fix(contrib/aws/aws-sdk-go-v2): skip _datadog attribute if batch size larger than 262144-byte payload limit

[darccio]

What does this PR do?

SNS _datadog trace context injection (about 338 bytes) was unconditionally added to every message, pushing payloads over SNS's 262,144-byte limit and causing BatchRequestTooLong errors.

Motivation

Fixes #4664.

Reviewer's Checklist

• Changed code has unit tests for its functionality at or near 100% coverage.
• New code is free of linting errors. You can check this by running make lint locally.
• New code doesn't break existing tests. You can check this by running make test locally.
• Add an appropriate team label so this PR gets put in the right place for the release notes.

Unsure? Have a question? Request a review!

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 61.66%. Comparing base (194346a) to head (9506d95).

Additional details and impacted files

see 443 files with indirect coverage changes

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[datadog-official]

🎉 All green!

❄️ No new flaky tests detected
🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 60.89% (-0.17%)

_{This comment will be updated automatically if new data arrives.
🔗 Commit SHA: 3ba0d06 | Docs | Datadog PR Page | Was this helpful? React with 👍/👎 or give us feedback!}

[darccio]

@codex review

[chatgpt-codex-connector]

💡 Codex Review

Here are some automated review suggestions for this pull request.

Reviewed commit: 9506d95b00

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[pr-commenter]

Benchmarks

Benchmark execution time: 2026-04-17 12:04:29

Comparing candidate commit 3ba0d06 in PR branch dario.castane/er/issue-4464 with baseline commit 194346a in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 270 metrics, 8 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 ----------------------------------'