add github workflow link to pr body

[sabrina-datadog]

What does this PR do?

add github workflow link to automated bump integrations core PR

Motivation

to easily link back to the workflow that generated the PR

Describe how you validated your changes

manually triggered workflow and checked generated PR's body

Possible Drawbacks / Trade-offs

Additional Notes

[agent-platform-auto-pr]

Static quality checks ✅

Please find below the results from static quality gates

Info

Result	Quality gate	On disk size	On disk size limit	On wire size	On wire size limit
✅	static_quality_gate_agent_deb_amd64	844.75MiB	858.45MiB	203.55MiB	214.3MiB
✅	static_quality_gate_docker_agent_amd64	929.15MiB	942.69MiB	310.7MiB	321.56MiB

[agent-platform-auto-pr]

[Fast Unit Tests Report]

On pipeline 55046150 (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

[agent-platform-auto-pr]

Uncompressed package size comparison

Comparison with ancestor 281ac365fd70635e764055933e8664d35be5c253

Diff per package

package	diff	status	size	ancestor	threshold
datadog-agent-amd64-deb	0.00MB	✅	873.45MB	873.45MB	0.50MB
datadog-agent-x86_64-rpm	0.00MB	✅	883.19MB	883.19MB	0.50MB
datadog-agent-x86_64-suse	0.00MB	✅	883.19MB	883.19MB	0.50MB
datadog-agent-arm64-deb	0.00MB	✅	861.34MB	861.34MB	0.50MB
datadog-agent-aarch64-rpm	0.00MB	✅	871.06MB	871.06MB	0.50MB
datadog-dogstatsd-amd64-deb	0.00MB	✅	59.09MB	59.09MB	0.50MB
datadog-dogstatsd-x86_64-rpm	0.00MB	✅	59.17MB	59.17MB	0.50MB
datadog-dogstatsd-x86_64-suse	0.00MB	✅	59.17MB	59.17MB	0.50MB
datadog-dogstatsd-arm64-deb	0.00MB	✅	56.56MB	56.56MB	0.50MB
datadog-heroku-agent-amd64-deb	0.00MB	✅	445.70MB	445.70MB	0.50MB
datadog-iot-agent-amd64-deb	0.00MB	✅	86.23MB	86.23MB	0.50MB
datadog-iot-agent-x86_64-rpm	0.00MB	✅	86.30MB	86.30MB	0.50MB
datadog-iot-agent-x86_64-suse	0.00MB	✅	86.30MB	86.30MB	0.50MB
datadog-iot-agent-arm64-deb	0.00MB	✅	82.50MB	82.50MB	0.50MB
datadog-iot-agent-aarch64-rpm	0.00MB	✅	82.57MB	82.57MB	0.50MB

Decision

✅ Passed

[cit-pr-commenter]

Regression Detector

Regression Detector Results

Metrics dashboard
Target profiles
Run ID: be4dcc70-232d-47c9-bca2-0b1ca8dbee56

Baseline: 281ac36
Comparison: 0f2361f
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	+1.23	[+1.14, +1.31]	1	Logs
➖	file_to_blackhole_500ms_latency	egress throughput	+0.09	[-0.69, +0.88]	1	Logs
➖	file_to_blackhole_1000ms_latency_linear_load	egress throughput	+0.08	[-0.40, +0.55]	1	Logs
➖	quality_gate_logs	% cpu utilization	+0.07	[-2.97, +3.11]	1	Logs
➖	file_to_blackhole_300ms_latency	egress throughput	+0.02	[-0.62, +0.66]	1	Logs
➖	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.28, +0.29]	1	Logs
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.01, +0.01]	1	Logs
➖	file_to_blackhole_0ms_latency	egress throughput	-0.00	[-0.85, +0.84]	1	Logs
➖	file_to_blackhole_0ms_latency_http2	egress throughput	-0.03	[-0.84, +0.78]	1	Logs
➖	file_to_blackhole_100ms_latency	egress throughput	-0.04	[-0.70, +0.62]	1	Logs
➖	file_to_blackhole_0ms_latency_http1	egress throughput	-0.05	[-0.87, +0.76]	1	Logs
➖	file_to_blackhole_1000ms_latency	egress throughput	-0.11	[-0.89, +0.67]	1	Logs
➖	file_tree	memory utilization	-0.19	[-0.25, -0.13]	1	Logs
➖	quality_gate_idle_all_features	memory utilization	-0.29	[-0.35, -0.22]	1	Logs bounds checks dashboard
➖	quality_gate_idle	memory utilization	-0.48	[-0.51, -0.44]	1	Logs bounds checks dashboard
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.73	[-1.59, +0.14]	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:

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 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_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_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.

[sabrina-datadog]

/merge

[dd-devflow]

Devflow running: /merge

View all feedbacks in Devflow UI.

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2025-02-06 15:30:20 UTC ℹ️ MergeQueue: pull request added to the queue

The median merge time in main is 29m.

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2025-02-06 16:14:46 UTC ℹ️ MergeQueue: This merge request was merged