feat(Deployment): Integrate Ansible deployment via PHP deployment pipeline

- Create AnsibleDeployStage using framework's Process module for secure command execution
- Integrate AnsibleDeployStage into DeploymentPipelineCommands for production deployments
- Add force_deploy flag support in Ansible playbook to override stale locks
- Use PHP deployment module as orchestrator (php console.php deploy:production)
- Fix ErrorAggregationInitializer to use Environment class instead of $_ENV superglobal

Architecture:
- BuildStage → AnsibleDeployStage → HealthCheckStage for production
- Process module provides timeout, error handling, and output capture
- Ansible playbook supports rollback via rollback-git-based.yml
- Zero-downtime deployments with health checks

src/Framework/MachineLearning/ModelManagement/PerformanceStorage.php

@@ -72,4 +72,43 @@ interface PerformanceStorage
      * Clear old prediction records (cleanup)
      */
     public function clearOldPredictions(Duration $olderThan): int;
+
+    /**
+     * Get recent predictions (limit-based)
+     *
+     * @return array<array{
+     *     model_name: string,
+     *     version: string,
+     *     prediction: mixed,
+     *     actual: mixed,
+     *     confidence: float,
+     *     features: array,
+     *     timestamp: \DateTimeImmutable,
+     *     is_correct: ?bool
+     * }>
+     */
+    public function getRecentPredictions(
+        string $modelName,
+        Version $version,
+        int $limit
+    ): array;
+
+    /**
+     * Calculate accuracy from recent predictions
+     */
+    public function calculateAccuracy(
+        string $modelName,
+        Version $version,
+        int $limit
+    ): float;
+
+    /**
+     * Get confidence baseline
+     *
+     * @return array{avg_confidence: float, std_dev_confidence: float}|null
+     */
+    public function getConfidenceBaseline(
+        string $modelName,
+        Version $version
+    ): ?array;
 }