
  • tests_flavor_dogstatsd_deb-x64
  • tests_flavor_heroku_deb-x64
  • tests_flavor_iot_deb-x64
  • tests_rpm-arm64-py3
  • tests_rpm-x64-py3
  • tests_windows-x64

If you modified Go files and expected unit tests to run in these jobs, please double check the job logs. If you think tests should have been executed reach out to #agent-devx-help

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Uncompressed package size comparison

Comparison with ancestor 736a4fe7673efc7f649f17bfe14162f700067116

Diff per package
package diff status size ancestor threshold
datadog-dogstatsd-amd64-deb 0.00MB 58.83MB 58.83MB 0.50MB
datadog-dogstatsd-x86_64-rpm 0.00MB 58.91MB 58.91MB 0.50MB
datadog-dogstatsd-x86_64-suse 0.00MB 58.91MB 58.91MB 0.50MB
datadog-dogstatsd-arm64-deb 0.00MB 56.34MB 56.34MB 0.50MB
datadog-iot-agent-amd64-deb 0.00MB 93.86MB 93.86MB 0.50MB
datadog-iot-agent-x86_64-rpm 0.00MB 93.93MB 93.93MB 0.50MB
datadog-iot-agent-x86_64-suse 0.00MB 93.93MB 93.93MB 0.50MB
datadog-iot-agent-arm64-deb 0.00MB 89.92MB 89.92MB 0.50MB
datadog-iot-agent-aarch64-rpm 0.00MB 89.99MB 89.99MB 0.50MB
datadog-agent-aarch64-rpm -50.60MB 947.83MB 998.42MB 0.50MB
datadog-agent-arm64-deb -50.65MB 938.13MB 988.78MB 0.50MB
datadog-agent-x86_64-rpm -54.00MB 960.50MB 1014.50MB 0.50MB
datadog-agent-x86_64-suse -54.00MB 960.50MB 1014.50MB 0.50MB
datadog-agent-amd64-deb -54.05MB 950.78MB 1004.83MB 0.50MB
datadog-heroku-agent-amd64-deb -54.05MB 478.52MB 532.57MB 0.50MB

Decision

✅ Passed

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Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: c6fc941e-386d-4763-be2b-f231a0ccd3b8

Baseline: 736a4fe
Comparison: 65b996a
Diff

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI trials links
tcp_syslog_to_blackhole ingress throughput +1.25 [+1.18, +1.31] 1 Logs
file_to_blackhole_1000ms_latency egress throughput +0.33 [-0.45, +1.10] 1 Logs
file_to_blackhole_0ms_latency_http2 egress throughput +0.04 [-0.86, +0.94] 1 Logs
file_to_blackhole_300ms_latency egress throughput +0.02 [-0.61, +0.66] 1 Logs
file_to_blackhole_0ms_latency egress throughput +0.01 [-0.87, +0.90] 1 Logs
uds_dogstatsd_to_api ingress throughput +0.00 [-0.11, +0.12] 1 Logs
tcp_dd_logs_filter_exclude ingress throughput -0.00 [-0.01, +0.01] 1 Logs
file_to_blackhole_0ms_latency_http1 egress throughput -0.01 [-0.95, +0.93] 1 Logs
quality_gate_idle memory utilization -0.01 [-0.06, +0.03] 1 Logs bounds checks dashboard
file_to_blackhole_100ms_latency egress throughput -0.05 [-0.76, +0.66] 1 Logs
quality_gate_idle_all_features memory utilization -0.17 [-0.27, -0.07] 1 Logs bounds checks dashboard
file_to_blackhole_500ms_latency egress throughput -0.19 [-0.97, +0.59] 1 Logs
file_to_blackhole_1000ms_latency_linear_load egress throughput -0.20 [-0.67, +0.27] 1 Logs
quality_gate_logs % cpu utilization -0.43 [-3.63, +2.77] 1 Logs
file_tree memory utilization -0.86 [-1.01, -0.72] 1 Logs
uds_dogstatsd_to_api_cpu % cpu utilization -0.87 [-1.57, -0.18] 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 memory_usage 10/10 bounds checks dashboard
quality_gate_idle_all_features memory_usage 10/10 bounds checks dashboard
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:

  1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

  2. 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.

  3. Its configuration does not mark it "erratic".

CI Pass/Fail Decision

Passed. All Quality Gates passed.

  • quality_gate_idle_all_features, 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 memory_usage: 10/10 replicas passed. Gate passed.
  • quality_gate_idle, bounds check memory_usage: 10/10 replicas passed. Gate passed.

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