Spring Boot 3.4 Virtual Threads: Pertanyaan Wawancara dan Benchmark Performa

// Comparing thread creation approaches
public class VirtualThreadDemo {

    public void demonstrateDifference() {
        // Platform Thread: ~1MB stack per thread
        // Practical limit: a few thousand on a standard JVM
        Thread platformThread = new Thread(() -> {
            performBlockingOperation();
        });

        // Virtual Thread: ~a few KB per thread
        // Can create millions without issues
        Thread virtualThread = Thread.ofVirtual().start(() -> {
            performBlockingOperation();
        });
    }

    // A Virtual Thread "mounts" onto a Platform Thread (carrier)
    // During I/O blocking, it releases the carrier for other Virtual Threads
    private void performBlockingOperation() {
        try {
            Thread.sleep(1000); // Virtual Thread detaches from carrier here
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
    }
}

# application.yml
# Global Virtual Threads activation
spring:
  threads:
    virtual:
      enabled: true

# Optional Tomcat pool configuration
server:
  tomcat:
    threads:
      max: 200  # Less critical with Virtual Threads
      min-spare: 10

// Programmatic activation if needed
@Configuration
public class WebConfig {

    @Bean
    public TomcatProtocolHandlerCustomizer<?> virtualThreadCustomizer() {
        // Each HTTP request runs on a Virtual Thread
        return protocolHandler -> {
            protocolHandler.setExecutor(Executors.newVirtualThreadPerTaskExecutor());
        };
    }
}

// Illustrating the mounting/unmounting cycle
public class MountingDemo {

    public void demonstrateMounting() {
        Thread.ofVirtual().start(() -> {
            // MOUNTED: Virtual Thread is using a carrier thread
            System.out.println("Carrier: " + getCurrentCarrier());

            // UNMOUNTING: releases carrier during blocking
            performDatabaseQuery(); // Blocking JDBC call

            // REMOUNTED: may be on a different carrier
            System.out.println("New carrier: " + getCurrentCarrier());
        });
    }

    // Blocking operations trigger unmounting automatically
    private void performDatabaseQuery() {
        // JDBC connection, file read, network call...
        // Virtual Thread detaches during I/O wait
    }

    private String getCurrentCarrier() {
        // Gets the current carrier thread name
        return Thread.currentThread().toString();
    }
}

// Ideal case for Virtual Threads
@Service
public class IOBoundService {

    private final RestClient restClient;
    private final UserRepository userRepository;

    // Each call involves network and database waiting
    // Virtual Threads shine here
    public UserProfile enrichUserProfile(Long userId) {
        // DB call - VT detaches during SQL query
        User user = userRepository.findById(userId).orElseThrow();

        // External REST call - VT detaches during HTTP wait
        ExternalData externalData = restClient
            .get()
            .uri("/api/external/{id}", userId)
            .retrieve()
            .body(ExternalData.class);

        // Data aggregation
        return new UserProfile(user, externalData);
    }
}

// Examples of cases to avoid
@Service
public class AntiPatterns {

    // ANTI-PATTERN 1: CPU-intensive computation
    // Virtual Threads provide no benefit here
    public BigInteger computeFactorial(int n) {
        // 100% CPU, no I/O, no unmounting possible
        BigInteger result = BigInteger.ONE;
        for (int i = 2; i <= n; i++) {
            result = result.multiply(BigInteger.valueOf(i));
        }
        return result; // Carrier is monopolized throughout
    }

    // ANTI-PATTERN 2: Synchronized causes pinning
    private final Object lock = new Object();

    public void pinnedOperation() {
        synchronized (lock) { // PINNING: VT stays on carrier
            performDatabaseQuery(); // Unmounting doesn't happen!
        }
    }

    // SOLUTION: Use ReentrantLock
    private final ReentrantLock reentrantLock = new ReentrantLock();

    public void unpinnedOperation() {
        reentrantLock.lock();
        try {
            performDatabaseQuery(); // Unmounting possible
        } finally {
            reentrantLock.unlock();
        }
    }
}

// Configuration and pinning detection
public class PinningDiagnostics {

    // JVM option to log pinning
    // -Djdk.tracePinnedThreads=full (detailed)
    // -Djdk.tracePinnedThreads=short (summary)

    // Example code causing pinning
    public void demonstratePinning() {
        Thread.ofVirtual().start(() -> {
            synchronized (this) {
                // This log will appear with tracePinnedThreads enabled
                try {
                    Thread.sleep(100); // Pinned during sleep!
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                }
            }
        });
    }
}

# Typical output with -Djdk.tracePinnedThreads=full
Thread[#23,VirtualThread[#1]/runnable@ForkJoinPool-1-worker-1,5,CarrierThreads]
    java.base/java.lang.VirtualThread$VThreadContinuation.onPinned(VirtualThread.java:183)
    java.base/java.lang.VirtualThread.parkOnCarrierThread(VirtualThread.java:661)
    com.example.PinningDiagnostics.demonstratePinning(PinningDiagnostics.java:15)

// Endpoint for measuring performance
@RestController
@RequestMapping("/api/benchmark")
public class BenchmarkController {

    private final ExternalApiClient apiClient;

    // Simulation of a typical endpoint with external calls
    @GetMapping("/user/{id}")
    public ResponseEntity<UserData> getUser(@PathVariable Long id) {
        // Three sequential I/O calls
        UserInfo info = apiClient.fetchUserInfo(id);        // ~50ms
        List<Order> orders = apiClient.fetchOrders(id);     // ~80ms
        CreditScore score = apiClient.fetchCreditScore(id); // ~100ms

        return ResponseEntity.ok(new UserData(info, orders, score));
    }
}

# Benchmark results - 10,000 concurrent requests
# Configuration: 8 cores, 16GB RAM, simulated latency 230ms/request

Platform Threads (pool 200):
- Throughput: 850 req/s
- P99 latency: 1250ms
- Heap memory: 2.1GB

Virtual Threads:
- Throughput: 4200 req/s
- P99 latency: 280ms
- Heap memory: 850MB

Gain: 5x throughput, 4.5x P99 latency reduction

# application.yml
# HikariCP configuration optimized for Virtual Threads
spring:
  datasource:
    hikari:
      # More connections since Virtual Threads allow more concurrency
      maximum-pool-size: 50
      minimum-idle: 10
      # Shorter timeout due to more concurrent requests
      connection-timeout: 5000
      # Fast validation
      validation-timeout: 3000

  # Redis with Lettuce - already async-friendly
  data:
    redis:
      lettuce:
        pool:
          max-active: 50
          max-idle: 20

// Pool monitoring to avoid contention
@Component
public class ConnectionPoolMonitor {

    private final HikariDataSource dataSource;

    @Scheduled(fixedRate = 10000)
    public void logPoolStats() {
        HikariPoolMXBean pool = dataSource.getHikariPoolMXBean();
        log.info("Pool stats - Active: {}, Idle: {}, Waiting: {}",
            pool.getActiveConnections(),
            pool.getIdleConnections(),
            pool.getThreadsAwaitingConnection());

        // Alert if too many threads waiting
        if (pool.getThreadsAwaitingConnection() > 100) {
            log.warn("Connection pool contention detected!");
        }
    }
}

// Custom metrics for Virtual Threads
@Component
public class VirtualThreadMetrics {

    private final MeterRegistry registry;
    private final AtomicLong activeVirtualThreads = new AtomicLong(0);

    @PostConstruct
    public void registerMetrics() {
        // Active Virtual Threads counter
        Gauge.builder("virtual.threads.active", activeVirtualThreads, AtomicLong::get)
            .description("Number of active virtual threads")
            .register(registry);

        // JVM metrics for carriers
        Gauge.builder("virtual.threads.carriers", this::getCarrierCount)
            .description("Number of carrier threads")
            .register(registry);
    }

    private double getCarrierCount() {
        // Gets the ForkJoinPool carrier count
        return ForkJoinPool.commonPool().getPoolSize();
    }

    // Interceptor to trace requests
    public void trackVirtualThread(Runnable task) {
        activeVirtualThreads.incrementAndGet();
        try {
            task.run();
        } finally {
            activeVirtualThreads.decrementAndGet();
        }
    }
}

# application.yml
# Metrics exposure
management:
  endpoints:
    web:
      exposure:
        include: health,metrics,prometheus
  metrics:
    tags:
      application: ${spring.application.name}

// Checking dependency compatibility
@Configuration
public class CompatibilityCheck {

    // Compatible libraries (recommended versions)
    // - Spring Boot 3.2+ (native support)
    // - HikariCP 5.1+ (ReentrantLock instead of synchronized)
    // - Lettuce 6.3+ (non-blocking I/O)
    // - Jackson 2.16+ (no synchronized)

    // Libraries requiring attention
    // - JDBC drivers: check version
    // - Some legacy HTTP clients

    @Bean
    public CommandLineRunner checkCompatibility() {
        return args -> {
            // Log versions for audit
            log.info("Java version: {}", System.getProperty("java.version"));
            log.info("Virtual threads available: {}",
                Thread.ofVirtual() != null);

            // Support verification
            if (Runtime.version().feature() < 21) {
                throw new IllegalStateException(
                    "Java 21+ required for Virtual Threads");
            }
        };
    }
}

// Configuration for progressive migration
@Configuration
public class DualExecutorConfig {

    // Traditional executor for legacy endpoints
    @Bean("platformExecutor")
    public ExecutorService platformExecutor() {
        return Executors.newFixedThreadPool(200);
    }

    // Virtual Threads executor for new endpoints
    @Bean("virtualExecutor")
    public ExecutorService virtualExecutor() {
        return Executors.newVirtualThreadPerTaskExecutor();
    }
}

@RestController
@RequestMapping("/api/v2")
public class MigratedController {

    @Qualifier("virtualExecutor")
    private final ExecutorService executor;

    // Endpoint migrated to Virtual Threads
    @GetMapping("/users/{id}")
    public CompletableFuture<User> getUser(@PathVariable Long id) {
        return CompletableFuture.supplyAsync(() -> {
            // Business code unchanged
            return userService.findById(id);
        }, executor);
    }
}

# application.yml
# Feature flag for migration
features:
  virtual-threads:
    enabled: true
    endpoints:
      - /api/v2/**
      - /api/reports/**

# Disable for quick rollback
# features.virtual-threads.enabled: false

// Load test with JUnit and Virtual Threads
@SpringBootTest(webEnvironment = WebEnvironment.RANDOM_PORT)
class VirtualThreadLoadTest {

    @LocalServerPort
    private int port;

    @Test
    void shouldHandleHighConcurrency() throws Exception {
        int concurrentRequests = 5000;
        CountDownLatch latch = new CountDownLatch(concurrentRequests);
        AtomicInteger successCount = new AtomicInteger(0);
        AtomicInteger errorCount = new AtomicInteger(0);

        HttpClient client = HttpClient.newHttpClient();

        // Launch 5000 simultaneous requests
        try (var executor = Executors.newVirtualThreadPerTaskExecutor()) {
            for (int i = 0; i < concurrentRequests; i++) {
                executor.submit(() -> {
                    try {
                        HttpRequest request = HttpRequest.newBuilder()
                            .uri(URI.create("http://localhost:" + port + "/api/test"))
                            .build();

                        HttpResponse<String> response = client.send(
                            request, BodyHandlers.ofString());

                        if (response.statusCode() == 200) {
                            successCount.incrementAndGet();
                        } else {
                            errorCount.incrementAndGet();
                        }
                    } catch (Exception e) {
                        errorCount.incrementAndGet();
                    } finally {
                        latch.countDown();
                    }
                });
            }
        }

        latch.await(60, TimeUnit.SECONDS);

        // Performance assertions
        assertThat(successCount.get()).isGreaterThan(4900); // >98% success
        assertThat(errorCount.get()).isLessThan(100);
    }
}

// Combining Virtual Threads + Structured Concurrency
public class StructuredConcurrencyExample {

    public UserDashboard fetchDashboard(Long userId) throws Exception {
        // StructuredTaskScope ensures all tasks complete together
        try (var scope = new StructuredTaskScope.ShutdownOnFailure()) {

            // Three parallel tasks on Virtual Threads
            Subtask<UserProfile> profileTask = scope.fork(() ->
                userService.getProfile(userId));

            Subtask<List<Notification>> notifTask = scope.fork(() ->
                notificationService.getRecent(userId));

            Subtask<AccountBalance> balanceTask = scope.fork(() ->
                accountService.getBalance(userId));

            // Wait for all tasks or fail on first error
            scope.join();
            scope.throwIfFailed();

            // All tasks succeeded - safe aggregation
            return new UserDashboard(
                profileTask.get(),
                notifTask.get(),
                balanceTask.get()
            );
        }
        // If one task fails, others are automatically cancelled
    }
}

// Same logic: imperative vs reactive
@Service
public class ComparisonService {

    // VIRTUAL THREADS APPROACH: classic imperative code
    // Easy to read, debug, and maintain
    public UserData getUserDataImperative(Long id) {
        User user = userRepository.findById(id).orElseThrow();
        List<Order> orders = orderRepository.findByUserId(id);
        PaymentInfo payment = paymentService.getInfo(id);

        return new UserData(user, orders, payment);
    }

    // REACTIVE APPROACH: streams and operators
    // More complex but native backpressure
    public Mono<UserData> getUserDataReactive(Long id) {
        return userRepository.findById(id)
            .zipWith(orderRepository.findByUserId(id).collectList())
            .zipWith(paymentService.getInfo(id))
            .map(tuple -> new UserData(
                tuple.getT1().getT1(),
                tuple.getT1().getT2(),
                tuple.getT2()
            ));
    }
}

// Comparing context approaches
public class ThreadLocalVsScopedValue {

    // CLASSIC APPROACH: ThreadLocal
    // Works but expensive with millions of VT
    private static final ThreadLocal<RequestContext> requestContext =
        new ThreadLocal<>();

    public void processWithThreadLocal(Request request) {
        requestContext.set(new RequestContext(request.getTraceId()));
        try {
            // Context accessible everywhere in the thread
            processRequest();
        } finally {
            requestContext.remove(); // Important to prevent leaks
        }
    }

    // MODERN APPROACH: ScopedValue (Java 21+)
    // More efficient, immutable, explicit scope
    private static final ScopedValue<RequestContext> CONTEXT =
        ScopedValue.newInstance();

    public void processWithScopedValue(Request request) {
        ScopedValue.where(CONTEXT, new RequestContext(request.getTraceId()))
            .run(() -> {
                // Context accessible within this scope
                processRequest();
                // No cleanup needed - automatic at scope end
            });
    }

    private void processRequest() {
        // Context access
        String traceId = CONTEXT.isBound()
            ? CONTEXT.get().getTraceId()
            : "unknown";
        log.info("Processing with trace: {}", traceId);
    }
}