dotnet-messaging-patterns

Durable messaging patterns for .NET event-driven architectures. Covers publish/subscribe, competing consumers, dead-letter queues, saga/process manager orchestration, and delivery guarantee strategies using Azure Service Bus, RabbitMQ, and MassTransit.

Out of scope: Background service lifecycle and IHostedService registration -- see [skill:dotnet-background-services]. Resilience pipelines and retry policies -- see [skill:dotnet-resilience]. JSON/binary serialization configuration -- see [skill:dotnet-serialization]. In-process producer/consumer queues with Channel<T> -- see [skill:dotnet-channels].

Cross-references: [skill:dotnet-background-services] for hosting message consumers, [skill:dotnet-resilience] for fault tolerance around message handlers, [skill:dotnet-serialization] for message envelope serialization, [skill:dotnet-channels] for in-process queuing patterns.

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Messaging Fundamentals

Message Types

Type	Purpose	Example
Command	Request an action (one recipient)	PlaceOrder, ShipPackage
Event	Notify something happened (many recipients)	OrderPlaced, PaymentReceived
Document	Transfer data between systems	CustomerProfile, ProductCatalog

Commands are sent to a specific queue; events are published to a topic/exchange and delivered to all subscribers. This distinction drives the choice between point-to-point and pub/sub topologies.

Delivery Guarantees

Guarantee	Behavior	Implementation
At-most-once	Fire and forget; message may be lost	No ack, no retry
At-least-once	Message retried until acknowledged; duplicates possible	Ack after processing + retry on failure
Exactly-once	Each message processed exactly once	At-least-once + idempotent consumer

At-least-once with idempotent consumers is the standard approach for durable messaging. True exactly-once requires distributed transactions (which most brokers do not support) or consumer-side deduplication.

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Publish/Subscribe

Azure Service Bus Topics

// Publisher -- send event to a topic
await using var client = new ServiceBusClient(connectionString);
await using var sender = client.CreateSender("order-events");

var message = new ServiceBusMessage(
    JsonSerializer.SerializeToUtf8Bytes(new OrderPlaced(orderId, total)))
{
    Subject = nameof(OrderPlaced),
    ContentType = "application/json",
    MessageId = Guid.NewGuid().ToString()
};

await sender.SendMessageAsync(message, cancellationToken);

// Subscriber -- process events from a subscription
await using var processor = client.CreateProcessor(
    topicName: "order-events",
    subscriptionName: "billing-service",
    new ServiceBusProcessorOptions
    {
        MaxConcurrentCalls = 10,
        AutoCompleteMessages = false
    });

processor.ProcessMessageAsync += async args =>
{
    var body = args.Message.Body.ToObjectFromJson<OrderPlaced>();
    await HandleOrderPlacedAsync(body);
    await args.CompleteMessageAsync(args.Message);
};

processor.ProcessErrorAsync += args =>
{
    logger.LogError(args.Exception, "Error processing message");
    return Task.CompletedTask;
};

await processor.StartProcessingAsync(cancellationToken);

Key packages:

<PackageReference Include="Azure.Messaging.ServiceBus" Version="7.*" />

RabbitMQ Fanout Exchange

// Publisher -- declare exchange and publish
var factory = new ConnectionFactory { HostName = "localhost" };
await using var connection = await factory.CreateConnectionAsync();
await using var channel = await connection.CreateChannelAsync();

await channel.ExchangeDeclareAsync(
    exchange: "order-events",
    type: ExchangeType.Fanout,
    durable: true);

var body = JsonSerializer.SerializeToUtf8Bytes(
    new OrderPlaced(orderId, total));

await channel.BasicPublishAsync(
    exchange: "order-events",
    routingKey: string.Empty,
    body: body);

Key packages:

<PackageReference Include="RabbitMQ.Client" Version="7.*" />

MassTransit Publish

MassTransit abstracts the broker, providing a unified API for Azure Service Bus, RabbitMQ, Amazon SQS, and in-memory transport.

// Registration
builder.Services.AddMassTransit(x =>
{
    x.AddConsumer<OrderPlacedConsumer>();

    x.UsingRabbitMq((context, cfg) =>
    {
        cfg.Host("localhost", "/", h =>
        {
            h.Username("guest");
            h.Password("guest");
        });
        cfg.ConfigureEndpoints(context);
    });
});

// Publisher
public sealed class OrderService(IPublishEndpoint publishEndpoint)
{
    public async Task PlaceOrderAsync(
        Guid orderId, decimal total, CancellationToken ct)
    {
        // Process order...
        await publishEndpoint.Publish(
            new OrderPlaced(orderId, total), ct);
    }
}

// Consumer
public sealed class OrderPlacedConsumer(
    ILogger<OrderPlacedConsumer> logger)
    : IConsumer<OrderPlaced>
{
    public async Task Consume(ConsumeContext<OrderPlaced> context)
    {
        logger.LogInformation(
            "Processing order {OrderId}", context.Message.OrderId);
        await ProcessAsync(context.Message);
    }
}

// Message contract (use records in a shared contracts assembly)
public record OrderPlaced(Guid OrderId, decimal Total);

Key packages:

<PackageReference Include="MassTransit" Version="8.*" />
<!-- Pick ONE transport: -->
<PackageReference Include="MassTransit.RabbitMQ" Version="8.*" />
<!-- OR -->
<PackageReference Include="MassTransit.Azure.ServiceBus.Core" Version="8.*" />

---

Competing Consumers

Multiple consumer instances process messages from the same queue in parallel. The broker delivers each message to exactly one consumer, distributing load across instances.

Pattern

Queue: order-processing
  ├── Consumer Instance A  (picks message 1)
  ├── Consumer Instance B  (picks message 2)
  └── Consumer Instance C  (picks message 3)

Azure Service Bus -- Scaling Consumers

// Multiple instances reading from the same queue automatically compete.
// MaxConcurrentCalls controls per-instance parallelism.
var processor = client.CreateProcessor("order-processing",
    new ServiceBusProcessorOptions
    {
        MaxConcurrentCalls = 20,
        PrefetchCount = 50,
        AutoCompleteMessages = false
    });

MassTransit -- Concurrency Limits

x.AddConsumer<OrderProcessor>(cfg =>
{
    cfg.UseConcurrentMessageLimit(10);
});

Ordering Considerations

Competing consumers sacrifice strict ordering for throughput. When order matters:

• Azure Service Bus: Use sessions (RequiresSession = true) to guarantee FIFO within a session ID (e.g., per customer)
• RabbitMQ: Use a single consumer per queue, or consistent-hash exchange to partition by key
• MassTransit: Configure UseMessagePartitioner for key-based ordering

---

Dead-Letter Queues

Dead-letter queues (DLQs) capture messages that cannot be processed after exhausting retries. They prevent poison messages from blocking the main queue.

Why Messages Are Dead-Lettered

Reason	Trigger
Max delivery attempts exceeded	Message failed processing N times
TTL expired	Message sat in queue past its time-to-live
Consumer rejection	Consumer explicitly dead-letters the message
Queue length exceeded	Queue overflow policy routes to DLQ

Azure Service Bus DLQ

// Dead-letter a message with reason
await args.DeadLetterMessageAsync(
    args.Message,
    deadLetterReason: "ValidationFailed",
    deadLetterErrorDescription: "Missing required field: CustomerId");

// Read from the dead-letter sub-queue
await using var dlqReceiver = client.CreateReceiver(
    "order-processing",
    new ServiceBusReceiverOptions
    {
        SubQueue = SubQueue.DeadLetter
    });

while (true)
{
    var message = await dlqReceiver.ReceiveMessageAsync(
        TimeSpan.FromSeconds(5), cancellationToken);
    if (message is null) break;

    logger.LogWarning(
        "DLQ message: {Reason} - {Description}",
        message.DeadLetterReason,
        message.DeadLetterErrorDescription);

    // Inspect, fix, and re-submit or discard
    await dlqReceiver.CompleteMessageAsync(message);
}

MassTransit Error/Fault Queues

MassTransit automatically creates _error and _skipped queues. Failed messages after retry exhaustion move to the error queue with fault metadata.

// Configure retry before dead-lettering
x.AddConsumer<OrderProcessor>(cfg =>
{
    cfg.UseMessageRetry(r => r.Intervals(
        TimeSpan.FromSeconds(1),
        TimeSpan.FromSeconds(5),
        TimeSpan.FromSeconds(15)));
});

DLQ Monitoring

Always monitor DLQ depth with alerts. Unmonitored DLQs accumulate silently until data is lost or stale.

---

Saga / Process Manager

Sagas coordinate multi-step business processes across services. Each step publishes events that trigger the next step, with compensation logic for failures.

Choreography vs Orchestration

Style	How it works	Use when
Choreography	Services react to events independently; no central coordinator	Simple flows, few steps, loosely coupled
Orchestration	A saga/process manager directs each step	Complex flows, compensation needed, visibility required

MassTransit State Machine Saga

// Saga state
public class OrderState : SagaStateMachineInstance
{
    public Guid CorrelationId { get; set; }
    public string CurrentState { get; set; } = default!;
    public Guid OrderId { get; set; }
    public decimal Total { get; set; }
    public DateTime? PaymentReceivedAt { get; set; }
}

// State machine definition
public sealed class OrderStateMachine : MassTransitStateMachine<OrderState>
{
    public State Submitted { get; private set; } = default!;
    public State PaymentPending { get; private set; } = default!;
    public State Completed { get; private set; } = default!;
    public State Faulted { get; private set; } = default!;

    public Event<OrderSubmitted> OrderSubmitted { get; private set; } = default!;
    public Event<PaymentReceived> PaymentReceived { get; private set; } = default!;
    public Event<PaymentFailed> PaymentFailed { get; private set; } = default!;

    public OrderStateMachine()
    {
        InstanceState(x => x.CurrentState);

        Event(() => OrderSubmitted,
            x => x.CorrelateById(ctx => ctx.Message.OrderId));
        Event(() => PaymentReceived,
            x => x.CorrelateById(ctx => ctx.Message.OrderId));
        Event(() => PaymentFailed,
            x => x.CorrelateById(ctx => ctx.Message.OrderId));

        Initially(
            When(OrderSubmitted)
                .Then(ctx =>
                {
                    ctx.Saga.OrderId = ctx.Message.OrderId;
                    ctx.Saga.Total = ctx.Message.Total;
                })
                .Publish(ctx => new RequestPayment(
                    ctx.Saga.OrderId, ctx.Saga.Total))
                .TransitionTo(PaymentPending));

        During(PaymentPending,
            When(PaymentReceived)
                .Then(ctx =>
                    ctx.Saga.PaymentReceivedAt = DateTime.UtcNow)
                .Publish(ctx => new FulfillOrder(ctx.Saga.OrderId))
                .TransitionTo(Completed),
            When(PaymentFailed)
                .Publish(ctx => new CancelOrder(ctx.Saga.OrderId))
                .TransitionTo(Faulted));
    }
}

// Registration -- requires MassTransit.EntityFrameworkCore package for EF persistence
// NuGet: MassTransit.EntityFrameworkCore Version="8.*"
builder.Services.AddMassTransit(x =>
{
    x.AddSagaStateMachine<OrderStateMachine, OrderState>()
        .EntityFrameworkRepository(r =>
        {
            r.ExistingDbContext<SagaDbContext>();
            r.UsePostgres();
        });

    x.UsingRabbitMq((context, cfg) =>
    {
        cfg.ConfigureEndpoints(context);
    });
});

Saga Persistence

Store	Package	Use when
Entity Framework Core	MassTransit.EntityFrameworkCore	Already using EF Core; need transactions
MongoDB	MassTransit.MongoDb	Document-oriented state; high throughput
Redis	MassTransit.Redis	Ephemeral sagas; low latency
In-Memory	Built-in	Testing only -- state lost on restart

Compensation Pattern

When a saga step fails, publish compensating commands to undo prior steps:

OrderSubmitted -> RequestPayment -> PaymentReceived -> ReserveInventory
                                                          |
                                                     InventoryFailed
                                                          |
                                                    RefundPayment (compensation)
                                                          |
                                                    CancelOrder (compensation)

---

Idempotent Consumers

At-least-once delivery means consumers may receive the same message multiple times. Idempotent consumers ensure repeated processing produces the same result.

Database-Based Deduplication

public sealed class IdempotentOrderConsumer(
    AppDbContext db,
    ILogger<IdempotentOrderConsumer> logger)
    : IConsumer<OrderPlaced>
{
    public async Task Consume(ConsumeContext<OrderPlaced> context)
    {
        var messageId = context.MessageId
            ?? throw new InvalidOperationException("Missing MessageId");

        // Check if already processed
        var exists = await db.ProcessedMessages
            .AnyAsync(m => m.MessageId == messageId);

        if (exists)
        {
            logger.LogInformation(
                "Duplicate message {MessageId}, skipping", messageId);
            return;
        }

        // Process the message
        await ProcessOrderAsync(context.Message);

        // Record as processed
        db.ProcessedMessages.Add(new ProcessedMessage
        {
            MessageId = messageId,
            ProcessedAt = DateTime.UtcNow,
            ConsumerType = nameof(IdempotentOrderConsumer)
        });

        await db.SaveChangesAsync();
    }
}

Natural Idempotency

Prefer operations that are naturally idempotent:

• Upserts (INSERT ... ON CONFLICT UPDATE) instead of blind inserts
• Conditional updates (UPDATE ... WHERE Status = 'Pending') instead of unconditional
• Deterministic IDs derived from message content instead of auto-generated

---

Message Envelope Pattern

Wrap message payloads in a standard envelope with metadata for tracing, versioning, and routing.

public sealed record MessageEnvelope<T>(
    string MessageId,
    string MessageType,
    DateTimeOffset Timestamp,
    string CorrelationId,
    string Source,
    int Version, // Schema version for backward-compatible deserialization
    T Payload);

MassTransit provides this automatically via ConsumeContext (MessageId, CorrelationId, Headers). When using raw broker clients, implement envelopes explicitly.

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Agent Gotchas

1. Do not use auto-complete with Azure Service Bus -- set AutoCompleteMessages = false and call CompleteMessageAsync after successful processing. Auto-complete acknowledges before processing finishes, risking data loss on failure.
2. Do not forget to handle poison messages -- always configure max delivery count and DLQ monitoring. Without these, a single bad message blocks the entire queue indefinitely.
3. Do not use in-memory saga persistence in production -- saga state is lost on restart, leaving business processes in unknown states. Use Entity Framework, MongoDB, or Redis persistence.
4. Do not assume message ordering across partitions -- competing consumers and topic subscriptions deliver messages out of order by default. Use sessions or partitioning when order matters.
5. Do not skip idempotency for at-least-once consumers -- brokers may redeliver on timeout, network glitch, or consumer restart. Every consumer must handle duplicate messages safely.
6. Do not hardcode connection strings -- use environment variables or Azure Key Vault references. For local development, use user secrets or .env files excluded from source control.

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References

• Azure Service Bus documentation
• Azure Service Bus client library for .NET
• RabbitMQ .NET client documentation
• MassTransit documentation
• MassTransit sagas
• Enterprise Integration Patterns