ci: increase k8s resources for benchmark PR comment job

[brettlangdon]

Increasing limits to help improve runtime of this job. Right now it takes around 5 minutes.

Checklist

• PR author has checked that all the criteria below are met
• The PR description includes an overview of the change
• The PR description articulates the motivation for the change
• The change includes tests OR the PR description describes a testing strategy
• The PR description notes risks associated with the change, if any
• Newly-added code is easy to change
• The change follows the library release note guidelines
• The change includes or references documentation updates if necessary
• Backport labels are set (if applicable)

Reviewer Checklist

• Reviewer has checked that all the criteria below are met
• Title is accurate
• All changes are related to the pull request's stated goal
• Avoids breaking API changes
• Testing strategy adequately addresses listed risks
• Newly-added code is easy to change
• Release note makes sense to a user of the library
• If necessary, author has acknowledged and discussed the performance implications of this PR as reported in the benchmarks PR comment
• Backport labels are set in a manner that is consistent with the release branch maintenance policy

[github-actions]

CODEOWNERS have been resolved as:

.gitlab/benchmarks.yml                                                  @DataDog/python-guild @DataDog/apm-core-python

[datadog-dd-trace-py-rkomorn]

Datadog Report

Branch report: brettlangdon/bp.pr.comment.limits
Commit report: da1cb4e
Test service: dd-trace-py

✅ 0 Failed, 130 Passed, 1468 Skipped, 4m 58.59s Total duration (35m 36.33s time saved)

[pr-commenter]

Benchmarks

Benchmark execution time: 2025-01-23 16:28:10

Comparing candidate commit da1cb4e in PR branch brettlangdon/bp.pr.comment.limits with baseline commit ff41c13 in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 394 metrics, 2 unstable metrics.

[brettlangdon]

This didn't end up improving the runtime by enough, we'll follow-up with other performance optimizations approaches in the future.