Bump marocchino/sticky-pull-request-comment from 2.5.0 to 2.9.0

[dependabot[bot]]

trafficstars

Bumps marocchino/sticky-pull-request-comment from 2.5.0 to 2.9.0.

Release notes

Sourced from marocchino/sticky-pull-request-comment's releases.

v2.9.0

• Update deps
• Use node 20

v2.8.0

• Add skip_unchanged input
• Update deps

v2.7.0

Update deps. Add two output.

• previous_comment_id: "ID of previous comment, if found"
• created_comment_id: "ID of newly created comment, if any"

v2.6.2

Reverted changes in version 2.6. As a result, the base_url has been removed.

v2.6.1

Change base_url default to ${{ env.GITHUB_API_URL }}

v2.6.0

• Update deps
• Add base_url option. (default: 'https://api.github.com')

Commits

• 331f8f5 📦️ build
• 5c844f7 ⬆️ node 20
• 989f9fa Merge pull request #1236 from marocchino/dependabot/npm_and_yarn/typescript-e...
• 42b601d build(deps-dev): Bump @​typescript-eslint/parser from 6.19.0 to 6.20.0
• 627a535 Merge pull request #1227 from marocchino/dependabot/npm_and_yarn/ts-jest-29.1.2
• 85fbd23 Merge pull request #1239 from marocchino/dependabot/npm_and_yarn/types/node-2...
• 9ecb719 Merge pull request #1240 from marocchino/dependabot/npm_and_yarn/octokit/grap...
• 76f17ea Merge pull request #1238 from MauriceArikoglu/patch-1
• b11ff05 build(deps): Bump @​octokit/graphql-schema from 14.47.1 to 14.52.0
• e141788 build(deps-dev): Bump @​types/node from 20.11.5 to 20.11.14
• Additional commits viewable in compare view

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[dependabot[bot]]

The following labels could not be found: dependencies-github-actions.

[pr-commenter[bot]]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: c15754f0-f083-41e6-aad5-84fc7dc5ff35 Baseline: af760b8db40118a095e4b027d013085b9441aa56 Comparison: 6f5756ecc6c3562c3cf56a158e226009e15f712c 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	-0.32	[-6.87, +6.23]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	tcp_syslog_to_blackhole	ingress throughput	+1.04	[+0.98, +1.10]
➖	process_agent_real_time_mode	memory utilization	+0.80	[+0.75, +0.85]
➖	idle	memory utilization	+0.23	[+0.18, +0.27]
➖	process_agent_standard_check	memory utilization	+0.18	[+0.13, +0.23]
➖	otel_to_otel_logs	ingress throughput	+0.09	[-0.57, +0.76]
➖	process_agent_standard_check_with_stats	memory utilization	+0.03	[-0.02, +0.08]
➖	trace_agent_msgpack	ingress throughput	+0.02	[+0.01, +0.03]
➖	trace_agent_json	ingress throughput	+0.01	[-0.01, +0.02]
➖	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]
➖	file_to_blackhole	% cpu utilization	-0.32	[-6.87, +6.23]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.68	[-2.10, +0.74]
➖	file_tree	memory utilization	-1.34	[-1.44, -1.23]

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:

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".

[duncanpharvey]

/merge

[dd-devflow[bot]]

:steam_locomotive: MergeQueue

This merge request is not mergeable yet, because of pending checks/missing approvals. It will be added to the queue as soon as checks pass and/or get approvals. Note: if you pushed new commits since the last approval, you may need additional approval. You can remove it from the waiting list with /remove command.

Use /merge -c to cancel this operation!

[agent-platform-auto-pr[bot]]

[Fast Unit Tests Report]

On pipeline 31915181 (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-developer-experience

[dd-devflow[bot]]

:steam_locomotive: MergeQueue

Pull request added to the queue.

This build is next! (estimated merge in less than 49m)

Use /merge -c to cancel this operation!

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 1f6ae77d-3a90-407b-b704-55c41bb17d12 Baseline: 15ed45e776b2e2d3d216f1b9831eef34e649317c Comparison: 958ccc1b2cfbd790e1f929c205af5c822b53b8f2

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

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	-0.16	[-5.61, +5.30]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	basic_py_check	% cpu utilization	+1.60	[-0.87, +4.07]
➖	process_agent_standard_check	memory utilization	+0.40	[+0.35, +0.46]
➖	process_agent_standard_check_with_stats	memory utilization	+0.35	[+0.29, +0.40]
➖	pycheck_1000_100byte_tags	% cpu utilization	+0.30	[-4.64, +5.23]
➖	otel_to_otel_logs	ingress throughput	+0.24	[-0.21, +0.70]
➖	tcp_syslog_to_blackhole	ingress throughput	+0.19	[+0.11, +0.27]
➖	trace_agent_msgpack	ingress throughput	+0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.21, +0.20]
➖	process_agent_real_time_mode	memory utilization	-0.02	[-0.06, +0.02]
➖	tcp_dd_logs_filter_exclude	ingress throughput	-0.03	[-0.05, -0.01]
➖	trace_agent_json	ingress throughput	-0.03	[-0.06, +0.00]
➖	file_to_blackhole	% cpu utilization	-0.16	[-5.61, +5.30]
➖	idle	memory utilization	-0.27	[-0.31, -0.24]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.57	[-3.57, +2.42]
➖	file_tree	memory utilization	-1.01	[-1.14, -0.89]

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:

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".