openmetrics: fix native transformer locking to first observed metric type

[lucia-sb]

What does this PR do?

Fixes the default native OpenMetrics V2 transformer so it no longer locks onto whichever metric type it sees first for a given metric name. It now reuses native_dynamic's per-type caching, so a metric name that legitimately reports more than one type (e.g. a gauge/counter pair colliding after OpenMetrics strips the _total suffix) gets each sample routed to the correct transformer regardless of arrival order.

Adds a regression test (test_v2/test_transformers/test_native.py) covering both the plain single-type case and the gauge/_total-counter collision.

Motivation

AI-6931: several integrations (krakend, kuma, coredns v2, istio, gitlab; argocd has a separate broken custom transformer) mis-submit go_memstats_alloc_bytes because Go exposes it as both a gauge and a _total counter. OpenMetrics strips the _total suffix from counter family names, so both samples collapse into the same metric name. The default native transformer cached the first sample's type (transformer = None, set once) and reused it forever, so the gauge's value gets silently overwritten by the counter's large cumulative value, and the .count metric is never emitted.

native_dynamic already handles this correctly by caching a transformer per observed type instead of a single slot. This PR makes native — the default type for every metric not given an explicit type — share that same per-type caching, fixing the collision at the base-check level instead of requiring a native_dynamic annotation in every affected integration.

Review checklist (to be filled by reviewers)

• Feature or bugfix MUST have appropriate tests (unit, integration, e2e)
• Add qa/required if this PR needs QA validation, or qa/skip-qa if it does not. Exactly one of the two is required.
• If you need to backport this PR to another branch, you can add the backport/<branch-name> label to the PR and it will automatically open a backport PR once this one is merged

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⚠️ Warnings

🚦 1 Pipeline job failed

PR All | test / j06ca546 / SNMP     

🧪 1 Test failed in 1 job

PR All | run  

All test failures are known flaky — job may pass on retry.

❄️ Known flaky: test_e2e_snmp_listener from test_e2e_snmp_listener.py  

Needed at least 1 candidates for 'datadog.snmp.check_duration', got 0
Expected:
        MetricStub(name='datadog.snmp.check_duration', type=0, value=None, tags=['autodiscovery_subnet:172.18.0.0/28', 'device_vendor:apc', 'firmware_version:2.0.3-test', 'loader:python', 'model:APC Smart-UPS 600', 'serial_num:test_serial', 'snmp_device:172.18.0.1', 'snmp_profile:apc_ups', 'ups_name:testIdentName'], hostname=None, device=None, flush_first_value=None)
Difference to closest:
        Expected tag snmp_device:172.18.0.1
        Found snmp_device:172.18.0.2

Similar submitted:
Score   Most similar
1.00    MetricStub(name='datadog.snmp.check_duration', type=0, value=0.2207350730895996, tags=['autodiscovery_subnet:172.18.0.0/28', 'device_vendor:apc', 'firmware_version:2.0.3-test', 'loader:python', 'model:APC Smart-UPS 600', 'serial_num:test_serial', 'snmp_device:172.18.0.2', 'snmp_profile:apc_ups', 'ups_name:testIdentName'], hostname='runnervmfmtub', device=None, flush_first_value=False)
...

Not introduced in this PR.

ℹ️ Info

No other issues found (see more)

❄️ No new flaky tests detected

🔄 Datadog auto-retried 2 jobs - 2 passed on retry

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 88.12% (+0.11%)

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[dd-octo-sts]

Validation Report

All 21 validations passed.

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Validation	Description	Status
agent-reqs	Verify check versions match the Agent requirements file	✅
ci	Validate CI configuration and code coverage settings	✅
codeowners	Validate every integration has a CODEOWNERS entry	✅
config	Validate default configuration files against spec.yaml	✅
dep	Verify dependency pins are consistent and Agent-compatible	✅
http	Validate integrations use the HTTP wrapper correctly	✅
imports	Validate check imports do not use deprecated modules	✅
integration-style	Validate check code style conventions	✅
jmx-metrics	Validate JMX metrics definition files and config	✅
labeler	Validate PR labeler config matches integration directories	✅
legacy-signature	Validate no integration uses the legacy Agent check signature	✅
license-headers	Validate Python files have proper license headers	✅
licenses	Validate third-party license attribution list	✅
metadata	Validate metadata.csv metric definitions	✅
models	Validate configuration data models match spec.yaml	✅
openmetrics	Validate OpenMetrics integrations disable the metric limit	✅
package	Validate Python package metadata and naming	✅
qa-label	Validate the pull request declares whether it needs QA for the next Agent release	✅
readmes	Validate README files have required sections	✅
saved-views	Validate saved view JSON file structure and fields	✅
version	Validate version consistency between package and changelog	✅

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