feat(metrics): add series-specific payload limit config

[rayz]

Summary

Adds ADP support for the Agent’s V2 series payload limit configuration keys:

• serializer_max_series_payload_size
• serializer_max_series_uncompressed_payload_size

These are now wired into the V2 series request builder, moved from unsupported to supported config
registry entries, and reflected in the DogStatsD config docs.

serializer_max_series_points_per_payload will not be supported as it will be removed from the Agent config.

Change Type

• Bug fix
• New feature
• Non-functional (chore, refactoring, docs)
• Performance

How did you test this PR?

Existing Unit Tests + CI

References

[datadog-datadog-prod-us1]

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⚠️ Warnings

🚦 1 Pipeline job failed

DataDog/saluki | run-benchmarks-adp     

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[pr-commenter]

Regression Detector (Agent Data Plane)

Run ID: 90c13792-0e7c-42d8-b0f7-f20d38da4d12
Baseline: 8c475ed7 · Comparison: bec8c799 · diff

Optimization Goals: ❌ 1 regression detected

experiment	goal	Δ mean %	links
dsd_uds_100mb_3k_contexts_cpu (erratic)	cpu	🔴 +12.24	metrics profiles logs

Fine details of change detection per experiment (34)

Experiments configured erratic: true are tagged (ignored) and skipped when determining which experiments regressed or improved. Experiments which are detected as erratic at runtime are tagged (erratic) to flag that the run's sample dispersion was high, but their regression / improvement signal still counts.

experiment	goal	Δ mean %	links
otlp_ingest_logs_5mb_memory (ignored)	memory	⚪ +6.15	metrics profiles logs
otlp_ingest_traces_ottl_filtering_5mb_cpu (erratic)	cpu	⚪ +0.78	metrics profiles logs
dsd_uds_500mb_3k_contexts_memory	memory	⚪ +0.65	metrics profiles logs
dsd_uds_512kb_3k_contexts_memory	memory	⚪ +0.39	metrics profiles logs
otlp_ingest_traces_ottl_transform_5mb_cpu (erratic)	cpu	⚪ +0.34	metrics profiles logs
quality_gates_rss_idle	memory	⚪ +0.22	metrics profiles logs
dsd_uds_100mb_3k_contexts_memory	memory	⚪ +0.16	metrics profiles logs
dsd_uds_1mb_3k_contexts_memory	memory	⚪ +0.11	metrics profiles logs
dsd_uds_10mb_3k_contexts_memory	memory	⚪ +0.11	metrics profiles logs
dsd_uds_500mb_3k_contexts_cpu (erratic)	cpu	⚪ +0.10	metrics profiles logs
otlp_ingest_traces_ottl_filtering_5mb_throughput	throughput	⚪ -0.02	metrics profiles logs
dsd_uds_100mb_3k_contexts_throughput	throughput	⚪ -0.01	metrics profiles logs
otlp_ingest_traces_5mb_memory	memory	⚪ +0.01	metrics profiles logs
otlp_ingest_logs_5mb_throughput (ignored)	throughput	⚪ -0.00	metrics profiles logs
dsd_uds_10mb_3k_contexts_throughput	throughput	⚪ -0.00	metrics profiles logs
dsd_uds_1mb_3k_contexts_throughput	throughput	⚪ +0.00	metrics profiles logs
dsd_uds_512kb_3k_contexts_throughput	throughput	⚪ +0.00	metrics profiles logs
otlp_ingest_traces_5mb_throughput	throughput	⚪ +0.01	metrics profiles logs
otlp_ingest_traces_ottl_transform_5mb_memory	memory	⚪ -0.02	metrics profiles logs
quality_gates_rss_dsd_heavy	memory	⚪ -0.03	metrics profiles logs
otlp_ingest_metrics_5mb_throughput	throughput	⚪ +0.03	metrics profiles logs
otlp_ingest_traces_ottl_transform_5mb_throughput	throughput	⚪ +0.07	metrics profiles logs
otlp_ingest_traces_ottl_filtering_5mb_memory	memory	⚪ -0.07	metrics profiles logs
quality_gates_rss_dsd_low	memory	⚪ -0.10	metrics profiles logs
quality_gates_rss_dsd_medium	memory	⚪ -0.15	metrics profiles logs
quality_gates_rss_dsd_ultraheavy	memory	⚪ -0.15	metrics profiles logs
otlp_ingest_logs_5mb_cpu (ignored)	cpu	⚪ -0.16	metrics profiles logs
dsd_uds_500mb_3k_contexts_throughput	throughput	⚪ +0.33	metrics profiles logs
otlp_ingest_metrics_5mb_cpu (erratic)	cpu	⚪ -0.75	metrics profiles logs
dsd_uds_512kb_3k_contexts_cpu (erratic)	cpu	⚪ -0.93	metrics profiles logs
otlp_ingest_traces_5mb_cpu (erratic)	cpu	⚪ -1.30	metrics profiles logs
otlp_ingest_metrics_5mb_memory	memory	⚪ -1.51	metrics profiles logs
dsd_uds_10mb_3k_contexts_cpu (erratic)	cpu	🟢 -6.84	metrics profiles logs
dsd_uds_1mb_3k_contexts_cpu (erratic)	cpu	🟢 -8.30	metrics profiles logs

Bounds Checks: ✅ Passed (5)

experiment	check	replicates	observed	links
quality_gates_rss_dsd_heavy	memory_usage	10/10	✅ 118 MiB ≤ 140 MiB	metrics profiles logs
quality_gates_rss_dsd_low	memory_usage	10/10	✅ 39.5 MiB ≤ 50 MiB	metrics profiles logs
quality_gates_rss_dsd_medium	memory_usage	10/10	✅ 60 MiB ≤ 75 MiB	metrics profiles logs
quality_gates_rss_dsd_ultraheavy	memory_usage	10/10	✅ 178 MiB ≤ 200 MiB	metrics profiles logs
quality_gates_rss_idle	memory_usage	10/10	✅ 26.7 MiB ≤ 40 MiB	metrics profiles logs

Explanation

A change is flagged as a regression when |Δ mean %| > 5.00% in the regressing direction for its optimization goal AND SMP marks the experiment as a regression (is_regression: true). Improvements use the matching criteria for the improving direction. Experiments configured erratic: true (tagged (ignored)) are skipped outright; experiments detected as erratic at runtime (tagged (erratic)) still count, since that flag describes sample dispersion rather than directional certainty. The Δ mean % cell is colored accordingly: 🟢 = improvement, 🔴 = regression, ⚪ = neutral. Reduction in CPU or memory is an improvement; reduction in ingress throughput is a regression.

[tobz]

So this is the main thing that strikes me as insufficient: we should be using the API-enforced limits as an upper bound (min(user_payload_size_limit, api_payload_size_limit))`.

We should never let users send payloads that risk being rejected due to exceeding size limits.

[tobz]

Also, to that end, I would change the doc comments for the config fields to say that every endpoint has an upper bound that is enforced by the API, and whatever value is specified here (as in: the user-supplied config value) will be clamped to that limit.

.. and then I'd probably also uniformly apply it to the V1 series payloads as well unless those are actually hard-coded in the Agent?