cleaner reporting on which metrics implementation is used in the test harness worker

Author: chrishagglund-ship-it

harness/main.py

@@ -71,12 +71,9 @@ def main() -> None:
 
     metrics_port = env_int_or_default("HARNESS_METRICS_PORT", 9991)
     metrics_settings = MetricsSettings(http_port=metrics_port)
-    print(f"Prometheus metrics will be served on port {metrics_port}")
 
-    # Main-process MetricsCollector: writes workflow-client / HTTP metrics into
-    # the shared PROMETHEUS_MULTIPROC_DIR so they merge with worker subprocess
-    # metrics in the exported /metrics payload.
     metrics_collector = create_metrics_collector(metrics_settings)
+    print(f"Prometheus metrics server started on port {metrics_port} ({metrics_collector.collector_name()} metrics)")
     clients = OrkesClients(configuration, metrics_collector=metrics_collector)
 
     register_metadata(clients)

src/conductor/client/telemetry/canonical_metrics_collector.py

@@ -29,6 +29,9 @@ class CanonicalMetricsCollector(MetricsCollectorBase):
     def __init__(self, settings: MetricsSettings):
         super().__init__(settings)
 
+    def collector_name(self) -> str:
+        return "canonical"
+
     # ------------------------------------------------------------------
     # Counters
     # ------------------------------------------------------------------

src/conductor/client/telemetry/legacy_metrics_collector.py

@@ -26,6 +26,9 @@ def __init__(self, settings: MetricsSettings):
         self.quantile_metrics: Dict[str, Any] = {}
         self.quantile_data: Dict[str, deque] = {}
 
+    def collector_name(self) -> str:
+        return "legacy"
+
     # ------------------------------------------------------------------
     # Counters
     # ------------------------------------------------------------------

src/conductor/client/telemetry/metrics_collector_base.py

@@ -363,6 +363,11 @@ def _get_histogram(self, name, documentation, labelnames, buckets=None):
     # Subclasses implement each with real logic or pass (no-op).
     # =========================================================================
 
+    @abc.abstractmethod
+    def collector_name(self) -> str:
+        """Return the name of this collector implementation ('legacy', 'canonical')."""
+        ...
+
     @abc.abstractmethod
     def increment_task_poll(self, task_type: str) -> None: ...
 

tests/unit/telemetry/test_metrics_factory.py

@@ -61,6 +61,19 @@ def test_canonical_takes_priority_over_legacy(self):
         collector = create_metrics_collector(self.settings)
         self.assertIsInstance(collector, CanonicalMetricsCollector)
 
+    def test_legacy_collector_name(self):
+        """LegacyMetricsCollector.collector_name() returns 'legacy'."""
+        collector = create_metrics_collector(self.settings)
+        self.assertEqual(collector.collector_name(), "legacy")
+
+    def test_canonical_collector_name(self):
+        """CanonicalMetricsCollector.collector_name() returns 'canonical'."""
+        os.environ["WORKER_CANONICAL_METRICS"] = "true"
+        collector = create_metrics_collector(
+            MetricsSettings(directory=tempfile.mkdtemp())
+        )
+        self.assertEqual(collector.collector_name(), "canonical")
+
     def test_both_implementations_satisfy_same_interface(self):
         """Both implementations have the same public method surface."""
         legacy = LegacyMetricsCollector(self.settings)
@@ -70,6 +83,7 @@ def test_both_implementations_satisfy_same_interface(self):
         )
 
         required_methods = [
+            "collector_name",
             "increment_task_poll",
             "increment_task_poll_error",
             "increment_task_execution_started",