By Ali Abdelrahman

Saga and Outbox Patterns Reimagined: Modern Transaction Management for Distributed Systems

distributed-systemsmicroservicessaga-patternoutbox-patternevent-sourcingtransaction-management

Your microservices are talking to each other. Orders get created, payments get processed, inventory gets updated. Everything looks good until one service fails halfway through. Now you have a payment charged but no order created, or inventory reserved but no payment processed.

This is the distributed transaction problem. In a world of microservices, you can’t just wrap everything in a database transaction. You need patterns that work across service boundaries.

The Saga and Outbox patterns solve this, but they’ve evolved. Modern implementations use idempotency keys, event replay detection, and even AI to handle the complexity. Let’s see how to build these patterns properly.

The Problem We’re Solving

Traditional database transactions work great within a single service. You start a transaction, make changes, and either commit everything or roll it all back. But microservices live in different databases, different processes, sometimes different data centers.

Here’s what breaks:

  • Partial failures: Service A succeeds, Service B fails, Service C never gets called
  • Message duplication: Network retries can send the same message multiple times
  • Inconsistent state: Your system ends up in a state that shouldn’t exist
  • Lost messages: Events get lost between services

The Saga pattern handles the business logic flow. The Outbox pattern ensures reliable message delivery. Together, they give you eventual consistency with proper error handling.

Traditional Saga and Outbox Patterns

Let’s start with the basics. Understanding these patterns helps you see why the modern adaptations matter.

Saga Pattern: Orchestration vs Choreography

Sagas come in two flavors: orchestration and choreography.

Orchestration uses a central coordinator. Think of it as a conductor directing an orchestra. The saga orchestrator tells each service what to do and when to do it.

public class OrderSagaOrchestrator
{
    public async Task<OrderResult> ProcessOrder(OrderRequest request)
    {
        var sagaId = Guid.NewGuid();
        
        try
        {
            // Step 1: Create order
            var order = await _orderService.CreateOrderAsync(request, sagaId);
            
            // Step 2: Reserve inventory
            var inventory = await _inventoryService.ReserveInventoryAsync(
                order.ProductId, order.Quantity, sagaId);
            
            // Step 3: Process payment
            var payment = await _paymentService.ProcessPaymentAsync(
                order.CustomerId, order.TotalAmount, sagaId);
            
            // Step 4: Confirm everything
            await _orderService.ConfirmOrderAsync(order.Id, sagaId);
            
            return new OrderResult { Success = true, OrderId = order.Id };
        }
        catch (Exception ex)
        {
            // Compensate for any completed steps
            await CompensateAsync(sagaId);
            throw;
        }
    }
    
    private async Task CompensateAsync(Guid sagaId)
    {
        // Rollback in reverse order
        await _paymentService.CancelPaymentAsync(sagaId);
        await _inventoryService.ReleaseInventoryAsync(sagaId);
        await _orderService.CancelOrderAsync(sagaId);
    }
}

Choreography lets services communicate directly. Each service knows what to do when it receives an event, and what events to publish when it’s done.

public class OrderService
{
    public async Task HandleOrderCreated(OrderCreatedEvent evt)
    {
        var order = await CreateOrderAsync(evt.OrderData);
        
        // Publish next event
        await _eventBus.PublishAsync(new InventoryReservationRequested
        {
            OrderId = order.Id,
            ProductId = order.ProductId,
            Quantity = order.Quantity,
            SagaId = evt.SagaId
        });
    }
    
    public async Task HandlePaymentProcessed(PaymentProcessedEvent evt)
    {
        await ConfirmOrderAsync(evt.OrderId);
        
        await _eventBus.PublishAsync(new OrderConfirmed
        {
            OrderId = evt.OrderId,
            SagaId = evt.SagaId
        });
    }
}

Outbox Pattern: Reliable Message Delivery

The Outbox pattern solves a simple but critical problem: how do you ensure a message gets sent after a database transaction commits?

Here’s the basic idea:

  1. Start a database transaction
  2. Update your business data
  3. Insert a message into an “outbox” table within the same transaction
  4. Commit the transaction
  5. A separate process reads the outbox and sends messages
-- Outbox table schema
CREATE TABLE outbox_events (
    id BIGSERIAL PRIMARY KEY,
    saga_id UUID NOT NULL,
    event_type VARCHAR(100) NOT NULL,
    event_data JSONB NOT NULL,
    created_at TIMESTAMP DEFAULT NOW(),
    processed_at TIMESTAMP NULL,
    retry_count INTEGER DEFAULT 0,
    idempotency_key VARCHAR(255) UNIQUE
);
public class OutboxEventPublisher
{
    public async Task PublishEventAsync<T>(T eventData, string sagaId, string idempotencyKey)
    {
        using var transaction = await _dbContext.Database.BeginTransactionAsync();
        
        try
        {
            // Update business data
            await _dbContext.SaveChangesAsync();
            
            // Add to outbox
            var outboxEvent = new OutboxEvent
            {
                SagaId = sagaId,
                EventType = typeof(T).Name,
                EventData = JsonSerializer.Serialize(eventData),
                IdempotencyKey = idempotencyKey
            };
            
            _dbContext.OutboxEvents.Add(outboxEvent);
            await _dbContext.SaveChangesAsync();
            
            await transaction.CommitAsync();
        }
        catch
        {
            await transaction.RollbackAsync();
            throw;
        }
    }
}

Common Pitfalls

These patterns work, but they have problems:

  • Message duplication: Network retries can send the same message twice
  • Partial failures: What happens when compensation fails?
  • Lost messages: Outbox processor crashes before sending
  • Infinite retries: Bad messages keep getting retried forever

Modern implementations solve these problems with better tooling and smarter logic.

Modern Adaptations

The patterns haven’t changed, but how we implement them has. Modern systems use idempotency keys, event replay detection, and observability to handle edge cases.

Idempotency Keys

Every operation gets a unique key. If you see the same key twice, you know it’s a duplicate and can safely ignore it.

public class IdempotentSagaOrchestrator
{
    private readonly IIdempotencyStore _idempotencyStore;
    
    public async Task<OrderResult> ProcessOrder(OrderRequest request, string idempotencyKey)
    {
        // Check if we've already processed this request
        var existingResult = await _idempotencyStore.GetResultAsync(idempotencyKey);
        if (existingResult != null)
        {
            return existingResult;
        }
        
        var sagaId = Guid.NewGuid();
        var result = new OrderResult();
        
        try
        {
            // Store the idempotency key before processing
            await _idempotencyStore.StoreKeyAsync(idempotencyKey, sagaId);
            
            // Process the saga
            result = await ProcessSagaSteps(request, sagaId);
            
            // Store the result
            await _idempotencyStore.StoreResultAsync(idempotencyKey, result);
            
            return result;
        }
        catch (Exception ex)
        {
            await CompensateAsync(sagaId);
            throw;
        }
    }
}

Event Replay Detection

Sometimes you need to replay events. Maybe a service was down, or you’re debugging. You need to know which events you’ve already processed.

public class EventReplayDetector
{
    public async Task<bool> ShouldProcessEvent(string eventId, string sagaId)
    {
        // Check if we've already processed this specific event
        var processed = await _eventStore.HasProcessedEventAsync(eventId, sagaId);
        if (processed)
        {
            return false;
        }
        
        // Check if we're in the middle of processing this saga
        var sagaState = await _sagaStore.GetSagaStateAsync(sagaId);
        if (sagaState != null && sagaState.Status == SagaStatus.InProgress)
        {
            // Check if this event is newer than our current position
            return eventId.CompareTo(sagaState.LastProcessedEventId) > 0;
        }
        
        return true;
    }
}

AI-Assisted Anomaly Detection

This is where things get interesting. AI can detect when something’s wrong with your saga execution and suggest fixes.

public class AISagaMonitor
{
    public async Task<SagaHealthCheck> AnalyzeSagaHealth(Guid sagaId)
    {
        var sagaEvents = await _eventStore.GetSagaEventsAsync(sagaId);
        var metrics = await _metricsStore.GetSagaMetricsAsync(sagaId);
        
        // Use AI to detect anomalies
        var analysis = await _aiService.AnalyzeSagaExecutionAsync(new SagaAnalysisRequest
        {
            Events = sagaEvents,
            Metrics = metrics,
            ExpectedPattern = GetExpectedSagaPattern(sagaEvents.First().SagaType)
        });
        
        if (analysis.HasAnomalies)
        {
            return new SagaHealthCheck
            {
                Status = SagaStatus.RequiresAttention,
                Anomalies = analysis.Anomalies,
                SuggestedActions = analysis.SuggestedActions
            };
        }
        
        return new SagaHealthCheck { Status = SagaStatus.Healthy };
    }
}

Kafka Integration with Debezium

Kafka with Debezium gives you real-time event streaming from your database changes. This makes the Outbox pattern even more reliable.

# Debezium connector configuration
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaConnector
metadata:
  name: outbox-connector
spec:
  class: io.debezium.connector.postgresql.PostgresConnector
  tasksMax: 1
  config:
    database.hostname: postgres
    database.port: 5432
    database.user: debezium
    database.password: password
    database.dbname: orders
    database.server.name: orders-server
    table.include.list: public.outbox_events
    transforms: outbox
    transforms.outbox.type: io.debezium.transforms.outbox.EventRouter
    transforms.outbox.route.topic.replacement: ${routedByValue}
    transforms.outbox.table.field.event.id: id
    transforms.outbox.table.field.event.key: saga_id
    transforms.outbox.table.field.event.type: event_type
    transforms.outbox.table.field.event.payload: event_data

OpenTelemetry Tracing

You need to see what’s happening across your distributed saga. OpenTelemetry gives you end-to-end tracing.

public class TracedSagaOrchestrator
{
    private readonly Tracer _tracer;
    
    public async Task<OrderResult> ProcessOrder(OrderRequest request)
    {
        using var activity = _tracer.StartActivity("ProcessOrder");
        activity?.SetTag("order.id", request.OrderId);
        activity?.SetTag("saga.id", request.SagaId);
        
        try
        {
            var result = await ProcessSagaSteps(request);
            activity?.SetStatus(ActivityStatusCode.Ok);
            return result;
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            throw;
        }
    }
    
    private async Task<OrderResult> ProcessSagaSteps(OrderRequest request)
    {
        using var activity = _tracer.StartActivity("ProcessSagaSteps");
        
        // Each step gets its own span
        using var orderSpan = _tracer.StartActivity("CreateOrder");
        var order = await _orderService.CreateOrderAsync(request);
        orderSpan?.SetTag("order.id", order.Id);
        
        using var inventorySpan = _tracer.StartActivity("ReserveInventory");
        var inventory = await _inventoryService.ReserveInventoryAsync(order);
        inventorySpan?.SetTag("inventory.reservation.id", inventory.Id);
        
        using var paymentSpan = _tracer.StartActivity("ProcessPayment");
        var payment = await _paymentService.ProcessPaymentAsync(order);
        paymentSpan?.SetTag("payment.id", payment.Id);
        
        return new OrderResult { Success = true, OrderId = order.Id };
    }
}

Implementation Example

Let’s build a complete example using C# and .NET. This shows how all the pieces fit together.

Saga Orchestrator with Modern Features

public class ModernOrderSagaOrchestrator
{
    private readonly IOrderService _orderService;
    private readonly IInventoryService _inventoryService;
    private readonly IPaymentService _paymentService;
    private readonly IOutboxEventPublisher _outboxPublisher;
    private readonly IIdempotencyStore _idempotencyStore;
    private readonly ISagaStateStore _sagaStore;
    private readonly Tracer _tracer;
    
    public async Task<OrderResult> ProcessOrderAsync(OrderRequest request)
    {
        var sagaId = request.SagaId ?? Guid.NewGuid();
        var idempotencyKey = $"order-{request.CustomerId}-{request.ProductId}-{request.Quantity}";
        
        using var activity = _tracer.StartActivity("ProcessOrder");
        activity?.SetTag("saga.id", sagaId.ToString());
        activity?.SetTag("idempotency.key", idempotencyKey);
        
        // Check idempotency
        var existingResult = await _idempotencyStore.GetResultAsync(idempotencyKey);
        if (existingResult != null)
        {
            activity?.SetTag("idempotent", true);
            return existingResult;
        }
        
        // Initialize saga state
        var sagaState = new SagaState
        {
            Id = sagaId,
            Status = SagaStatus.InProgress,
            StartedAt = DateTime.UtcNow,
            Steps = new List<SagaStep>()
        };
        
        await _sagaStore.SaveSagaStateAsync(sagaState);
        
        try
        {
            // Step 1: Create Order
            var order = await ExecuteSagaStep(
                sagaId,
                "CreateOrder",
                () => _orderService.CreateOrderAsync(request),
                (order) => _orderService.CancelOrderAsync(order.Id)
            );
            
            // Step 2: Reserve Inventory
            var inventory = await ExecuteSagaStep(
                sagaId,
                "ReserveInventory",
                () => _inventoryService.ReserveInventoryAsync(order.ProductId, order.Quantity),
                (inv) => _inventoryService.ReleaseInventoryAsync(inv.Id)
            );
            
            // Step 3: Process Payment
            var payment = await ExecuteSagaStep(
                sagaId,
                "ProcessPayment",
                () => _paymentService.ProcessPaymentAsync(order.CustomerId, order.TotalAmount),
                (pay) => _paymentService.RefundPaymentAsync(pay.Id)
            );
            
            // Step 4: Confirm Order
            await ExecuteSagaStep(
                sagaId,
                "ConfirmOrder",
                () => _orderService.ConfirmOrderAsync(order.Id),
                null // No compensation needed for final step
            );
            
            // Update saga state
            sagaState.Status = SagaStatus.Completed;
            sagaState.CompletedAt = DateTime.UtcNow;
            await _sagaStore.SaveSagaStateAsync(sagaState);
            
            var result = new OrderResult
            {
                Success = true,
                OrderId = order.Id,
                SagaId = sagaId
            };
            
            // Store result for idempotency
            await _idempotencyStore.StoreResultAsync(idempotencyKey, result);
            
            // Publish completion event
            await _outboxPublisher.PublishEventAsync(
                new OrderCompleted { OrderId = order.Id, SagaId = sagaId },
                sagaId.ToString(),
                $"order-completed-{order.Id}"
            );
            
            activity?.SetStatus(ActivityStatusCode.Ok);
            return result;
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            await CompensateSagaAsync(sagaId);
            throw;
        }
    }
    
    private async Task<T> ExecuteSagaStep<T>(
        Guid sagaId,
        string stepName,
        Func<Task<T>> action,
        Func<T, Task> compensation)
    {
        using var activity = _tracer.StartActivity(stepName);
        activity?.SetTag("saga.id", sagaId.ToString());
        activity?.SetTag("step.name", stepName);
        
        try
        {
            var result = await action();
            
            // Record successful step
            var step = new SagaStep
            {
                Name = stepName,
                Status = StepStatus.Completed,
                CompletedAt = DateTime.UtcNow,
                Result = JsonSerializer.Serialize(result)
            };
            
            await _sagaStore.AddSagaStepAsync(sagaId, step);
            
            activity?.SetStatus(ActivityStatusCode.Ok);
            return result;
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            
            // Record failed step
            var step = new SagaStep
            {
                Name = stepName,
                Status = StepStatus.Failed,
                FailedAt = DateTime.UtcNow,
                Error = ex.Message
            };
            
            await _sagaStore.AddSagaStepAsync(sagaId, step);
            throw;
        }
    }
    
    private async Task CompensateSagaAsync(Guid sagaId)
    {
        using var activity = _tracer.StartActivity("CompensateSaga");
        activity?.SetTag("saga.id", sagaId.ToString());
        
        var sagaState = await _sagaStore.GetSagaStateAsync(sagaId);
        if (sagaState == null) return;
        
        // Compensate in reverse order
        var completedSteps = sagaState.Steps
            .Where(s => s.Status == StepStatus.Completed)
            .OrderByDescending(s => s.CompletedAt)
            .ToList();
        
        foreach (var step in completedSteps)
        {
            try
            {
                await CompensateStepAsync(step);
            }
            catch (Exception ex)
            {
                // Log compensation failure but continue
                activity?.SetTag($"compensation.failed.{step.Name}", ex.Message);
            }
        }
        
        sagaState.Status = SagaStatus.Compensated;
        sagaState.CompensatedAt = DateTime.UtcNow;
        await _sagaStore.SaveSagaStateAsync(sagaState);
    }
}

Outbox Event Publisher with Retry Logic

public class ResilientOutboxEventPublisher : BackgroundService
{
    private readonly IServiceProvider _serviceProvider;
    private readonly ILogger<ResilientOutboxEventPublisher> _logger;
    private readonly IEventBus _eventBus;
    
    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        while (!stoppingToken.IsCancellationRequested)
        {
            try
            {
                await ProcessOutboxEventsAsync();
                await Task.Delay(TimeSpan.FromSeconds(5), stoppingToken);
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, "Error processing outbox events");
                await Task.Delay(TimeSpan.FromSeconds(30), stoppingToken);
            }
        }
    }
    
    private async Task ProcessOutboxEventsAsync()
    {
        using var scope = _serviceProvider.CreateScope();
        var dbContext = scope.ServiceProvider.GetRequiredService<ApplicationDbContext>();
        
        var unprocessedEvents = await dbContext.OutboxEvents
            .Where(e => e.ProcessedAt == null && e.RetryCount < 3)
            .OrderBy(e => e.CreatedAt)
            .Take(100)
            .ToListAsync();
        
        foreach (var outboxEvent in unprocessedEvents)
        {
            try
            {
                await ProcessEventAsync(outboxEvent);
                
                outboxEvent.ProcessedAt = DateTime.UtcNow;
                await dbContext.SaveChangesAsync();
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, "Failed to process outbox event {EventId}", outboxEvent.Id);
                
                outboxEvent.RetryCount++;
                if (outboxEvent.RetryCount >= 3)
                {
                    outboxEvent.ProcessedAt = DateTime.UtcNow; // Mark as failed
                    outboxEvent.Error = ex.Message;
                }
                
                await dbContext.SaveChangesAsync();
            }
        }
    }
    
    private async Task ProcessEventAsync(OutboxEvent outboxEvent)
    {
        var eventType = Type.GetType(outboxEvent.EventType);
        if (eventType == null)
        {
            throw new InvalidOperationException($"Unknown event type: {outboxEvent.EventType}");
        }
        
        var eventData = JsonSerializer.Deserialize(outboxEvent.EventData, eventType);
        if (eventData == null)
        {
            throw new InvalidOperationException($"Failed to deserialize event data for {outboxEvent.EventType}");
        }
        
        await _eventBus.PublishAsync(eventData, outboxEvent.SagaId);
    }
}

Message Broker Integration

public class KafkaEventBus : IEventBus
{
    private readonly IProducer<string, string> _producer;
    private readonly ILogger<KafkaEventBus> _logger;
    
    public async Task PublishAsync<T>(T eventData, string sagaId)
    {
        var topic = GetTopicName<T>();
        var key = sagaId;
        var value = JsonSerializer.Serialize(eventData);
        
        try
        {
            var message = new Message<string, string>
            {
                Key = key,
                Value = value,
                Headers = new Headers
                {
                    { "event-type", Encoding.UTF8.GetBytes(typeof(T).Name) },
                    { "saga-id", Encoding.UTF8.GetBytes(sagaId) },
                    { "timestamp", Encoding.UTF8.GetBytes(DateTime.UtcNow.ToString("O")) }
                }
            };
            
            await _producer.ProduceAsync(topic, message);
            _logger.LogInformation("Published event {EventType} for saga {SagaId}", typeof(T).Name, sagaId);
        }
        catch (Exception ex)
        {
            _logger.LogError(ex, "Failed to publish event {EventType} for saga {SagaId}", typeof(T).Name, sagaId);
            throw;
        }
    }
    
    private string GetTopicName<T>()
    {
        var eventName = typeof(T).Name;
        return eventName.ToLowerInvariant().Replace("event", "");
    }
}

Testing and Observability

Testing distributed transactions is hard. You need to test not just the happy path, but also failure scenarios and edge cases.

Unit Testing Saga Steps

[Test]
public async Task ProcessOrder_ShouldCreateOrderSuccessfully()
{
    // Arrange
    var request = new OrderRequest
    {
        CustomerId = "customer-1",
        ProductId = "product-1",
        Quantity = 2,
        TotalAmount = 100.00m
    };
    
    var mockOrderService = new Mock<IOrderService>();
    var mockInventoryService = new Mock<IInventoryService>();
    var mockPaymentService = new Mock<IPaymentService>();
    
    mockOrderService
        .Setup(x => x.CreateOrderAsync(It.IsAny<OrderRequest>()))
        .ReturnsAsync(new Order { Id = "order-1", Status = OrderStatus.Created });
    
    var orchestrator = new ModernOrderSagaOrchestrator(
        mockOrderService.Object,
        mockInventoryService.Object,
        mockPaymentService.Object,
        Mock.Of<IOutboxEventPublisher>(),
        Mock.Of<IIdempotencyStore>(),
        Mock.Of<ISagaStateStore>(),
        Mock.Of<Tracer>()
    );
    
    // Act
    var result = await orchestrator.ProcessOrderAsync(request);
    
    // Assert
    Assert.That(result.Success, Is.True);
    Assert.That(result.OrderId, Is.EqualTo("order-1"));
    
    mockOrderService.Verify(x => x.CreateOrderAsync(It.IsAny<OrderRequest>()), Times.Once);
}

Integration Testing with Testcontainers

[Test]
public async Task ProcessOrder_ShouldCompensateOnPaymentFailure()
{
    // Arrange
    using var postgres = new PostgreSqlTestcontainer("postgres:13")
        .WithDatabase("testdb")
        .WithUsername("test")
        .WithPassword("test");
    
    using var kafka = new KafkaTestcontainer("confluentinc/cp-kafka:latest");
    
    await postgres.StartAsync();
    await kafka.StartAsync();
    
    // Configure services with test containers
    var services = new ServiceCollection();
    services.AddDbContext<ApplicationDbContext>(options =>
        options.UseNpgsql(postgres.ConnectionString));
    
    services.AddSingleton<IEventBus>(provider =>
        new KafkaEventBus(kafka.GetBootstrapServers()));
    
    var serviceProvider = services.BuildServiceProvider();
    
    // Act & Assert
    var orchestrator = serviceProvider.GetRequiredService<ModernOrderSagaOrchestrator>();
    
    var request = new OrderRequest
    {
        CustomerId = "customer-1",
        ProductId = "product-1",
        Quantity = 2,
        TotalAmount = 100.00m
    };
    
    // Mock payment service to fail
    var mockPaymentService = new Mock<IPaymentService>();
    mockPaymentService
        .Setup(x => x.ProcessPaymentAsync(It.IsAny<string>(), It.IsAny<decimal>()))
        .ThrowsAsync(new PaymentException("Insufficient funds"));
    
    // This should trigger compensation
    Assert.ThrowsAsync<PaymentException>(() => orchestrator.ProcessOrderAsync(request));
    
    // Verify compensation was called
    // (You'd need to verify the saga state shows compensation occurred)
}

Observability with OpenTelemetry

public class SagaObservabilityMiddleware
{
    private readonly RequestDelegate _next;
    private readonly Tracer _tracer;
    private readonly IMetrics _metrics;
    
    public async Task InvokeAsync(HttpContext context)
    {
        using var activity = _tracer.StartActivity("SagaRequest");
        activity?.SetTag("http.method", context.Request.Method);
        activity?.SetTag("http.url", context.Request.Path);
        
        var sagaId = context.Request.Headers["X-Saga-Id"].FirstOrDefault();
        if (!string.IsNullOrEmpty(sagaId))
        {
            activity?.SetTag("saga.id", sagaId);
        }
        
        try
        {
            await _next(context);
            activity?.SetStatus(ActivityStatusCode.Ok);
            
            _metrics.GetCounter("saga_requests_total")
                .Add(1, new KeyValuePair<string, object>("status", "success"));
        }
        catch (Exception ex)
        {
            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
            
            _metrics.GetCounter("saga_requests_total")
                .Add(1, new KeyValuePair<string, object>("status", "error"));
            
            throw;
        }
    }
}

The Future: AI Reconciliation and Temporal Workflows

The patterns we’ve covered work well, but the future holds even more interesting possibilities.

AI-Powered Reconciliation

AI can analyze saga execution patterns and automatically fix common problems:

public class AISagaReconciler
{
    public async Task<ReconciliationResult> ReconcileSagaAsync(Guid sagaId)
    {
        var sagaState = await _sagaStore.GetSagaStateAsync(sagaId);
        var events = await _eventStore.GetSagaEventsAsync(sagaId);
        
        // Use AI to analyze the saga state
        var analysis = await _aiService.AnalyzeSagaStateAsync(new SagaAnalysisRequest
        {
            SagaState = sagaState,
            Events = events,
            ExpectedPattern = GetExpectedPattern(sagaState.SagaType)
        });
        
        if (analysis.RequiresReconciliation)
        {
            var reconciliationPlan = await _aiService.GenerateReconciliationPlanAsync(analysis);
            return await ExecuteReconciliationPlanAsync(sagaId, reconciliationPlan);
        }
        
        return new ReconciliationResult { Required = false };
    }
}

Temporal Workflows

Temporal provides a different approach to distributed transactions. Instead of managing state yourself, you define workflows that Temporal executes reliably:

[Workflow]
public class OrderWorkflow
{
    [WorkflowMethod]
    public async Task<OrderResult> ProcessOrderAsync(OrderRequest request)
    {
        var order = await Workflow.ExecuteActivityAsync(
            () => _orderService.CreateOrderAsync(request),
            new ActivityOptions { RetryOptions = RetryOptions.Default });
        
        var inventory = await Workflow.ExecuteActivityAsync(
            () => _inventoryService.ReserveInventoryAsync(order.ProductId, order.Quantity),
            new ActivityOptions { RetryOptions = RetryOptions.Default });
        
        var payment = await Workflow.ExecuteActivityAsync(
            () => _paymentService.ProcessPaymentAsync(order.CustomerId, order.TotalAmount),
            new ActivityOptions { RetryOptions = RetryOptions.Default });
        
        await Workflow.ExecuteActivityAsync(
            () => _orderService.ConfirmOrderAsync(order.Id),
            new ActivityOptions { RetryOptions = RetryOptions.Default });
        
        return new OrderResult { Success = true, OrderId = order.Id };
    }
}

Getting Started

Here’s how to implement these patterns in your system:

  1. Start with the basics: Implement a simple saga orchestrator with compensation logic
  2. Add the outbox pattern: Use it for reliable message delivery
  3. Implement idempotency: Add idempotency keys to prevent duplicate processing
  4. Add observability: Use OpenTelemetry to trace saga execution
  5. Test thoroughly: Write unit and integration tests for failure scenarios
  6. Monitor and improve: Use metrics to identify bottlenecks and failures

Start small. Pick one business process that spans multiple services. Implement the saga pattern for that process. Then add the outbox pattern for reliable messaging. Once you’re comfortable with the basics, add the modern features like idempotency and AI-powered monitoring.

The Bottom Line

Distributed transactions are hard, but they don’t have to be impossible. The Saga and Outbox patterns give you a solid foundation. Modern implementations with idempotency keys, event replay detection, and observability make them production-ready.

The key is to start simple and add complexity gradually. Don’t try to implement everything at once. Focus on getting the basic patterns working first, then add the modern features that make them robust and observable.

Your microservices will thank you. And so will your users when they don’t see partial failures or duplicate charges.

Ashraf Samir is a software architect who helps teams build reliable distributed systems. He writes about microservices, event-driven architecture, and the challenges of building systems that work at scale.

Join the Discussion

Have thoughts on this article? Share your insights and engage with the community.