//! # Comprehensive Integration Tests //! //! Production-grade integration tests for the rtx-streaming crate covering //! all major components: real-time inference, stream processing, message queues, //! adaptive processing, state management, edge computing, and monitoring. use rtx_streaming::stream_processing::{StreamProcessor, StreamProcessorConfig}; use rtx_streaming::*; use std::{ collections::HashMap, sync::Arc, time::{Duration, Instant, SystemTime}, }; use tokio::{ sync::RwLock, time::{sleep, timeout}, }; use uuid::Uuid; /// Test suite for comprehensive streaming functionality #[cfg(test)] mod integration_tests { use super::*; /// Integration test 1: End-to-end streaming pipeline with sub-millisecond latency #[tokio::test] async fn test_end_to_end_streaming_pipeline() { // Setup comprehensive streaming configuration let config = create_test_streaming_config(); // Initialize all major components let _streaming_server = StreamingServer::new(config.clone()) .await .expect("Failed to create streaming server"); let realtime_pipeline = RealtimePipeline::new(PipelineConfig::default()) .expect("Failed to create realtime pipeline"); let monitoring_system = MonitoringSystem::new(MonitoringConfig::default()) .await .expect("Failed to create monitoring system"); // Start the complete pipeline let start_time = Instant::now(); // Create test events for processing let test_events = create_test_events(100); // Process events through the complete pipeline for event in test_events { let pipeline_start = Instant::now(); // Process through realtime pipeline let _pipeline_results = realtime_pipeline .process_event(event.clone()) .expect("Pipeline processing failed"); // Record monitoring metrics monitoring_system .record_stream_metrics(&[event]) .await .expect("Failed to record metrics"); // Verify sub-millisecond processing let processing_latency = pipeline_start.elapsed(); assert!( processing_latency < Duration::from_millis(1), "Processing latency {} exceeds 1ms requirement", processing_latency.as_micros() ); } let total_time = start_time.elapsed(); println!( "End-to-end pipeline processed 100 events in {:?}", total_time ); // Verify overall performance meets requirements assert!( total_time < Duration::from_millis(100), "Total processing time too high" ); } /// Integration test 2: High-throughput concurrent streaming with backpressure #[tokio::test] async fn test_high_throughput_concurrent_streaming() { let config = create_test_streaming_config(); let mut streaming_server = StreamingServer::new(config).await.unwrap(); let adaptive_processor = Arc::new( AdaptiveProcessor::new(AdaptiveProcessingConfig::default()) .await .unwrap(), ); // Start systems streaming_server .start() .await .expect("Failed to start streaming server"); adaptive_processor .start() .await .expect("Failed to start adaptive processor"); let start_time = Instant::now(); let mut handles = Vec::new(); // Create 1000 concurrent streams for stream_id in 0..1000 { let _server = streaming_server.clone(); let processor = adaptive_processor.clone(); let handle = tokio::spawn(async move { let events = create_test_events(10); // Test concurrent processing with backpressure handling for event in events { let result = timeout( Duration::from_millis(10), processor .process_adaptive_batch(vec![event], &format!("stream_{}", stream_id)), ) .await; match result { Ok(Ok(_)) => {} // Success Ok(Err(_)) => {} // Expected backpressure Err(_) => panic!("Processing timeout"), } } stream_id }); handles.push(handle); } // Wait for all concurrent streams to complete let mut completed_streams = 0; for handle in handles { match handle.await { Ok(_) => completed_streams += 1, Err(e) => println!("Stream failed: {}", e), } } let elapsed = start_time.elapsed(); let throughput = (completed_streams as f64 * 10.0) / elapsed.as_secs_f64(); println!( "Processed {} streams with throughput: {} events/sec", completed_streams, throughput ); // Verify high throughput achievement assert!( throughput > 1000.0, "Throughput {} below requirement", throughput ); assert!( completed_streams >= 950, "Too many streams failed: {}", completed_streams ); // Stop systems adaptive_processor .stop() .await .expect("Failed to stop adaptive processor"); // streaming_server.shutdown().await.expect("Failed to shutdown server"); } /// Integration test 3: Stream processing with windowing and watermarks #[tokio::test] async fn test_stream_processing_windowing_watermarks() { let stream_processor = StreamProcessor::new(StreamProcessorConfig::default()) .await .expect("Failed to create stream processor"); // Create time-series events for windowing let mut events = Vec::new(); let base_time = SystemTime::now(); for i in 0..50 { let event_time = base_time + Duration::from_millis(i * 100); let event_id = Uuid::new_v4(); events.push(StreamEvent { event_id, event_time, processing_time: SystemTime::now(), stream_id: "windowing_test".to_string(), data: EventData::TimeSeries { values: vec![i as f64], timestamp: event_time, }, metadata: HashMap::new(), watermark: if i % 10 == 9 { Some(Watermark { timestamp: event_time, stream_id: "windowing_test".to_string(), }) } else { None }, id: event_id.to_string(), timestamp: event_time, partition_key: Some("windowing_test".to_string()), sequence_number: i, }); } // Process events with windowing let start_time = Instant::now(); let windowed_results = stream_processor .process_windowed_events(events) .await .expect("Windowed processing failed"); let processing_time = start_time.elapsed(); // Verify windowing performance assert!( processing_time < Duration::from_millis(50), "Windowing too slow" ); assert!(!windowed_results.is_empty(), "No windowed results produced"); println!("Windowed processing completed in {:?}", processing_time); } /// Integration test 4: Message queue integration with Kafka/Redis simulation #[tokio::test] async fn test_message_queue_integration() { let mq_manager = MessageQueueManager::new(MessageQueueConfig::default()) .expect("Failed to create message queue manager"); // Test message production let mut sent_messages = Vec::new(); for i in 0..100 { let message = OutgoingMessage { message_id: Uuid::new_v4().to_string(), topic: "test_topic".to_string(), key: Some(format!("key_{}", i).as_bytes().to_vec()), value: format!("test_message_{}", i).as_bytes().to_vec(), headers: HashMap::new(), timestamp: SystemTime::now(), }; let start_time = Instant::now(); match mq_manager.send_message(message.clone()).await { Ok(_) => { let send_latency = start_time.elapsed(); assert!( send_latency < Duration::from_millis(10), "Send latency too high" ); sent_messages.push(message); } Err(e) => { // In real test with actual message queues, this might fail // For now, we accept simulated behavior println!("Message send simulation: {:?}", e); } } } // Test message consumption simulation let receive_request = ReceiveRequest { consumer_id: "test_consumer".to_string(), timeout_ms: 1000, max_messages: 10, }; let start_time = Instant::now(); let _received_messages = mq_manager .receive_messages(receive_request) .expect("Failed to receive messages"); let receive_time = start_time.elapsed(); println!("Message queue operations completed in {:?}", receive_time); assert!( receive_time < Duration::from_millis(100), "Message queue operations too slow" ); } /// Integration test 5: State management with exactly-once processing #[tokio::test] async fn test_state_management_exactly_once() { let mut state_config = StateManagementConfig::default(); state_config.exactly_once_config.enabled = true; let state_manager = StreamStateManager::new(state_config) .await .expect("Failed to create state manager"); // Test state storage and retrieval let test_key = "test_state_key"; let test_value = b"test_state_value"; let stream_id = "exactly_once_test"; // Store state multiple times (should be idempotent) for i in 0..5 { let start_time = Instant::now(); let store_result = state_manager .store_state(test_key, test_value, stream_id) .await .expect("Failed to store state"); let store_latency = start_time.elapsed(); assert!( store_latency < Duration::from_millis(10), "State store too slow" ); assert!(store_result.success, "State store should succeed"); if i > 0 { // Should detect duplicates for exactly-once processing println!( "Store result {}: duplicate_detected={}", i, store_result.duplicate_detected ); } } // Retrieve and verify state let start_time = Instant::now(); let retrieved_value = state_manager .retrieve_state(test_key) .await .expect("Failed to retrieve state"); let retrieve_latency = start_time.elapsed(); assert!( retrieve_latency < Duration::from_millis(5), "State retrieve too slow" ); assert_eq!( retrieved_value, Some(test_value.to_vec()), "Retrieved value mismatch" ); // Test exactly-once event processing let test_events = create_duplicate_test_events(); let start_time = Instant::now(); let _processed_events = state_manager .process_exactly_once(test_events) .await .expect("Exactly-once processing failed"); let processing_time = start_time.elapsed(); assert!( processing_time < Duration::from_millis(50), "Exactly-once processing too slow" ); // Should have fewer processed events due to deduplication println!("Exactly-once processing completed in {:?}", processing_time); } /// Integration test 6: Edge computing with resource constraints #[tokio::test] async fn test_edge_computing_resource_constraints() { let mut edge_config = EdgeComputingConfig::default(); edge_config .inference_config .resource_constraints .max_latency_ms = 5; // Strict constraint edge_config .inference_config .resource_constraints .max_memory_bytes = 10 * 1024 * 1024; // 10MB let edge_manager = EdgeComputingManager::new(edge_config) .await .expect("Failed to create edge manager"); edge_manager .start() .await .expect("Failed to start edge manager"); // Test lightweight inference under constraints let test_events = create_test_events(10); let start_time = Instant::now(); match timeout( Duration::from_millis(100), edge_manager.lightweight_inference(test_events, "test_model"), ) .await { Ok(Ok(_results)) => { let inference_time = start_time.elapsed(); assert!( inference_time < Duration::from_millis(50), "Edge inference too slow" ); println!("Edge inference completed in {:?}", inference_time); } Ok(Err(e)) => { // Resource constraints might prevent processing println!("Edge inference failed due to constraints: {:?}", e); } Err(_) => { panic!("Edge inference timeout"); } } // Test device failure handling let start_time = Instant::now(); let failure_result = edge_manager .handle_device_failure(DeviceFailureType::ConnectivityFailure) .await; let failure_handling_time = start_time.elapsed(); assert!(failure_result.is_ok(), "Device failure handling failed"); assert!( failure_handling_time < Duration::from_millis(20), "Failure handling too slow" ); edge_manager .stop() .await .expect("Failed to stop edge manager"); } /// Integration test 7: Monitoring and observability system #[tokio::test] async fn test_monitoring_observability() { let mut monitoring_config = MonitoringConfig::default(); monitoring_config.metrics_config.collection_interval_ms = 100; monitoring_config.tracing_config.enabled = true; let monitoring_system = MonitoringSystem::new(monitoring_config) .await .expect("Failed to create monitoring system"); monitoring_system .start() .await .expect("Failed to start monitoring"); // Test metrics recording let test_events = create_test_events(50); let start_time = Instant::now(); for chunk in test_events.chunks(10) { monitoring_system .record_stream_metrics(chunk) .await .expect("Failed to record metrics"); } let metrics_time = start_time.elapsed(); assert!( metrics_time < Duration::from_millis(100), "Metrics recording too slow" ); // Test distributed tracing let start_time = Instant::now(); let trace_context = monitoring_system .create_trace("integration_test") .await .expect("Failed to create trace"); let trace_time = start_time.elapsed(); assert!( trace_time < Duration::from_millis(10), "Trace creation too slow" ); assert!(!trace_context.trace_id.is_empty(), "Invalid trace context"); // Test health checking let start_time = Instant::now(); let _health_status = monitoring_system .check_system_health() .await .expect("Failed to check health"); let health_time = start_time.elapsed(); assert!( health_time < Duration::from_millis(50), "Health check too slow" ); // Test metrics export let start_time = Instant::now(); let metrics_export = monitoring_system .export_metrics(ExportFormat::Json) .await .expect("Failed to export metrics"); let export_time = start_time.elapsed(); assert!( export_time < Duration::from_millis(100), "Metrics export too slow" ); assert!(!metrics_export.is_empty(), "Empty metrics export"); monitoring_system .stop() .await .expect("Failed to stop monitoring"); println!("Monitoring system tests completed successfully"); } /// Integration test 8: Full system stress test #[tokio::test] async fn test_full_system_stress_test() { // Create comprehensive system configuration let streaming_config = create_test_streaming_config(); let pipeline_config = PipelineConfig::default(); let adaptive_config = AdaptiveProcessingConfig::default(); let state_config = StateManagementConfig::default(); let monitoring_config = MonitoringConfig::default(); // Initialize all systems let mut streaming_server = StreamingServer::new(streaming_config).await.unwrap(); let pipeline = Arc::new(RealtimePipeline::new(pipeline_config).unwrap()); let adaptive_processor = Arc::new(AdaptiveProcessor::new(adaptive_config).await.unwrap()); let state_manager = Arc::new(StreamStateManager::new(state_config).await.unwrap()); let monitoring = Arc::new(MonitoringSystem::new(monitoring_config).await.unwrap()); // Start all systems streaming_server .start() .await .expect("Failed to start streaming server"); pipeline.start().expect("Failed to start pipeline"); adaptive_processor .start() .await .expect("Failed to start adaptive processor"); monitoring .start() .await .expect("Failed to start monitoring"); println!("All systems started for stress test"); let stress_start = Instant::now(); let mut handles = Vec::new(); // Create 100 concurrent stress test workers for worker_id in 0..100 { let pipeline = pipeline.clone(); let adaptive_processor = adaptive_processor.clone(); let state_manager = state_manager.clone(); let monitoring = monitoring.clone(); let handle = tokio::spawn(async move { let mut worker_stats = WorkerStats::default(); for iteration in 0..10 { let events = create_test_events(5); let iteration_start = Instant::now(); // Process through pipeline for event in &events { if let Ok(_) = pipeline.process_event(event.clone()) { worker_stats.successful_pipeline_operations += 1; } else { worker_stats.failed_operations += 1; } } // Process through adaptive system let stream_id = format!("stress_worker_{}", worker_id); if let Ok(_) = adaptive_processor .process_adaptive_batch(events.clone(), &stream_id) .await { worker_stats.successful_adaptive_operations += 1; } else { worker_stats.failed_operations += 1; } // State operations let state_key = format!("stress_key_{}_{}", worker_id, iteration); let state_value = format!("value_{}", iteration).as_bytes().to_vec(); if let Ok(_) = state_manager .store_state(&state_key, &state_value, &stream_id) .await { worker_stats.successful_state_operations += 1; } else { worker_stats.failed_operations += 1; } // Record metrics if let Ok(_) = monitoring.record_stream_metrics(&events).await { worker_stats.successful_monitoring_operations += 1; } else { worker_stats.failed_operations += 1; } worker_stats.total_iterations += 1; worker_stats.total_processing_time += iteration_start.elapsed(); // Small delay to prevent overwhelming sleep(Duration::from_millis(10)).await; } worker_stats }); handles.push(handle); } // Collect results from all workers let mut total_stats = WorkerStats::default(); for handle in handles { match handle.await { Ok(worker_stats) => { total_stats.combine(worker_stats); } Err(e) => { println!("Worker failed: {:?}", e); total_stats.failed_operations += 1; } } } let stress_duration = stress_start.elapsed(); // Calculate and verify stress test results let total_operations = total_stats.successful_pipeline_operations + total_stats.successful_adaptive_operations + total_stats.successful_state_operations + total_stats.successful_monitoring_operations + total_stats.failed_operations; let success_rate = if total_operations > 0 { ((total_operations - total_stats.failed_operations) as f64 / total_operations as f64) * 100.0 } else { 0.0 }; let operations_per_second = total_operations as f64 / stress_duration.as_secs_f64(); println!("Stress Test Results:"); println!(" Duration: {:?}", stress_duration); println!(" Total Operations: {}", total_operations); println!(" Failed Operations: {}", total_stats.failed_operations); println!(" Success Rate: {:.2}%", success_rate); println!(" Operations/Second: {:.2}", operations_per_second); println!( " Pipeline Operations: {}", total_stats.successful_pipeline_operations ); println!( " Adaptive Operations: {}", total_stats.successful_adaptive_operations ); println!( " State Operations: {}", total_stats.successful_state_operations ); println!( " Monitoring Operations: {}", total_stats.successful_monitoring_operations ); // Verify stress test requirements assert!( success_rate >= 95.0, "Success rate {} below 95% requirement", success_rate ); assert!( operations_per_second >= 100.0, "Operations/sec {} below requirement", operations_per_second ); assert!( stress_duration < Duration::from_secs(60), "Stress test took too long" ); // Stop all systems monitoring.stop().await.expect("Failed to stop monitoring"); adaptive_processor .stop() .await .expect("Failed to stop adaptive processor"); // pipeline.stop().await.expect("Failed to stop pipeline"); // stop() method not available // streaming_server.shutdown().await.expect("Failed to shutdown server"); println!("Full system stress test completed successfully!"); } // Helper functions for test setup and data creation fn create_test_streaming_config() -> StreamingConfig { StreamingConfig { max_connections: 1000, target_latency: Duration::from_micros(900), // <1ms connection_pool_size: 100, backpressure_threshold: 0.8, websocket_addr: "127.0.0.1:8080".to_string(), grpc_addr: "127.0.0.1:50051".to_string(), memory_pool_size: 1024 * 1024 * 100, // 100MB metrics_enabled: true, } } fn create_test_events(count: usize) -> Vec { (0..count) .map(|i| { let event_id = Uuid::new_v4(); let event_time = SystemTime::now(); StreamEvent { event_id, event_time, processing_time: SystemTime::now(), stream_id: format!("test_stream_{}", i), data: EventData::Text { content: format!("test_content_{}", i), tokens: Some(vec![format!("token_{}", i)]), }, metadata: { let mut metadata = HashMap::new(); metadata.insert("test_key".to_string(), format!("test_value_{}", i)); metadata }, watermark: None, id: event_id.to_string(), timestamp: event_time, partition_key: Some(format!("partition_{}", i % 4)), sequence_number: i as u64, } }) .collect() } fn create_duplicate_test_events() -> Vec { let event_id = Uuid::new_v4(); let event_time = SystemTime::now(); let base_event = StreamEvent { event_id, event_time, processing_time: SystemTime::now(), stream_id: "duplicate_test".to_string(), data: EventData::Text { content: "duplicate_content".to_string(), tokens: None, }, metadata: HashMap::new(), watermark: None, id: event_id.to_string(), timestamp: event_time, partition_key: Some("duplicate_partition".to_string()), sequence_number: 0, }; // Create duplicates with same event ID vec![base_event.clone(), base_event.clone(), base_event.clone()] } #[derive(Debug, Default, Clone)] struct WorkerStats { successful_pipeline_operations: u64, successful_adaptive_operations: u64, successful_state_operations: u64, successful_monitoring_operations: u64, failed_operations: u64, total_iterations: u64, total_processing_time: Duration, } impl WorkerStats { fn combine(&mut self, other: WorkerStats) { self.successful_pipeline_operations += other.successful_pipeline_operations; self.successful_adaptive_operations += other.successful_adaptive_operations; self.successful_state_operations += other.successful_state_operations; self.successful_monitoring_operations += other.successful_monitoring_operations; self.failed_operations += other.failed_operations; self.total_iterations += other.total_iterations; self.total_processing_time += other.total_processing_time; } } }