chore(ci) update one-pipeline

[gh-worker-campaigns-3e9aa4]

This pull request updates one-pipeline to a newer version.

Recent changes:

• Use artifact-gateway to authenticate promote-oci jobs
• Allow bigger lib injection and oci package sizes
• Config registry validation improvements and fixes

Some of these changes may have already applied depending on your previous version of one-pipeline. See the libdatadog-build repository for all changes

[github-actions]

👋 Hey @DataDog/ruby-guild, please fill "Change log entry" section in the pull request description.

If changes need to be present in CHANGELOG.md you can state it this way

**Change log entry**

Yes. A brief summary to be placed into the CHANGELOG.md

(possible answers Yes/Yep/Yeah)

Or you can opt out like that

**Change log entry**

None.

(possible answers No/Nope/None)

^{Visited at: 2026-03-20 16:09:19 UTC}

[datadog-prod-us1-3]

✅ Tests

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 95.36% (+0.01%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 92b7628 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-03-20 16:40:40

Comparing candidate commit 8d5d914 in PR branch engraver-auto-campaigner/update-one-pipeline-1774022942 with baseline commit 8d5d914 in branch master.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 46 metrics, 0 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

[p-datadog]

OCI package sizes look good — both linux/amd64 and linux/arm64 are back to 27M, same as before the packaging image rebuild. Well within the 40MB guardrail.