feat(runtime): complete Vault integration for SecretResolver [OMN-1374]

src/omnibase_infra/runtime/models/__init__.py

@@ -41,6 +41,7 @@
     ModelSecretResolverConfig: Configuration for SecretResolver
     ModelCachedSecret: Cached secret with TTL tracking
     ModelSecretCacheStats: Cache statistics for observability
+    ModelSecretResolverMetrics: Resolution metrics for observability
     ModelSecretSourceInfo: Non-sensitive source information for introspection
 """
 
@@ -107,6 +108,9 @@
 from omnibase_infra.runtime.models.model_secret_resolver_config import (
     ModelSecretResolverConfig,
 )
+from omnibase_infra.runtime.models.model_secret_resolver_metrics import (
+    ModelSecretResolverMetrics,
+)
 from omnibase_infra.runtime.models.model_secret_source_info import ModelSecretSourceInfo
 from omnibase_infra.runtime.models.model_secret_source_spec import (
     ModelSecretSourceSpec,
@@ -149,6 +153,7 @@
     "ModelSecretCacheStats",
     "ModelSecretMapping",
     "ModelSecretResolverConfig",
+    "ModelSecretResolverMetrics",
     "ModelSecretSourceInfo",
     "ModelSecretSourceSpec",
     "SecretSourceType",

src/omnibase_infra/runtime/models/model_secret_resolver_metrics.py

@@ -0,0 +1,111 @@
+# SPDX-License-Identifier: MIT
+# Copyright (c) 2025 OmniNode Team
+"""Model for secret resolver metrics.
+
+.. versionadded:: 0.8.0
+    Initial implementation for OMN-1374.
+"""
+
+from __future__ import annotations
+
+from pydantic import BaseModel, ConfigDict, Field
+
+
+class ModelSecretResolverMetrics(BaseModel):
+    """Resolution metrics for SecretResolver observability.
+
+    Provides aggregated metrics for monitoring secret resolution performance
+    and health across different source types (env, file, vault, cache).
+
+    Attributes:
+        success_counts: Count of successful resolutions by source type.
+        failure_counts: Count of failed resolutions by source type.
+        latency_samples: Number of latency samples collected.
+        avg_latency_ms: Average resolution latency in milliseconds.
+        cache_hits: Total number of cache hits.
+        cache_misses: Total number of cache misses.
+
+    Example:
+        >>> metrics = ModelSecretResolverMetrics(
+        ...     success_counts={"env": 5, "vault": 3},
+        ...     failure_counts={"vault": 1},
+        ...     latency_samples=9,
+        ...     avg_latency_ms=12.5,
+        ...     cache_hits=100,
+        ...     cache_misses=10,
+        ... )
+        >>> metrics.success_counts["env"]
+        5
+    """
+
+    model_config = ConfigDict(
+        strict=True,
+        frozen=True,
+        extra="forbid",
+        from_attributes=True,
+    )
+
+    success_counts: dict[str, int] = Field(
+        default_factory=dict,
+        description="Count of successful resolutions by source type (e.g., 'env', 'vault', 'file').",
+    )
+    failure_counts: dict[str, int] = Field(
+        default_factory=dict,
+        description="Count of failed resolutions by source type.",
+    )
+    latency_samples: int = Field(
+        default=0,
+        ge=0,
+        description="Number of latency samples collected.",
+    )
+    avg_latency_ms: float = Field(
+        default=0.0,
+        ge=0.0,
+        description="Average resolution latency in milliseconds.",
+    )
+    cache_hits: int = Field(
+        default=0,
+        ge=0,
+        description="Total number of cache hits.",
+    )
+    cache_misses: int = Field(
+        default=0,
+        ge=0,
+        description="Total number of cache misses.",
+    )
+
+    @property
+    def cache_hit_rate(self) -> float:
+        """Calculate cache hit rate.
+
+        Returns:
+            Hit rate as a float between 0.0 and 1.0.
+            Returns 0.0 if no hits or misses have occurred.
+
+        Example:
+            >>> metrics = ModelSecretResolverMetrics(cache_hits=80, cache_misses=20)
+            >>> metrics.cache_hit_rate
+            0.8
+        """
+        total = self.cache_hits + self.cache_misses
+        return self.cache_hits / total if total > 0 else 0.0
+
+    @property
+    def total_resolutions(self) -> int:
+        """Calculate total number of resolutions attempted.
+
+        Returns:
+            Sum of all success and failure counts across all source types.
+
+        Example:
+            >>> metrics = ModelSecretResolverMetrics(
+            ...     success_counts={"env": 5, "vault": 3},
+            ...     failure_counts={"vault": 1},
+            ... )
+            >>> metrics.total_resolutions
+            9
+        """
+        return sum(self.success_counts.values()) + sum(self.failure_counts.values())
+
+
+__all__: list[str] = ["ModelSecretResolverMetrics"]