ci: publish docker image for system tests

[MilanGarnier]

Description

Adds a CI job at dd-trace-php/.gitlab/generate-package.php which pushes the build to github's container registry (similarly to what already exists for prod builds). This is necessary to enable LIBRARY_TARGET_BRANCH to work for the PHP target in utils/scripts/load-binary.sh. (mimicking what already exists for dd-trace-dotnet)

The endgoal is to have DataDog/system-tests#7209 picking up the right branch

Reviewer checklist

[datadog-datadog-prod-us1]

 

✨ Fix all issues with BitsAI

⚠️ Warnings

🚦 11 Pipeline jobs failed

DataDog/apm-reliability/dd-trace-php | ASAN test_c: [8.4, arm64]     

DataDog/apm-reliability/dd-trace-php | ASAN test_c: [8.5, arm64]     

DataDog/apm-reliability/dd-trace-php | Loader test on arm64 libc: [8.4, nts, arm64]     

View all 11 failed jobs.

ℹ️ Info

No other issues found (see more)

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 54.08% (-0.04%)

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[chatgpt-codex-connector]

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Reviewed commit: c7decf82b6

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[realFlowControl]

I just recently learned that https://github.com/DataDog/public-images exists, could this do the syncing of the image for us?

[MilanGarnier]

@realFlowControl I didn't know publish-images either, but from what I understand, the tool seems to be centered aroung publishing releases across various sources, whereas what I want to do here is to push once a build, exclusively for system-tests to use. (but I'm really not an expert here)

[pr-commenter]

Benchmarks [ tracer ]

Benchmark execution time: 2026-06-26 10:07:01

Comparing candidate commit 1032cd9 in PR branch milan.garnier/publish-ci-builds with baseline commit 81891ec in branch master.

Found 1 performance improvements and 0 performance regressions! Performance is the same for 193 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 ----------------------------------'

scenario:EmptyFileBench/benchEmptyFileDdprof-opcache

• 🟩 execution_time [-408.018µs; -139.182µs] or [-11.232%; -3.831%]