Prosody: C# Bindings for Kafka

Prosody offers C# bindings to the Prosody Kafka client, providing features for message production and consumption, including configurable retry mechanisms, failure handling strategies, and integrated OpenTelemetry support for distributed tracing.

Features

• Kafka Consumer: Per-key ordering with cross-key concurrency, offset management, consumer groups
• Kafka Producer: Idempotent delivery with configurable retries
• Timer System: Persistent scheduled execution backed by Cassandra or in-memory store
• Keyed State: Per-key persistent state (value/map/deque) with transactional, at-least-once semantics
• Quality of Service: Fair scheduling limits concurrency and prevents failures from starving fresh traffic. Pipeline mode adds deferred retry and monopolization detection
• Distributed Tracing: OpenTelemetry integration for tracing message flow across services
• Error Monitoring: Optional Sentry integration for automatic handler exception reporting
• Backpressure: Pauses partitions when handlers fall behind
• Mocking: In-memory Kafka broker for tests (WithMock(true))
• Failure Handling: Pipeline (retry forever), Low-Latency (dead letter), Best-Effort (log and skip)

Installation

Add the NuGet package to your project:

dotnet add package ProsodyEvents.Prosody

Quick Start

using Prosody;

// Initialize the client with the builder pattern
await using var client = ProsodyClientBuilder.Create()
    // Bootstrap servers should normally be set using the PROSODY_BOOTSTRAP_SERVERS environment variable
    .WithBootstrapServers("localhost:9092")
    // To allow loopbacks, the SourceSystem must be different from the GroupId.
    // Normally, the SourceSystem would be left unspecified, which would default to the GroupId.
    .WithSourceSystem("my-application-source")
    // The GroupId should be set to the name of your application
    .WithGroupId("my-application")
    // Topics the client should subscribe to
    .WithSubscribedTopics("my-topic")
    .Build();

// Define a message handler
var messageHandler = new MyHandler();

// Subscribe to messages using the message handler
await client.SubscribeAsync(messageHandler);

// Send a message to a topic
await client.SendAsync("my-topic", "message-key", new { Content = "Hello, Kafka!" });

// Ensure proper shutdown when done
await client.UnsubscribeAsync();

// Handler implementation
public class MyHandler : IProsodyHandler<MyPayload>
{
    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        // Process the received message
        var payload = message.Payload;
        Console.WriteLine($"Received message: {payload}");

        // Schedule a timer for delayed processing (requires Cassandra unless Mock = true)
        if (payload?.ScheduleFollowup == true)
        {
            var futureTime = DateTimeOffset.UtcNow.AddSeconds(30);
            await prosodyContext.ScheduleAsync(futureTime);
        }
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken)
    {
        // Handle timer firing
        Console.WriteLine($"Timer fired for key: {timer.Key} at {timer.Time}");
        return Task.CompletedTask;
    }
}

Architecture

Prosody enables efficient, parallel processing of Kafka messages while maintaining order for messages with the same key:

• Partition-Level Parallelism: Separate management of each Kafka partition
• Key-Based Queuing: Ordered processing for each key within a partition
• Concurrent Processing: Simultaneous processing of different keys
• Backpressure Management: Pause consumption from backed-up partitions

Quality of Service

All modes use fair scheduling to limit concurrency and distribute execution time. Pipeline mode adds deferred retry and monopolization detection.

Fair Scheduling (All Modes)

The scheduler controls which message runs next and how many run concurrently.

Virtual Time (VT): Each key accumulates VT equal to its handler execution time. The scheduler picks the key with the lowest VT. A key that runs for 500ms accumulates 500ms of VT; a key that hasn't run recently has zero VT and gets priority.

Two-Class Split: Normal messages and failure retries have separate VT pools. The scheduler allocates execution time between them (default: 70% normal, 30% failure). During a failure spike, retries get at most 30% of execution time—fresh messages continue processing.

Starvation Prevention: Tasks receive a quadratic priority boost based on wait time. A task waiting 2 minutes (configurable) gets maximum boost, overriding VT disadvantage.

Deferred Retry (Pipeline Mode)

Moves failing keys to timer-based retry so the partition can continue processing other keys.

On transient failure: store the message offset in Cassandra, schedule a timer, return success. The partition advances. When the timer fires, reload the message from Kafka and retry.

// Configure defer behavior
await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Configure(options =>
    {
        options.DeferEnabled = true;                              // Enable deferral (default: true)
        options.DeferBase = TimeSpan.FromSeconds(1);              // Wait 1s before first retry
        options.DeferMaxDelay = TimeSpan.FromHours(24);           // Cap at 24 hours
        options.DeferFailureThreshold = 0.9;                      // Disable when >90% failing
    })
    .Build();

Failure Rate Gating: When >90% of recent messages fail, deferral disables. The retry middleware blocks the partition, applying backpressure upstream.

Monopolization Detection (Pipeline Mode)

Rejects keys that consume too much execution time.

The middleware tracks per-key execution time in 5-minute rolling windows. Keys exceeding 90% of window time are rejected with a transient error, routing them through defer.

// Configure monopolization detection
await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Configure(options =>
    {
        options.MonopolizationEnabled = true;                     // Enable detection (default: true)
        options.MonopolizationThreshold = 0.9;                    // Reject keys using >90% of window
        options.MonopolizationWindow = TimeSpan.FromMinutes(5);   // 5-minute window
    })
    .Build();

Handler Timeout

Handlers are automatically cancelled if they exceed a deadline:

await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Configure(options =>
    {
        options.Timeout = TimeSpan.FromSeconds(30);               // Cancel after 30 seconds
        options.StallThreshold = TimeSpan.FromSeconds(60);        // Report unhealthy after 60 seconds
    })
    .Build();

When a handler times out, prosodyContext.ShouldCancel becomes true and the CancellationToken is cancelled. The handler should exit promptly. If not specified, timeout defaults to 80% of StallThreshold.

Configuration

For the complete configuration reference, see CONFIGURATION.md.

ClientOptions properties take precedence. Unset properties use environment variables, then library defaults.

Liveness and Readiness Probes

Prosody includes a built-in probe server for consumer-based applications that provides health check endpoints. The probe server is tied to the consumer's lifecycle and offers two main endpoints:

1. /readyz: A readiness probe that checks if any partitions are assigned to the consumer. Returns a success status only when the consumer has at least one partition assigned, indicating it's ready to process messages.

2. /livez: A liveness probe that checks if any partitions have stalled (haven't processed a message within a configured time threshold).

Configure the probe server using the builder:

await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .WithProbePort(8000)                                          // Set to 0 to disable
    .Configure(options =>
    {
        options.StallThreshold = TimeSpan.FromSeconds(15);        // 15 seconds before considering a partition stalled
    })
    .Build();

Or via environment variables:

PROSODY_PROBE_PORT=8000  # Set to 0 to disable
PROSODY_STALL_THRESHOLD=15s  # Default stall detection threshold

Important Notes

1. The probe server starts automatically when the consumer is subscribed and stops when unsubscribed.
2. A partition is considered "stalled" if it hasn't processed a message within the StallThreshold duration.
3. The stall threshold should be set based on your application's message processing latency and expected message frequency.
4. Setting the threshold too low might cause false positives, while setting it too high could delay detection of actual issues.
5. The probe server is only active when consuming messages (not for producer-only usage).

You can monitor the stall state programmatically using the client's methods:

// Get the number of partitions currently assigned to this consumer
var partitionCount = await client.AssignedPartitionCountAsync();

// Check if the consumer has stalled partitions
if (await client.IsStalledAsync())
{
    Console.WriteLine("Consumer has stalled partitions");
}

Advanced Usage

Pipeline Mode

Pipeline mode is the default mode. Ensures ordered processing, retrying failed operations indefinitely:

// Initialize client in pipeline mode
await using var client = ProsodyClientBuilder.Create()
    .WithMode(ClientMode.Pipeline)  // Explicitly set pipeline mode (this is the default)
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Build();

Low-Latency Mode

Prioritizes quick processing, sending persistently failing messages to a failure topic:

// Initialize client in low-latency mode
await using var client = ProsodyClientBuilder.Create()
    .WithMode(ClientMode.LowLatency)  // Set low-latency mode
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .WithFailureTopic("failed-messages")  // Specify a topic for failed messages
    .Build();

Best-Effort Mode

Optimized for development environments or services where message processing failures are acceptable:

// Initialize client in best-effort mode
await using var client = ProsodyClientBuilder.Create()
    .WithMode(ClientMode.BestEffort)  // Set best-effort mode
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Build();

Event Type Filtering

Prosody supports filtering messages based on event type prefixes, allowing your consumer to process only specific types of events:

// Process only events with types starting with "user." or "account."
await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .WithAllowedEvents("user.", "account.")
    .Build();

Or via environment variables:

PROSODY_ALLOWED_EVENTS=user.,account.

Matching Behavior

Prefixes must match exactly from the start of the event type:

✓ Matches:

• {"type": "user.created"} matches prefix user.
• {"type": "account.deleted"} matches prefix account.

✗ No Match:

• {"type": "admin.user.created"} doesn't match user.
• {"type": "my.account.deleted"} doesn't match account.
• {"type": "notification"} doesn't match any prefix

If no prefixes are configured, all messages are processed. Messages without a type field are always processed.

Source System Deduplication

Prosody prevents processing loops in distributed systems by tracking the source of each message:

// Consumer and producer in one application
await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-service")
    .WithSourceSystem("my-service-producer")  // Must differ from GroupId to allow loopbacks; defaults to GroupId
    .WithSubscribedTopics("my-topic")
    .Build();

Or via environment variable:

PROSODY_SOURCE_SYSTEM=my-service-producer

How It Works

1. Producers add a source-system header to all outgoing messages.
2. Consumers check this header on incoming messages.
3. If a message's source system matches the consumer's group ID, the message is skipped.

This prevents endless loops where a service consumes its own produced messages.

Message Deduplication

Prosody automatically deduplicates messages using the id field in their JSON payload. Consecutive messages with the same ID and key are processed only once.

// Messages with IDs are deduplicated per key
await client.SendAsync("my-topic", "key1", new
{
    Id = "msg-123",      // Message will be processed
    Content = "Hello!"
});

await client.SendAsync("my-topic", "key1", new
{
    Id = "msg-123",      // Message will be skipped (duplicate)
    Content = "Hello again!"
});

await client.SendAsync("my-topic", "key2", new
{
    Id = "msg-123",      // Message will be processed (different key)
    Content = "Hello!"
});

Deduplication uses a global in-memory cache shared across all partitions, which survives partition reassignments within the same process. For cross-restart deduplication, a Cassandra-backed persistent store is used when Cassandra is configured.

Deduplication is always active. IdempotenceCacheSize must be greater than 0; a value of 0 (via either the option or PROSODY_IDEMPOTENCE_CACHE_SIZE=0) is rejected when the client is built. The cache capacity can be tuned:

await using var client = ProsodyClientBuilder.Create()
    .WithGroupId("my-consumer-group")
    .WithSubscribedTopics("my-topic")
    .Configure(options => options.IdempotenceCacheSize = 16384)   // Tune the shared cache capacity
    .Build();

To invalidate all previously recorded dedup entries and force reprocessing, change the version string:

.Configure(options => options.IdempotenceVersion = "2")          // Invalidate all prior dedup records

The Cassandra TTL for dedup records defaults to 7 days and can be adjusted:

.Configure(options => options.IdempotenceTtl = TimeSpan.FromDays(14))  // Keep records for 14 days

Note that in-memory deduplication is best-effort and not guaranteed. Duplicates can still occur when instances restart if Cassandra is not configured.

Timer Functionality

Prosody supports timer-based delayed execution within message handlers. When a timer fires, your handler's OnTimerAsync method will be called:

public class MyHandler : IProsodyHandler<MyPayload>
{
    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        // Schedule a timer to fire in 30 seconds
        var futureTime = DateTimeOffset.UtcNow.AddSeconds(30);
        await prosodyContext.ScheduleAsync(futureTime);

        // Schedule multiple timers
        var oneMinute = DateTimeOffset.UtcNow.AddMinutes(1);
        var twoMinutes = DateTimeOffset.UtcNow.AddMinutes(2);
        await prosodyContext.ScheduleAsync(oneMinute);
        await prosodyContext.ScheduleAsync(twoMinutes);

        // Check what's scheduled
        var scheduledTimes = await prosodyContext.ScheduledAsync();
        Console.WriteLine($"Scheduled timers: {scheduledTimes.Length}");
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken)
    {
        Console.WriteLine("Timer fired!");
        Console.WriteLine($"Key: {timer.Key}");
        Console.WriteLine($"Scheduled time: {timer.Time}");
        return Task.CompletedTask;
    }
}

Timer Methods

The context provides timer scheduling methods that allow you to delay execution or implement timeout behavior:

• ScheduleAsync(DateTimeOffset time): Schedules a timer to fire at the specified time
• ClearAndScheduleAsync(DateTimeOffset time): Clears all timers and schedules a new one
• UnscheduleAsync(DateTimeOffset time): Removes a timer scheduled for the specified time
• ClearScheduledAsync(): Removes all scheduled timers
• ScheduledAsync(): Returns an array of all scheduled timer times

Timer Object

When a timer fires, the OnTimerAsync method receives a timer object with these properties:

• Key (string): The entity key identifying what this timer belongs to
• Time (DateTimeOffset): The time when this timer was scheduled to fire

Note: Timer precision is limited to seconds due to the underlying storage format. Sub-second precision in scheduled times will be rounded to the nearest second.

Timer Configuration

Timer functionality requires Cassandra for persistence unless running in mock mode. Configure Cassandra connection via environment variable:

PROSODY_CASSANDRA_NODES=localhost:9042  # Required for timer persistence

Or programmatically when creating the client:

await using var client = ProsodyClientBuilder.Create()
    .WithBootstrapServers("localhost:9092")
    .WithGroupId("my-application")
    .WithSubscribedTopics("my-topic")
    .Configure(options => options.CassandraNodes = ["localhost:9042"])  // Required unless Mock = true
    .Build();

For testing, you can use mock mode to avoid Cassandra dependency:

// Mock mode for testing (timers work but aren't persisted)
await using var client = ProsodyClientBuilder.Create()
    .WithBootstrapServers("localhost:9092")
    .WithGroupId("my-application")
    .WithSubscribedTopics("my-topic")
    .WithMock(true)  // No Cassandra required in mock mode
    .Build();

Keyed State

Keyed state gives every Kafka key its own durable working memory. Prosody automatically uses the current message or timer key, so a handler can relate the current event to earlier events for that key. State survives restarts and rebalances. By default, changes become visible only when the event succeeds.

Use keyed state for time-aware stream processing: counters, deduplication, rolling aggregates, pending work, and per-key workflows. Keep your relational database as the source of truth for business data and for work that needs joins or ad hoc queries. Reconstructing stream state with repeated database queries can be slow and expensive; keyed state is built for that job.

Most collections should have a TTL. Set it comfortably beyond the longest timer or workflow that uses the state; Prosody validates the minimum supported TTL. Omit it only when keeping inactive keys forever is intentional.

Published state

Published state lets another client read a JSON value, map, or deque without subscribing to the owner's topics. Use the same typed definition for the owned collection and its read-only view. The owner sets published: true, names its Subsystem, and registers the definition as usual:

var currentOrder = StateDefinition.Value<Order>("current-order", published: true);
var options = new ClientOptions
{
    GroupId = "order-writer",
    Subsystem = "checkout",
    StateCollections = [currentOrder],
};

// Inside the owner's handler, the event supplies the user key.
var ownedOrder = context.State(currentOrder);
await ownedOrder.SetAsync(updatedOrder, cancellationToken);

Another client opens a reader by naming the subsystem and passing that same definition. The reader is independent of subscriptions and only returns committed state:

PublishedValue<Order> orderReader = await client.StateAsync("checkout", currentOrder);
StateValue<Order> value = await orderReader.GetAsync("customer-123", cancellationToken);

Published readers provide the owned collection's read operations without its mutations. An owned handle gets the user key from the current event; a published reader is outside a handler, so every operation takes that key explicitly. Map and deque enumeration returns IAsyncEnumerable<T> and reads in chunks rather than loading the entire collection. Pass ScanDirection.Backward when reverse order is useful.

The default cache window is five seconds unless the client configuration changes it. Set readCache: StateReadCache.For(ttl) on a definition to choose a different freshness window, or use StateReadCache.Disabled to read durable storage on every operation. To stop publishing a collection, deploy its definition with published: false while keeping it registered and retaining Subsystem for that deployment.

A counter for each key

Declare each collection once, register it on the client, and ask the event context for the current key's state:

var count = StateDefinition.Value<int>("count", ttl: TimeSpan.FromDays(30));

public sealed class CountHandler(ValueStateDefinition<int> count)
    : IProsodyHandler<Event>
{
    public async Task OnMessageAsync(
        ProsodyContext context,
        Message<Event> message,
        CancellationToken cancellationToken)
    {
        var state = context.State(count);
        var current = (await state.GetAsync(cancellationToken)).GetValueOrDefault(0);
        await state.SetAsync(current + 1, cancellationToken);
    }
}

var client = ProsodyClientBuilder.Create()
    .WithStateCollections(count)
    .Build();

Here, counters expire after 30 days without an update.

Window activity into one notification

This example turns a burst of activity into two useful notifications. It sends the first event immediately, collects later events for five minutes, then sends one summary. Because the user ID is the Kafka key, every user gets an independent window.

var window = StateDefinition.Value<bool>("window", ttl: TimeSpan.FromDays(1));
var pending = StateDefinition.MessageDeque<Activity>(
    "pending", ttl: TimeSpan.FromDays(1), capacity: 100);

public async Task OnMessageAsync(
    ProsodyContext context,
    Message<Activity> message,
    CancellationToken cancellationToken)
{
    var windowState = context.State(window);
    var pendingState = context.State(pending);

    if ((await windowState.GetAsync(cancellationToken)).GetValueOrDefault(false))
    {
        await pendingState.PushBackAsync(message, cancellationToken);
        return;
    }

    await Notify(message.Key, [message]);
    await windowState.SetAsync(true, cancellationToken);
    await context.ClearAndScheduleAsync(
        DateTimeOffset.UtcNow + TimeSpan.FromMinutes(5));
}

public async Task OnTimerAsync(
    ProsodyContext context,
    ProsodyTimer timer,
    CancellationToken cancellationToken)
{
    var pendingState = context.State(pending);
    var batch = new List<Message<Activity>>();
    await foreach (var message in pendingState.WithCancellation(cancellationToken))
        batch.Add(message);

    if (batch.Count > 0) await Notify(timer.Key, batch);
    await pendingState.ClearAsync(cancellationToken);
    await context.State(window).ClearAsync(cancellationToken);
}

See the complete, compiled example for imports, types, client setup, and NotifyAsync: examples/keyed_state_windowing.cs.

Why this works:

• Register both definitions with WithStateCollections before Build(). Keyed state uses Cassandra unless Mock = true.
• Use ClearAndScheduleAsync, not ScheduleAsync, so a retried event does not add another timer for the same key.
• capacity: 100 and the one-day TTL prevent an inactive or unusually busy key from retaining an unlimited backlog. Since this example only pushes at the back, overflow drops the oldest saved message.
• A MessageDeque requires the original Kafka messages to remain available for the whole window. Use a plain Deque of payloads if topic retention or compaction cannot guarantee that.
• Prosody runs one handler at a time for each key, so a user's message and timer handlers cannot overlap.
• Sending a notification is outside Prosody's state transaction and may happen again after a retry. Give notifications a stable idempotency key, or send them through an outbox, when duplicates matter.

Collections and handles

A definition gives a collection a stable name, kind, and options. Register it once on the client, then pass the same definition to context.State() to access the current key. Do not reuse a persisted name for a different collection kind or payload type.

Create handles inside the handler and do not retain them or their iterators afterward.

Collection	JSON payload	Kafka message	Main operations
Value	StateDefinition.Value<T>	StateDefinition.MessageValue<TPayload>	GetAsync, SetAsync, ClearAsync
Ordered string map	StateDefinition.Map<TValue>	StateDefinition.MessageMap<TPayload>	GetAsync, GetManyAsync, ContainsKeyAsync, SetAsync, RemoveAsync, EnumerateAsync, ClearAsync
Deque	StateDefinition.Deque<T>	StateDefinition.MessageDeque<TPayload>	PushBackAsync, PushFrontAsync, PopBackAsync, PopFrontAsync, GetAsync, CountAsync, EnumerateAsync, ClearAsync

Map and deque scans use await foreach. Map keys are strings. Reads return StateValue<T>, which distinguishes an absent value from a stored default(T). null cannot be stored—use ClearAsync or RemoveAsync instead. Payload types guide JSON serialization but do not add runtime validation.

When changes become visible

Reads inside a handler see its earlier writes. The default behavior is the safest choice for most handlers: Prosody buffers those changes and publishes them together when the event succeeds. If the handler throws, none of its pending changes become visible.

Each collection also offers explicit controls for workflows that need different behavior:

• readUncommitted: true writes that collection's changes after the handler succeeds but before the event is recorded as complete. A crash in between can leave the changes visible even though the event is retried. Use it only for idempotent changes, where processing the same event again produces the same stored result.
• await state.CommitAsync() immediately publishes this collection's pending changes. They remain visible even if the handler later throws and the event is retried.
• await state.RollbackAsync() discards this collection's pending changes since its last CommitAsync(). It cannot undo changes that were already committed.

Keyed-state payloads use the client's JsonSerializerOptions. For AOT or trimmed builds, include every state payload type in the source-generated JsonSerializerContext; see AOT / Trim-safe Usage.

OpenTelemetry Tracing

Prosody supports OpenTelemetry tracing, allowing you to monitor and analyze the performance of your Kafka-based applications. The library will emit traces using the OTLP protocol if the OTEL_EXPORTER_OTLP_ENDPOINT environment variable is defined.

Note: Prosody emits its own traces separately because it uses its own tracing runtime, as it would be expensive to send all traces to C#.

Required Packages

To use OpenTelemetry tracing with Prosody, you need to install the following packages:

dotnet add package OpenTelemetry
dotnet add package OpenTelemetry.Extensions.Hosting
dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol

Initializing Tracing

To initialize tracing in your application:

using OpenTelemetry;
using OpenTelemetry.Resources;
using OpenTelemetry.Trace;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddOpenTelemetry()
    .ConfigureResource(resource => resource.AddService("my-service-name"))
    .WithTracing(tracing => tracing
        .AddSource("my-service-name")
        .AddOtlpExporter());

var app = builder.Build();

Setting OpenTelemetry Environment Variables

Set the following standard OpenTelemetry environment variables:

OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
OTEL_SERVICE_NAME=my-service-name

For more information on these and other OpenTelemetry environment variables, refer to the OpenTelemetry specification.

Using Tracing in Your Application

After initializing tracing, you can define spans in your application, and they will be properly propagated through Kafka:

using System.Diagnostics;

public class MyHandler : IProsodyHandler<MyPayload>
{
    private static readonly ActivitySource ActivitySource = new("my-service-name");

    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        using var activity = ActivitySource.StartActivity("process-message");

        // Process the received message
        activity?.AddEvent(new ActivityEvent("message.received"));

        Console.WriteLine($"Received message: {message.Payload}");
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken) => Task.CompletedTask;
}

Span Linking

By default, message execution spans use Child (child-of relationship — the execution span is part of the same trace as the producer). Timer execution spans use FollowsFrom (the execution span starts a new trace with a span link back to the scheduling span, since timer execution is causally related but not part of the same operation).

Both strategies are configurable via the MessageSpans / PROSODY_MESSAGE_SPANS and TimerSpans / PROSODY_TIMER_SPANS options. Accepted values: child, follows_from.

Best Practices

Ensuring Thread-Safe Handlers

Your event handler methods will be called concurrently from multiple threads. NEVER use mutable shared state across event handler calls, like setting instance variables. Sharing state can introduce subtle data races and corruption that may only appear in production. If you must use shared state, use appropriate synchronization primitives like lock, SemaphoreSlim, or concurrent collections.

Ensuring Idempotent Message Handlers

Idempotent message handlers are crucial for maintaining data consistency, fault tolerance, and scalability when working with distributed, event-based systems. They ensure that processing a message multiple times has the same effect as processing it once, which is essential for recovering from failures.

Strategies for achieving idempotence:

1. Natural Idempotence: Use inherently idempotent operations (e.g., setting a value in a key-value store).

2. Deduplication with Unique Identifiers:

• Kafka messages can be uniquely identified by their partition and offset.
• Before processing, check if the message has been handled before.
• Store processed message identifiers with an appropriate TTL.

3. Database Upserts: Use upsert operations for database writes (e.g., MERGE in SQL Server or INSERT ... ON CONFLICT DO UPDATE in PostgreSQL via EF Core).

4. Partition Offset Tracking:

• Store the latest processed offset for each partition.
• Only process messages with higher offsets than the last processed one.
• Critically, store these offsets transactionally with other state updates to ensure consistency.

5. Idempotency Keys for External APIs: Utilize idempotency keys when supported by external APIs.

6. Check-then-Act Pattern:

• For non-idempotent external systems, verify if an operation was previously completed before execution.
• Maintain a record of completed operations, keyed by a unique message identifier.

7. Saga Pattern:

• Implement a state machine in your database for multi-step operations.
• Each message advances the state machine, allowing for idempotent processing and easy failure recovery.
• Particularly useful for complex, distributed transactions across multiple services.

Proper Shutdown

Always unsubscribe from topics before exiting your application:

// Ensure proper shutdown
await client.UnsubscribeAsync();

This ensures:

1. Completion and commitment of all in-flight work
2. Quick rebalancing, allowing other consumers to take over partitions
3. Proper release of resources

Implement shutdown handling in your application using IHostedService or IHostApplicationLifetime:

using Microsoft.Extensions.Hosting;
using Prosody;

public class ProsodyWorker : BackgroundService
{
    private readonly ProsodyClient _client;

    public ProsodyWorker()
    {
        _client = ProsodyClientBuilder.Create()
            .WithBootstrapServers("localhost:9092")
            .WithGroupId("my-consumer-group")
            .WithSubscribedTopics("my-topic")
            .Build();
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        await _client.SubscribeAsync(new MyHandler());

        // Wait for shutdown signal
        await Task.Delay(Timeout.Infinite, stoppingToken);
    }

    public override async Task StopAsync(CancellationToken cancellationToken)
    {
        Console.WriteLine("Shutting down gracefully...");
        await _client.UnsubscribeAsync();
        _client.Dispose();
        await base.StopAsync(cancellationToken);
    }
}

Error Handling

Prosody classifies errors as transient (temporary, can be retried) or permanent (won't be resolved by retrying). By default, all errors are considered transient.

Using Attributes

Use the [PermanentError] attribute to classify exceptions that should not be retried:

using Prosody;
using System.Text.Json;

public class MyHandler : IProsodyHandler<MyPayload>
{
    [PermanentError(typeof(JsonException), typeof(ArgumentException))]
    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        // Your message handling logic here
        // JsonException and ArgumentException will be treated as permanent
        // All other exceptions will be treated as transient (default behavior)
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken) => Task.CompletedTask;
}

Using PermanentException

You can also throw a PermanentException directly:

using Prosody;

public class MyHandler : IProsodyHandler<MyPayload>
{
    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        var payload = message.Payload;

        if (payload?.Version < MinimumSupportedVersion)
        {
            throw new PermanentException("Message version is no longer supported");
        }

        // Process message...
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken) => Task.CompletedTask;
}

Using IPermanentError Interface

For custom exception types, implement the IPermanentError marker interface:

using Prosody;

public class ValidationException : Exception, IPermanentError
{
    public ValidationException(string message) : base(message) { }
}

Best Practices for Error Handling

• Use permanent errors for issues like malformed data or business logic violations.
• Use transient errors for temporary issues like network problems.
• Be cautious with permanent errors as they prevent retries and can result in data loss.
• Consider system reliability and data consistency when classifying errors.

Handling Task Cancellation

Prosody cancels tasks during partition rebalancing or timeout. During shutdown, handlers run freely for most of the shutdown timeout before the cancellation signal fires — giving in-flight work time to complete. How you handle cancellation is critical:

• A handler that returns normally (no exception) is considered successful — Prosody treats the message as processed.
• Any exception — including OperationCanceledException — signals failure. Prosody does not distinguish cancellation from other errors; all exceptions are classified as transient (or permanent if marked).
• Never silently return on cancellation. If the handler returns without an exception, Prosody assumes the message was fully processed. Swallowing cancellation (e.g., if (cancellationToken.IsCancellationRequested) return;) tells Prosody the message succeeded when it didn't, which can cause data loss.

The correct pattern is to let OperationCanceledException propagate. When Prosody initiates the cancellation (rebalance, timeout, shutdown), it already knows the handler didn't complete — the transient error result simply confirms this. Prosody will not naively retry a message it just cancelled during shutdown; the retry behavior depends on the operating mode and the reason for cancellation.

The library provides a CancellationToken to your handler methods. Pass this token to any async operations that support it to ensure prompt cancellation.

Best practices:

1. Throw, don't swallow. Use ThrowIfCancellationRequested() or pass the token to async APIs that throw on cancellation. Never check IsCancellationRequested and silently return — this breaks the cancellation contract and causes Prosody to treat incomplete work as successful.
2. Exit promptly when cancelled to avoid rebalancing delays.
3. Use try/finally blocks for clean resource handling.
4. Pass the CancellationToken to all async operations that support it.

Example of using CancellationToken in message processing:

public class MyHandler : IProsodyHandler<MyPayload>
{
    private readonly HttpClient _httpClient;
    private readonly MyDbContext _dbContext;
    private readonly ProsodyClient _client;

    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<MyPayload> message, CancellationToken cancellationToken)
    {
        // Pass the token to HTTP calls — throws OperationCanceledException on cancellation
        var response = await _httpClient.GetAsync("https://api.example.com", cancellationToken);
        var data = await response.Content.ReadAsStringAsync(cancellationToken);

        // Pass the token to database operations
        await _dbContext.Messages.AddAsync(new MessageEntity { Payload = data }, cancellationToken);
        await _dbContext.SaveChangesAsync(cancellationToken);

        // Send a message, passing the cancellation token
        await _client.SendAsync("topic", "key", new { Data = "value" }, cancellationToken);
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken) => Task.CompletedTask;
}

For CPU-bound loops, poll ThrowIfCancellationRequested() periodically. This throws OperationCanceledException when cancellation is requested, correctly signaling to Prosody that the handler did not complete:

public class MyHandler : IProsodyHandler<List<Item>>
{
    public async Task OnMessageAsync(ProsodyContext prosodyContext, Message<List<Item>> message, CancellationToken cancellationToken)
    {
        foreach (var item in message.Payload ?? [])
        {
            // Correct: throws OperationCanceledException, signaling incomplete work
            cancellationToken.ThrowIfCancellationRequested();

            ProcessItem(item);
        }
    }

    public Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken) => Task.CompletedTask;
}

Anti-pattern — do not silently return on cancellation:

// WRONG: Prosody sees success and commits the offset, losing the unprocessed message
foreach (var item in items)
{
    if (cancellationToken.IsCancellationRequested)
        return; // Silent return = Prosody thinks the message was fully processed

    ProcessItem(item);
}

Failing to follow these practices can lead to:

• Data loss from incomplete work being marked as successful when cancellation is silently swallowed.
• Slower message processing due to delayed rebalancing.
• Resource leaks if long-running operations aren't properly cancelled.

Logging Configuration

Prosody provides flexible logging integration with your application.

Static Configuration

using Microsoft.Extensions.Logging;
using Prosody;
using Prosody.Logging;

// Configure logging globally for all Prosody clients (must be called once, before creating clients)
var loggerFactory = LoggerFactory.Create(builder => builder.AddConsole());
ProsodyLogging.Configure(loggerFactory);

To reset logging in test fixtures (e.g., during teardown so Configure can be called again):

ProsodyLogging.ResetForTesting();

Dependency Injection

For ASP.NET Core or Generic Host applications:

var builder = Host.CreateApplicationBuilder(args);

// Auto-configures Prosody logging with the host's ILoggerFactory
builder.Services.AddProsodyLogging();

var host = builder.Build();

Log messages are emitted under the Prosody.Native category.

Error Monitoring (Sentry)

Prosody automatically reports handler exceptions to Sentry when the host application has Sentry initialized. Prosody never calls SentrySdk.Init — it only enriches an already-initialized Sentry instance.

Setup

Initialize Sentry in your host application before subscribing to messages:

SentrySdk.Init(o =>
{
    o.Dsn = "https://examplePublicKey@o0.ingest.sentry.io/0";
    o.Environment = "production";
    o.Release = "my-app@1.2.3";
});

Or with ASP.NET Core / Generic Host:

builder.WebHost.UseSentry("https://examplePublicKey@o0.ingest.sentry.io/0");

If Sentry is not initialized, Prosody silently skips error reporting with zero overhead.

How It Works

Prosody checks SentrySdk.IsEnabled on each handler failure. If the host has Sentry initialized, Prosody captures the exception and enriches it with handler context. Prosody never owns the Sentry lifecycle — initialization and disposal remain entirely in the host application.

What Gets Reported

Both transient and permanent handler exceptions are captured with contextual data:

• prosody.event_type tag: "message" or "timer"
• prosody.error_class tag: "permanent" or "transient"
• prosody context:
  • For messages: topic, key, partition, offset
  • For timers: key, fire time

Safety Guarantee

Sentry failures never affect message processing. If Sentry is unreachable or misconfigured, the exception is logged and handler results are unchanged.

Note: The Sentry package is currently a hard dependency of ProsodyEvents.Prosody. A future improvement is to extract Sentry support into a separate ProsodyEvents.Prosody.Sentry package so consumers who don't use Sentry don't pull in the dependency.

Administrative Operations

⚠️ Important Note: Topic management in production environments should typically be handled through GitOps using Strimzi KafkaTopic manifests. The AdminClient is provided for testing scenarios and specific cases where manual topic creation and deletion is required.

AdminClient

The AdminClient provides administrative operations for Kafka topics:

using Prosody;

// Initialize admin client
using var admin = new AdminClient("localhost:9092");

// Create a topic for testing
await admin.CreateTopicAsync(
    name: "test-topic",
    partitionCount: 4,
    replicationFactor: 1
);

// Delete a topic
await admin.DeleteTopicAsync("test-topic");

Configuration Parameters

The AdminClient constructor accepts:

• bootstrapServers (params string[]): Kafka bootstrap servers (required)

Or via environment variable:

PROSODY_BOOTSTRAP_SERVERS=localhost:9092  # Single server
PROSODY_BOOTSTRAP_SERVERS=localhost:9092,localhost:9093  # Multiple servers

Release Process

Prosody uses an automated release process managed by GitHub Actions. Here's an overview of how releases are handled:

1. Trigger: The release process is triggered automatically on pushes to the main branch.

2. Release Please: The process starts with the "Release Please" action, which:

   • Analyzes commit messages since the last release.
   • Creates or updates a release pull request with changelog updates and version bumps.
   • When the PR is merged, it creates a GitHub release and a git tag.

3. Build Process: If a new release is created, the following native build jobs are triggered:

   • Linux builds for x86_64 and aarch64 architectures.
   • Windows builds for x64 and arm64 architectures.
   • macOS builds for arm64 (Apple Silicon) architecture.

4. Pack: A single NuGet package (ProsodyEvents.Prosody) is assembled from the native artifacts and the generated C# bindings, bundling all supported runtimes under runtimes/<rid>/native/ inside the .nupkg.

5. Test: The packed .nupkg is consumed by the test project (via TestPackage=true) and run against Kafka and Cassandra on each supported RID / target framework combination (.NET 8, 9, 10) before publication.

6. Publication: If all tests pass, the package is published to nuget.org.

Contributing to Releases

To contribute to a release:

1. Make your changes in a feature branch.
2. Use Conventional Commits syntax for your commit messages. This helps Release Please determine the next version number and generate the changelog.
3. Create a pull request to merge your changes into the main branch.
4. Once your PR is approved and merged, Release Please will include your changes in the next release PR.

Manual Releases

While the process is automated, manual intervention may sometimes be necessary:

• You can manually trigger the release workflow from the GitHub Actions tab if needed (including the release_as input to force a specific version, e.g. 2.2.0-beta.1).
• If you need to make changes to the release PR created by Release Please, you can do so before merging it.

All releases are automatically published to nuget.org. Ensure you have thoroughly tested your changes before merging to main.

API Reference

ProsodyClientBuilder

Fluent builder for configuring and creating a ProsodyClient. All With* methods return the builder for chaining.

• static ProsodyClientBuilder Create(): Creates a new builder instance.

Builder Methods:

• WithBootstrapServers(params string[] servers): Set Kafka bootstrap servers
• WithGroupId(string groupId): Set consumer group ID
• WithSubscribedTopics(params string[] topics): Set topics to subscribe to
• WithMode(ClientMode mode): Set client operating mode
• WithAllowedEvents(params string[] prefixes): Set event type prefixes to allow
• WithSourceSystem(string sourceSystem): Set source system identifier
• WithMock(bool mock): Enable/disable in-memory mock client
• WithMaxConcurrency(uint maxConcurrency): Set max concurrent messages
• WithMaxRetries(uint maxRetries): Set max retry attempts
• WithFailureTopic(string topic): Set dead letter topic
• WithProbePort(ushort port): Set health check probe port
• WithSendTimeout(TimeSpan timeout): Set max time to wait for message delivery
• Configure(Action<ClientOptions> configure): Set any option on ClientOptions directly
• ConfigureJsonOptions(Action<JsonSerializerOptions> configure): Override JSON serialization options (runs after defaults are applied)
• WithStateCollections(params StateDefinition[] definitions): Register keyed-state collections before subscribe

Build:

• ProsodyClient Build(): Validates configuration and creates a new ProsodyClient.

ProsodyClient

• ProsodyClient(ClientOptions options): Create a new ProsodyClient with the specified options.
• string SourceSystem { get; }: Get the source system identifier configured for the client.
• Task<ConsumerState> GetConsumerStateAsync(): Get the current state of the consumer.
• Task<uint> AssignedPartitionCountAsync(): Get the number of partitions currently assigned to this consumer.
• Task<bool> IsStalledAsync(): Check if the consumer has stalled partitions.
• Task<PublishedValue<T>> StateAsync<T>(string subsystem, ValueStateDefinition<T> definition, CancellationToken cancellationToken = default): Open a read-only published value.
• Task<PublishedMap<TValue>> StateAsync<TValue>(string subsystem, MapStateDefinition<TValue> definition, CancellationToken cancellationToken = default): Open a read-only published map.
• Task<PublishedDeque<T>> StateAsync<T>(string subsystem, DequeStateDefinition<T> definition, CancellationToken cancellationToken = default): Open a read-only published deque.
• Task SendAsync<T>(string topic, string key, T payload, CancellationToken cancellationToken = default): Send a message to a specified topic (uses configured JsonSerializerOptions; annotated with [RequiresUnreferencedCode]).
• Task SendAsync<T>(string topic, string key, T payload, JsonTypeInfo<T> typeInfo, CancellationToken cancellationToken = default): Trim-clean overload; serializes using the supplied JsonTypeInfo<T> instead of the client's options.
• Task SubscribeAsync<T>(IProsodyHandler<T> handler): Subscribe to messages using a strongly typed payload handler (annotated with [RequiresUnreferencedCode]).
• Task SubscribeAsync<T>(IProsodyHandler<T> handler, IPermanentErrorClassifier classifier): Trim-clean overload; bypasses [PermanentError] attribute reflection.
• Task UnsubscribeAsync(): Unsubscribe from messages and shut down the consumer.
• void Dispose(): Dispose of client resources synchronously.
• ValueTask DisposeAsync(): Dispose of client resources asynchronously (unsubscribes the consumer first). Enables await using.

AdminClient

• AdminClient(params string[] bootstrapServers): Initialize a new AdminClient with the given configuration.
• Task CreateTopicAsync(string name, ushort partitionCount, ushort replicationFactor): Create a Kafka topic.
• Task DeleteTopicAsync(string name): Delete an existing Kafka topic.
• void Dispose(): Dispose of admin client resources.

IProsodyHandler<TPayload>

Interface for handling messages and timers:

public interface IProsodyHandler<TPayload>
{
    Task OnMessageAsync(ProsodyContext prosodyContext, Message<TPayload> message, CancellationToken cancellationToken);
    Task OnTimerAsync(ProsodyContext prosodyContext, ProsodyTimer timer, CancellationToken cancellationToken);
}

Message<T>

Represents a Kafka message with the following properties:

• Topic (string): The name of the topic.
• Partition (int): The partition number.
• Offset (long): The message offset within the partition.
• Timestamp (DateTimeOffset): The timestamp when the message was created or sent.
• Key (string): The message key.
• T? Payload: The deserialized payload (deserialized once before the handler is invoked).

ProsodyContext

Represents the context of message processing:

• bool ShouldCancel { get; }: Check if cancellation has been requested (includes timeout and shutdown).
• Task OnCancelAsync(): Returns a task that completes when cancellation is signaled.

Keyed-state binding:

• State(definition): Binds a registered collection for the current attempt, returning IValueState<T> / IMapState<TValue> / IDequeState<T> (message definitions vend *State<Message<TPayload>>). Throws PermanentStateException for an unregistered name or a kind/payload identity mismatch. See the Keyed State API reference below.

Timer scheduling methods:

• Task ScheduleAsync(DateTimeOffset time): Schedules a timer to fire at the specified time
• Task ClearAndScheduleAsync(DateTimeOffset time): Clears all timers and schedules a new one
• Task UnscheduleAsync(DateTimeOffset time): Removes a timer scheduled for the specified time
• Task ClearScheduledAsync(): Removes all scheduled timers
• Task<DateTimeOffset[]> ScheduledAsync(): Returns an array of all scheduled timer times

ProsodyTimer

Represents a timer that has fired, provided to the OnTimerAsync method:

• Key (string): The entity key identifying what this timer belongs to
• Time (DateTimeOffset): The time when this timer was scheduled to fire

ConsumerState

Enum representing the consumer lifecycle state:

• Unconfigured: Consumer has not been configured
• Configured: Consumer is configured but not running
• Running: Consumer is actively processing messages

ClientMode

Enum representing the operating mode:

• Pipeline: Default mode, retry indefinitely with defer and monopolization detection
• LowLatency: Few retries then dead letter (requires FailureTopic)
• BestEffort: Log failures, no retries

Keyed State

Definition factories (each returns an immutable, validated record used both in WithStateCollections(...) and with context.State(...)):

• StateDefinition.Value<T>(string name, TimeSpan? ttl = null, bool? readUncommitted = null, bool published = false, StateReadCache? readCache = null) → ValueStateDefinition<T>
• StateDefinition.Map<TValue>(string name, TimeSpan? ttl = null, bool? readUncommitted = null, int? keysetLimit = null, bool published = false, StateReadCache? readCache = null) → MapStateDefinition<TValue>
• StateDefinition.Deque<T>(string name, TimeSpan? ttl = null, bool? readUncommitted = null, int? capacity = null, bool published = false, StateReadCache? readCache = null) → DequeStateDefinition<T>
• StateDefinition.MessageValue<TPayload>(string name, TimeSpan? ttl = null, bool? readUncommitted = null) → MessageValueDefinition<TPayload>
• StateDefinition.MessageMap<TPayload>(string name, TimeSpan? ttl = null, bool? readUncommitted = null, int? keysetLimit = null) → MessageMapDefinition<TPayload>
• StateDefinition.MessageDeque<TPayload>(string name, TimeSpan? ttl = null, bool? readUncommitted = null, int? capacity = null) → MessageDequeDefinition<TPayload>

The item type parameter (T / TValue) is constrained to notnull on the JSON collections, so a nullable item type is a compile-time error. Message collections leave the payload nullable — their item type is the non-null Message<TPayload>.

Published JSON collections use the same definition for owned and read-only access. See Published state for setup and examples. PublishedMap<TValue> provides GetAsync, batched GetManyAsync, ContainsKeyAsync, EnumerateAsync, and key-only EnumerateKeysAsync. PublishedDeque<T> provides GetAsync, CountAsync, IsEmptyAsync, PeekFrontAsync, PeekBackAsync, and EnumerateAsync.

IValueState<T> where T : notnull:

• Task<StateValue<T>> GetAsync(CancellationToken cancellationToken = default)
• Task SetAsync(T value, CancellationToken cancellationToken = default)
• Task ClearAsync(CancellationToken cancellationToken = default)
• Task CommitAsync(CancellationToken cancellationToken = default)
• Task RollbackAsync(CancellationToken cancellationToken = default)

IMapState<TValue> : IAsyncEnumerable<KeyValuePair<string, TValue>> (keys are string, TValue : notnull):

• Task<StateValue<TValue>> GetAsync(string key, CancellationToken cancellationToken = default)
• Task<IReadOnlyList<StateValue<TValue>>> GetManyAsync(IEnumerable<string> keys, CancellationToken cancellationToken = default)
• Task<bool> ContainsKeyAsync(string key, CancellationToken cancellationToken = default)
• Task SetAsync(string key, TValue value, CancellationToken cancellationToken = default)
• Task RemoveAsync(string key, CancellationToken cancellationToken = default)
• Task ClearAsync(CancellationToken cancellationToken = default)
• IAsyncEnumerable<KeyValuePair<string, TValue>> EnumerateAsync(ScanDirection direction = ScanDirection.Forward, CancellationToken cancellationToken = default)
• IAsyncEnumerable<string> EnumerateKeysAsync(ScanDirection direction = ScanDirection.Forward, CancellationToken cancellationToken = default)
• Task CommitAsync(CancellationToken cancellationToken = default)
• Task RollbackAsync(CancellationToken cancellationToken = default)

IDequeState<T> : IAsyncEnumerable<T> (T : notnull):

• Task PushBackAsync(T value, CancellationToken cancellationToken = default)
• Task PushFrontAsync(T value, CancellationToken cancellationToken = default)
• Task<StateValue<T>> PopFrontAsync(CancellationToken cancellationToken = default)
• Task<StateValue<T>> PopBackAsync(CancellationToken cancellationToken = default)
• Task<StateValue<T>> PeekFrontAsync(CancellationToken cancellationToken = default)
• Task<StateValue<T>> PeekBackAsync(CancellationToken cancellationToken = default)
• Task<StateValue<T>> GetAsync(int index, CancellationToken cancellationToken = default)
• Task<int> CountAsync(CancellationToken cancellationToken = default)
• Task<bool> IsEmptyAsync(CancellationToken cancellationToken = default)
• IAsyncEnumerable<T> EnumerateAsync(ScanDirection direction = ScanDirection.Forward, CancellationToken cancellationToken = default)
• Task CommitAsync(CancellationToken cancellationToken = default)
• Task RollbackAsync(CancellationToken cancellationToken = default)

StateValue<T> (a readonly struct optional read result, T : notnull):

• bool HasValue { get; }: whether a value is present.
• T Value { get; }: the stored value; throws InvalidOperationException when absent.
• T GetValueOrDefault(T defaultValue): the stored value when present, otherwise defaultValue (mirrors Nullable<T>).
• bool TryGetValue(out T value): the familiar Try pattern — true with the value when present, false otherwise.

ScanDirection: Forward (ascending) or Backward (descending).

Errors:

• StateException: abstract base; exposes StateErrorCategory Category { get; }.
• TransientStateException : StateException: the default for a temporary store failure or caller mistake. Examples include a null write or invalid index.
• NullValueException : TransientStateException: a rejected null/unrepresentable write; use ClearAsync / RemoveAsync to delete instead.
• PermanentStateException : StateException, IPermanentError: reserved for failures a retry cannot resolve in-process (unregistered/identity-mismatched collection, duplicate/invalid name or TTL), or one a handler throws explicitly.
• StateErrorCategory: Permanent or Transient.

License

MIT