Michael Schiemer
3b623e7afb
- 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 $_ENV superglobal Architecture: - BuildStage → AnsibleDeployStage → HealthCheckStage for production - Process module provides timeout, error handling, and output capture - Ansible playbook supports rollback via rollback-git-based.yml - Zero-downtime deployments with health checks
113 lines
3.9 KiB
PHP
113 lines
3.9 KiB
PHP
<?php
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declare(strict_types=1);
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/**
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* Manual Test for ML Monitoring Scheduler
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*
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* Tests scheduler job registration and execution simulation
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*/
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require_once __DIR__ . '/../../vendor/autoload.php';
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use App\Framework\Core\AppBootstrapper;
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use App\Framework\MachineLearning\Scheduler\MLMonitoringScheduler;
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use App\Framework\Scheduler\Services\SchedulerService;
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echo "=== ML Monitoring Scheduler Manual Test ===\n\n";
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try {
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// Bootstrap framework
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echo "1. Bootstrapping framework...\n";
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$basePath = dirname(__DIR__, 2);
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// Create minimal dependencies
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$clock = new \App\Framework\DateTime\SystemClock();
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$highResClock = new \App\Framework\DateTime\SystemHighResolutionClock();
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$memoryMonitor = new \App\Framework\Performance\MemoryMonitor();
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$collector = new \App\Framework\Performance\EnhancedPerformanceCollector(
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$clock,
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$highResClock,
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$memoryMonitor,
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enabled: false
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);
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$bootstrapper = new AppBootstrapper($basePath, $collector, $memoryMonitor);
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$container = $bootstrapper->bootstrapWorker();
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echo " ✓ Framework bootstrapped\n\n";
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// Manually initialize ML Model Management
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echo " → Manually registering ML Model Management services...\n";
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$mlInitializer = new \App\Framework\MachineLearning\ModelManagement\MLModelManagementInitializer($container);
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$mlInitializer->initialize();
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echo " ✓ ML Model Management initialized\n\n";
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// Get scheduler services
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echo "2. Testing Scheduler Services...\n";
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$schedulerService = $container->get(SchedulerService::class);
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echo " ✓ SchedulerService retrieved\n";
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$mlScheduler = $container->get(MLMonitoringScheduler::class);
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echo " ✓ MLMonitoringScheduler retrieved\n\n";
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// Schedule all ML monitoring jobs
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echo "3. Scheduling ML Monitoring Jobs...\n";
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try {
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$mlScheduler->scheduleAll();
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echo " ✓ All ML monitoring jobs scheduled\n\n";
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} catch (\Throwable $e) {
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echo " ✗ Scheduling error: " . $e->getMessage() . "\n";
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echo " File: " . $e->getFile() . ":" . $e->getLine() . "\n\n";
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}
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// Check scheduled tasks
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echo "4. Verifying Scheduled Tasks...\n";
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try {
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$dueTasks = $schedulerService->getDueTasks();
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echo " ✓ getDueTasks() works\n";
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echo " - Currently due tasks: " . count($dueTasks) . "\n";
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} catch (\Throwable $e) {
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echo " ✗ Verification error: " . $e->getMessage() . "\n";
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}
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echo "\n";
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// Test immediate execution of due tasks (simulation)
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echo "5. Testing Task Execution (Simulation)...\n";
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try {
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$results = $schedulerService->executeDueTasks();
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echo " ✓ executeDueTasks() completed\n";
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echo " - Tasks executed: " . count($results) . "\n";
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foreach ($results as $result) {
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$status = $result->success ? '✓' : '✗';
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echo " {$status} {$result->taskName}: ";
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if ($result->success) {
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echo "Success\n";
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if (!empty($result->returnValue)) {
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echo " Return: " . json_encode($result->returnValue, JSON_PRETTY_PRINT) . "\n";
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}
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} else {
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echo "Failed\n";
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if ($result->error !== null) {
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echo " Error: " . $result->error . "\n";
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}
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}
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}
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} catch (\Throwable $e) {
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echo " ✗ Execution error: " . $e->getMessage() . "\n";
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echo " File: " . $e->getFile() . ":" . $e->getLine() . "\n";
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}
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echo "\n";
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echo "=== Scheduler Test Completed ===\n";
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echo "✓ Scheduler integration test successful\n";
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} catch (\Throwable $e) {
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echo "\n!!! FATAL ERROR !!!\n";
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echo "Error: " . $e->getMessage() . "\n";
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echo "File: " . $e->getFile() . ":" . $e->getLine() . "\n";
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echo "\nStack trace:\n" . $e->getTraceAsString() . "\n";
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exit(1);
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}
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