feat(Production): Complete production deployment infrastructure

- Add comprehensive health check system with multiple endpoints
- Add Prometheus metrics endpoint
- Add production logging configurations (5 strategies)
- Add complete deployment documentation suite:
  * QUICKSTART.md - 30-minute deployment guide
  * DEPLOYMENT_CHECKLIST.md - Printable verification checklist
  * DEPLOYMENT_WORKFLOW.md - Complete deployment lifecycle
  * PRODUCTION_DEPLOYMENT.md - Comprehensive technical reference
  * production-logging.md - Logging configuration guide
  * ANSIBLE_DEPLOYMENT.md - Infrastructure as Code automation
  * README.md - Navigation hub
  * DEPLOYMENT_SUMMARY.md - Executive summary
- Add deployment scripts and automation
- Add DEPLOYMENT_PLAN.md - Concrete plan for immediate deployment
- Update README with production-ready features

All production infrastructure is now complete and ready for deployment.

tests/Integration/MachineLearning/MLModelManagementIntegrationTest.php

@@ -0,0 +1,231 @@
+<?php
+
+declare(strict_types=1);
+
+use App\Framework\Core\ValueObjects\Version;
+use App\Framework\Database\NPlusOneDetection\MachineLearning\NPlusOneModelAdapter;
+use App\Framework\MachineLearning\ModelManagement\ModelRegistry;
+use App\Framework\Queue\MachineLearning\QueueAnomalyModelAdapter;
+use App\Framework\Waf\MachineLearning\WafBehavioralModelAdapter;
+
+/**
+ * Integration Tests for ML Model Management System
+ *
+ * Tests the complete integration of all three ML systems with Model Management
+ */
+
+describe('ML Model Management Integration', function () {
+
+    test('N+1 Detector model adapter is registered in container', function () {
+        $adapter = container()->get(NPlusOneModelAdapter::class);
+
+        expect($adapter)->toBeInstanceOf(NPlusOneModelAdapter::class);
+    })->skip('Requires full framework bootstrap');
+
+    test('WAF Behavioral model adapter is registered in container', function () {
+        $adapter = container()->get(WafBehavioralModelAdapter::class);
+
+        expect($adapter)->toBeInstanceOf(WafBehavioralModelAdapter::class);
+    })->skip('Requires full framework bootstrap');
+
+    test('Queue Anomaly model adapter is registered in container', function () {
+        $adapter = container()->get(QueueAnomalyModelAdapter::class);
+
+        expect($adapter)->toBeInstanceOf(QueueAnomalyModelAdapter::class);
+    })->skip('Requires full framework bootstrap');
+
+    test('Model registry is accessible', function () {
+        $registry = container()->get(ModelRegistry::class);
+
+        expect($registry)->toBeInstanceOf(ModelRegistry::class);
+    })->skip('Requires full framework bootstrap');
+});
+
+describe('Model Registration', function () {
+
+    test('can register N+1 detector model', function () {
+        // This test would require full framework initialization
+        // For now, we verify the class structure
+
+        expect(class_exists(NPlusOneModelAdapter::class))->toBeTrue();
+
+        $reflection = new ReflectionClass(NPlusOneModelAdapter::class);
+        expect($reflection->hasMethod('registerCurrentModel'))->toBeTrue();
+        expect($reflection->hasMethod('analyzeWithTracking'))->toBeTrue();
+        expect($reflection->hasMethod('getCurrentPerformanceMetrics'))->toBeTrue();
+    });
+
+    test('can register WAF behavioral model', function () {
+        expect(class_exists(WafBehavioralModelAdapter::class))->toBeTrue();
+
+        $reflection = new ReflectionClass(WafBehavioralModelAdapter::class);
+        expect($reflection->hasMethod('registerCurrentModel'))->toBeTrue();
+        expect($reflection->hasMethod('analyzeWithTracking'))->toBeTrue();
+        expect($reflection->hasMethod('getCurrentPerformanceMetrics'))->toBeTrue();
+    });
+
+    test('can register queue anomaly model', function () {
+        expect(class_exists(QueueAnomalyModelAdapter::class))->toBeTrue();
+
+        $reflection = new ReflectionClass(QueueAnomalyModelAdapter::class);
+        expect($reflection->hasMethod('registerCurrentModel'))->toBeTrue();
+        expect($reflection->hasMethod('analyzeWithTracking'))->toBeTrue();
+        expect($reflection->hasMethod('getCurrentPerformanceMetrics'))->toBeTrue();
+    });
+});
+
+describe('Adapter Class Structure', function () {
+
+    test('N+1 adapter has correct model name constant', function () {
+        $reflection = new ReflectionClass(NPlusOneModelAdapter::class);
+        $constants = $reflection->getConstants();
+
+        expect($constants)->toHaveKey('MODEL_NAME');
+        expect($constants['MODEL_NAME'])->toBe('n1-detector');
+        expect($constants)->toHaveKey('CURRENT_VERSION');
+        expect($constants['CURRENT_VERSION'])->toBe('1.0.0');
+    });
+
+    test('WAF adapter has correct model name constant', function () {
+        $reflection = new ReflectionClass(WafBehavioralModelAdapter::class);
+        $constants = $reflection->getConstants();
+
+        expect($constants)->toHaveKey('MODEL_NAME');
+        expect($constants['MODEL_NAME'])->toBe('waf-behavioral');
+        expect($constants)->toHaveKey('CURRENT_VERSION');
+        expect($constants['CURRENT_VERSION'])->toBe('1.0.0');
+    });
+
+    test('Queue adapter has correct model name constant', function () {
+        $reflection = new ReflectionClass(QueueAnomalyModelAdapter::class);
+        $constants = $reflection->getConstants();
+
+        expect($constants)->toHaveKey('MODEL_NAME');
+        expect($constants['MODEL_NAME'])->toBe('queue-anomaly');
+        expect($constants)->toHaveKey('CURRENT_VERSION');
+        expect($constants['CURRENT_VERSION'])->toBe('1.0.0');
+    });
+});
+
+describe('Adapter Method Signatures', function () {
+
+    test('N+1 adapter has correct method signatures', function () {
+        $reflection = new ReflectionClass(NPlusOneModelAdapter::class);
+
+        // registerCurrentModel
+        $method = $reflection->getMethod('registerCurrentModel');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(1); // Optional performance metrics
+
+        // analyzeWithTracking
+        $method = $reflection->getMethod('analyzeWithTracking');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(2); // context, groundTruth
+
+        // getCurrentPerformanceMetrics
+        $method = $reflection->getMethod('getCurrentPerformanceMetrics');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(0);
+
+        // checkPerformanceDegradation
+        $method = $reflection->getMethod('checkPerformanceDegradation');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(1); // threshold percent
+    });
+
+    test('WAF adapter has correct method signatures', function () {
+        $reflection = new ReflectionClass(WafBehavioralModelAdapter::class);
+
+        $method = $reflection->getMethod('registerCurrentModel');
+        expect($method->isPublic())->toBeTrue();
+
+        $method = $reflection->getMethod('analyzeWithTracking');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(3); // features, baseline, groundTruth
+
+        $method = $reflection->getMethod('getCurrentPerformanceMetrics');
+        expect($method->isPublic())->toBeTrue();
+    });
+
+    test('Queue adapter has correct method signatures', function () {
+        $reflection = new ReflectionClass(QueueAnomalyModelAdapter::class);
+
+        $method = $reflection->getMethod('registerCurrentModel');
+        expect($method->isPublic())->toBeTrue();
+
+        $method = $reflection->getMethod('analyzeWithTracking');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(2); // features, groundTruth
+
+        $method = $reflection->getMethod('getCurrentPerformanceMetrics');
+        expect($method->isPublic())->toBeTrue();
+    });
+});
+
+describe('Scheduler Integration', function () {
+
+    test('ML monitoring scheduler class exists', function () {
+        $class = 'App\\Framework\\MachineLearning\\Scheduler\\MLMonitoringScheduler';
+        expect(class_exists($class))->toBeTrue();
+    });
+
+    test('ML monitoring scheduler has scheduleAll method', function () {
+        $class = 'App\\Framework\\MachineLearning\\Scheduler\\MLMonitoringScheduler';
+        $reflection = new ReflectionClass($class);
+
+        expect($reflection->hasMethod('scheduleAll'))->toBeTrue();
+
+        $method = $reflection->getMethod('scheduleAll');
+        expect($method->isPublic())->toBeTrue();
+        expect($method->getNumberOfParameters())->toBe(0);
+    });
+
+    test('ML monitoring scheduler initializer exists', function () {
+        $class = 'App\\Framework\\MachineLearning\\Scheduler\\MLMonitoringSchedulerInitializer';
+        expect(class_exists($class))->toBeTrue();
+
+        $reflection = new ReflectionClass($class);
+        expect($reflection->isFinal())->toBeTrue();
+        expect($reflection->isReadOnly())->toBeTrue();
+    });
+});
+
+describe('File Structure', function () {
+
+    test('all adapter files exist', function () {
+        $files = [
+            '/var/www/html/src/Framework/Database/NPlusOneDetection/MachineLearning/NPlusOneModelAdapter.php',
+            '/var/www/html/src/Framework/Waf/MachineLearning/WafBehavioralModelAdapter.php',
+            '/var/www/html/src/Framework/Queue/MachineLearning/QueueAnomalyModelAdapter.php',
+        ];
+
+        foreach ($files as $file) {
+            expect(file_exists($file))->toBeTrue("File should exist: {$file}");
+        }
+    });
+
+    test('scheduler files exist', function () {
+        $files = [
+            '/var/www/html/src/Framework/MachineLearning/Scheduler/MLMonitoringScheduler.php',
+            '/var/www/html/src/Framework/MachineLearning/Scheduler/MLMonitoringSchedulerInitializer.php',
+        ];
+
+        foreach ($files as $file) {
+            expect(file_exists($file))->toBeTrue("File should exist: {$file}");
+        }
+    });
+
+    test('deployment documentation exists', function () {
+        $file = '/var/www/html/docs/ml-model-management-deployment.md';
+        expect(file_exists($file))->toBeTrue();
+
+        $content = file_get_contents($file);
+        expect($content)->toContain('ML Model Management System');
+        expect($content)->toContain('Production Deployment Guide');
+    });
+
+    test('integration example exists', function () {
+        $file = '/var/www/html/examples/n1-model-management-integration.php';
+        expect(file_exists($file))->toBeTrue();
+    });
+});