Prosody: JavaScript Bindings for Kafka

Prosody offers JavaScript 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
• 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
• Backpressure: Pauses partitions when handlers fall behind
• Mocking: In-memory Kafka broker for tests (mock: true)
• Failure Handling: Pipeline (retry forever), Low-Latency (dead letter), Best-Effort (log and skip)

Installation

npm install @prosody-events/prosody

The package ships TypeScript declarations for the public API. EventHandler<P> carries an application payload type into Message<P>, and keyed-state definitions carry their item types through context.state(). Unparameterized handlers, messages, definitions, and state handles default to JsonValue. See the strict TypeScript examples for IDE-ready projects compiled by the repository typecheck.

Quick Start

const { ProsodyClient } = require("@prosody-events/prosody");

// Initialize the client with Kafka bootstrap servers, consumer group, and topics
const client = new ProsodyClient({
  // Bootstrap servers should normally be set using the PROSODY_BOOTSTRAP_SERVERS environment variable
  bootstrapServers: "localhost:9092",

  // To allow loopbacks, sourceSystem must be different from groupId.
  // Normally, sourceSystem is omitted and defaults to groupId.
  sourceSystem: "my-application-source",

  // groupId should be set to the name of your application
  groupId: "my-consumer-group",

  // Topics the client should subscribe to
  subscribedTopics: "my-topic",
});

// Define a message handler
const messageHandler = {
  onMessage: async (context, message, signal) => {
    // Process the received message
    console.log(`Received message: ${JSON.stringify(message)}`);

    // Schedule a timer for delayed processing
    if (message.payload.scheduleFollowup) {
      const followupTime = new Date(Date.now() + 30000); // 30 seconds from now
      await context.schedule(followupTime);
    }
  },

  onTimer: async (context, timer, signal) => {
    // Handle timer firing
    console.log(`Timer fired for key: ${timer.key} at ${timer.time}`);
  },
};

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

// Send a message to a topic
await client.send("my-topic", "message-key", { content: "Hello, Kafka!" });

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

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
const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  deferEnabled: true, // Enable deferral (default: true)
  deferBaseMs: 1000, // Wait 1s before first retry
  deferMaxDelayMs: 86400000, // Cap at 24 hours
  deferFailureThreshold: 0.9, // Disable when >90% failing
});

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
const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  monopolizationEnabled: true, // Enable detection (default: true)
  monopolizationThreshold: 0.9, // Reject keys using >90% of window
  monopolizationWindowMs: 300000, // 5-minute window
});

Handler Timeout

Handlers are automatically cancelled if they exceed a deadline:

const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  timeoutMs: 30000, // Cancel after 30 seconds
  stallThresholdMs: 60000, // Report unhealthy after 60 seconds
});

When a handler times out, context.shouldCancel becomes true and context.onCancel() resolves. The handler should exit promptly. If not specified, timeout defaults to 80% of stallThresholdMs.

Configuration

For the complete configuration reference, see CONFIGURATION.md.

Constructor options take precedence. Unset options 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 either the client constructor:

const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  probePort: 8000, // Set to null to disable
  stallThresholdMs: 15000, // 15 seconds before considering a partition stalled
});

Or via environment variables:

PROSODY_PROBE_PORT=8000  # Set to 'none' 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 properties:

// Get the number of partitions currently assigned to this consumer
const partitionCount = client.assignedPartitionCount;

// You can use these in your own health checks or monitoring
if (client.isStalled) {
  console.warn("Consumer has stalled partitions");
}

Advanced Usage

Pipeline Mode

All messages must be processed. Retries indefinitely. Uses defer and monopolization detection.

Middleware stack:

Kafka → Deduplication → Retry → Defer → Monopolization → Shutdown → Scheduler → Timeout → Telemetry → Handler

Layer	Purpose
Deduplication	Skips messages whose ID was already processed
Retry	Retries transient errors indefinitely
Defer	Stores failing messages for timer-based retry
Monopolization	Rejects keys exceeding execution time threshold
Shutdown	Drains in-flight work on partition revocation
Scheduler	Enforces concurrency limits and VT-based priority
Timeout	Cancels handlers exceeding deadline
Telemetry	Emits handler lifecycle events

const client = new ProsodyClient({
  mode: Mode.Pipeline, // Default mode
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
});

Low-Latency Mode

Tries a few times, then routes failures to a dead letter topic.

• Retries up to maxRetries times, then writes to failure topic
• Fair scheduling limits how much time retries consume
• Use when you need to keep moving and can reprocess failures later

const client = new ProsodyClient({
  mode: Mode.LowLatency,
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  failureTopic: "failed-messages", // Required for low-latency mode
  maxRetries: 3, // Retry up to 3 times after the initial attempt
});

Best-Effort Mode

Logs failures and moves on.

• No retries; failed messages are logged and committed
• Fair scheduling still enforces concurrency limits
• Use for development or when message loss is acceptable

const client = new ProsodyClient({
  mode: Mode.BestEffort,
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
});

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."
const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  allowedEvents: ["user.", "account."],
});

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
const client = new ProsodyClient({
  groupId: "my-service",
  sourceSystem: "my-service-producer", // Must differ from groupId to allow loopbacks; defaults to groupId
  subscribedTopics: "my-topic",
});

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.

Deduplication uses a two-tier approach:

• Global in-memory cache: A single cache shared across all partitions within the same consumer instance. Survives partition reassignments within the same process. Controlled by idempotenceCacheSize (default 8192).
• Cassandra-backed persistent store: Survives restarts and rebalances across instances. TTL controlled by idempotenceTtlS (default 7 days, i.e. 604800s).

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 constructed.

// Messages with IDs are deduplicated per key
await client.send("my-topic", "key1", {
  id: "msg-123", // Message will be processed
  content: "Hello!",
});

await client.send("my-topic", "key1", {
  id: "msg-123", // Message will be skipped (duplicate)
  content: "Hello again!",
});

await client.send("my-topic", "key2", {
  id: "msg-123", // Message will be processed (different key)
  content: "Hello!",
});

To invalidate all previously recorded dedup entries (forcing reprocessing of messages), change the version:

const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
  idempotenceVersion: "2", // Changing this invalidates all previously recorded entries
});

Or via environment variable:

PROSODY_IDEMPOTENCE_VERSION=2

Timer Functionality

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

const messageHandler = {
  onMessage: async (context, message, signal) => {
    // Schedule a timer to fire in 30 seconds
    const futureTime = new Date(Date.now() + 30000);
    await context.schedule(futureTime);

    // Schedule multiple timers
    const oneMinute = new Date(Date.now() + 60000);
    const twoMinutes = new Date(Date.now() + 120000);
    await context.schedule(oneMinute);
    await context.schedule(twoMinutes);

    // Check what's scheduled
    const scheduled = await context.scheduled();
    console.log(`Scheduled timers: ${scheduled.length}`);
  },

  onTimer: async (context, timer, signal) => {
    console.log("Timer fired!");
    console.log(`Key: ${timer.key}`);
    console.log(`Scheduled time: ${timer.time}`);
  },
};

Timer Methods

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

• schedule(time): Schedules a timer to fire at the specified time
• clearAndSchedule(time): Clears all timers and schedules a new one
• unschedule(time): Removes a timer scheduled for the specified time
• clearScheduled(): Removes all scheduled timers
• scheduled(): Returns an array of all scheduled timer times

Timer Object

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

• key (string): The entity key identifying what this timer belongs to
• time (Date): 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:

const client = new ProsodyClient({
  bootstrapServers: "localhost:9092",
  groupId: "my-application",
  subscribedTopics: "my-topic",
  cassandraNodes: "localhost:9042", // Required unless mock: true
});

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

// Mock mode for testing (timers work but aren't persisted)
const client = new ProsodyClient({
  bootstrapServers: "localhost:9092",
  groupId: "my-application",
  subscribedTopics: "my-topic",
  mock: true, // No Cassandra required in mock mode
});

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 Decorators

If you're using TypeScript or a JavaScript environment that supports decorators, you can use the @permanent decorator to classify exceptions that should not be retried:

import { permanent, ProsodyClient } from "@prosody-events/prosody";

class MyHandler {
  @permanent(TypeError, AttributeError)
  async onMessage(context, message, signal) {
    // Your message handling logic here
    // TypeError and AttributeError will be treated as permanent
    // All other exceptions will be treated as transient (default behavior)
  }
}

const client = new ProsodyClient(config);
client.subscribe(new MyHandler());

Without Decorators

If you're not using decorators, you can still classify errors as permanent by throwing a PermanentError:

import { PermanentError, ProsodyClient } from "@prosody-events/prosody";

const messageHandler = {
  onMessage: async (context, message, signal) => {
    try {
      // Your message handling logic here
    } catch (error) {
      if (error instanceof TypeError || error instanceof AttributeError) {
        throw new PermanentError(error.message);
      }
      // All other exceptions will be treated as transient (default behavior)
      throw error;
    }
  },
};

const client = new ProsodyClient(config);
client.subscribe(messageHandler);

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.

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:

const CURRENT_ORDER = value("current-order", { published: true });
const owner = new ProsodyClient({
  ...config,
  subsystem: "checkout",
  stateCollections: [CURRENT_ORDER],
});

// Inside the owner's handler, the event supplies the user key.
const currentOrder = context.state(CURRENT_ORDER);
await currentOrder.set({ sku: "book" });

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:

const orderReader = await client.state("checkout", CURRENT_ORDER);
const currentOrder = await orderReader.get("customer-123");

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 iteration is asynchronous and reads in chunks rather than loading the entire collection.

The default cache window is five seconds unless the client configuration changes it. Set readCache: { ttlMs } on a definition to choose a different freshness window, or readCache: false 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:

const COUNT = value<number>("count", { ttlSeconds: 30 * 24 * 60 * 60 });

const client = new ProsodyClient({
  ...config,
  stateCollections: [COUNT],
});

client.subscribe({
  async onMessage(context) {
    const count = context.state(COUNT);
    await count.set(((await count.get()) ?? 0) + 1);
  },
});

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.

const WINDOW = value<boolean>("window", { ttlSeconds: 24 * 60 * 60 });
const PENDING = messageDeque<Activity>("pending", {
  capacity: 100,
  ttlSeconds: 24 * 60 * 60,
});

const handler = {
  async onMessage(context, message) {
    const window = context.state(WINDOW);
    const pending = context.state(PENDING);

    if (await window.get()) {
      await pending.push(message);
      return;
    }

    await notify(message.key, [message]);
    await window.set(true);
    await context.clearAndSchedule(new Date(Date.now() + 5 * 60_000));
  },

  async onTimer(context, timer) {
    const pending = context.state(PENDING);
    const batch: Message<Activity>[] = [];
    for await (const message of pending.values()) batch.push(message);

    if (batch.length > 0) await notify(timer.key, batch);
    await pending.clear();
    await context.state(WINDOW).clear();
  },
} satisfies EventHandler<Activity>;

See the complete, type-checked example for imports, types, client setup, and notify: examples/windowing.ts.

Why this works:

• Register both definitions in stateCollections before subscribing. Keyed state uses Cassandra unless mock: true.
• Use clearAndSchedule, not schedule, 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, 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	value<T>	messageValue<P>	get, set, clear
Ordered string map	map<V>	messageMap<P>	get, getMany, has, set, delete, entries, keys, clear
Deque	deque<T>	messageDeque<P>	push, unshift, pop, shift, at, length, values, clear

All operations are async. Map and deque scans are async iterables; a for await loop may stop early safely. Map keys are strings. null and undefined mean absence and cannot be stored—use clear() or delete() instead.

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.
• commit() immediately publishes this collection's pending changes. They remain visible even if the handler later throws and the event is retried.
• rollback() discards this collection's pending changes since its last commit(). It cannot undo changes that were already committed.

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 JavaScript.

Required Packages

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

npm install @opentelemetry/api @opentelemetry/sdk-node @opentelemetry/exporter-trace-otlp-http

Initializing Tracing

To initialize tracing in your application:

const opentelemetry = require("@opentelemetry/api");
const { NodeSDK } = require("@opentelemetry/sdk-node");
const {
  OTLPTraceExporter,
} = require("@opentelemetry/exporter-trace-otlp-http");

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter(),
  serviceName: "my-service-name",
});

sdk.start();

// Creates a tracer from the global tracer provider
const tracer = opentelemetry.trace.getTracer("my-service-name");

Setting OpenTelemetry Environment Variables

Set the following standard OpenTelemetry environment variables:

OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
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:

const { ProsodyClient } = require("@prosody-events/prosody");
const opentelemetry = require("@opentelemetry/api");

const tracer = opentelemetry.trace.getTracer("my-service-name");

const client = new ProsodyClient({
  groupId: "my-consumer-group",
  subscribedTopics: "my-topic",
});

const messageHandler = {
  onMessage: async (context, message, signal) => {
    const span = tracer.startSpan("process-message");
    try {
      // Process the received message
      span.addEvent("message.received", {
        "message.payload": JSON.stringify(message),
      });
    } finally {
      span.end();
    }
  },
};

client.subscribe(messageHandler);

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 follows_from (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 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.

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.unsubscribe();

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:

const { ProsodyClient } = require("@prosody-events/prosody");

async function main() {
  const client = new ProsodyClient({
    groupId: "my-consumer-group",
    subscribedTopics: "my-topic",
  });

  const messageHandler = {
    onMessage: async (context, message, signal) => {
      // Process the message
    },
  };

  client.subscribe(messageHandler);

  // Create a promise that resolves when shutdown is signaled
  const shutdownPromise = new Promise((resolve) => {
    const shutdown = async (signal) => {
      console.log(`Received ${signal}. Initiating shutdown...`);
      await client.unsubscribe();
      resolve();
    };

    process.on("SIGTERM", () => shutdown("SIGTERM"));
    process.on("SIGINT", () => shutdown("SIGINT"));
    process.on("SIGHUP", () => shutdown("SIGHUP"));
  });

  // Wait for shutdown to be signaled
  await shutdownPromise;
}

main().catch(console.error);

Handling Task Cancellation

Prosody cancels tasks during partition rebalancing or shutdown. How you handle cancellation is critical:

• Prosody interprets task success based on exception propagation.
• A task that exits without an exception is considered successful.
• Any exception signals task failure.

The library uses AbortSignals in both the send method and onMessage handler. It's crucial to pass this abort signal to any I/O operations, fetch calls, or database queries to ensure prompt task cancellation.

Best practices:

1. Exit promptly when cancelled to avoid rebalancing delays.
2. Use try/catch blocks to handle cancellation gracefully.
3. Use try/finally or equivalent constructs for clean resource handling.
4. Pass the AbortSignal to all async operations that support it.

Example of using AbortSignal in message processing:

const messageHandler = {
  onMessage: async (context, message, signal) => {
    // Pass the signal to fetch calls
    const response = await fetch("https://api.example.com", { signal });
    const data = await response.json();

    // Pass the signal to database operations
    await db.query(
      "INSERT INTO messages (payload) VALUES ($1)",
      [message.payload],
      { signal },
    );

    // Process the data...

    // Send a message, passing the abort signal
    await client.send("topic", "key", { data: "value" }, signal);
  },
};

For the send method, note that while an abort signal will cause the method to return early, it may not cancel the message being sent, depending on when the abort is signaled. If the abort occurs after the message has been handed off to the Kafka client, the message may still be sent.

Failing to follow these practices can lead to:

• Slower message processing due to delayed rebalancing.
• Data loss from missed messages when cancellation errors are suppressed.
• Resource leaks if long-running operations aren't properly cancelled.

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 build jobs are triggered:

   • Linux builds for x86_64 and aarch64 (glibc).
   • Windows build for x64.
   • macOS build for aarch64 (Apple Silicon).

4. Testing: The built binaries are tested on Linux (x86_64 and aarch64) with Node.js 20 and 22.

5. Artifact Upload: Each build job uploads its artifacts (Node.js native addons) to GitHub Actions.

6. Publication: If all builds and tests are successful, the final step publishes the package to the npm registry.

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.
• If you need to make changes to the release PR created by Release Please, you can do so before merging it.

Remember, all releases are automatically published to the npm registry. Ensure you have thoroughly tested your changes before merging to main.

API Reference

ProsodyClient

• constructor(config: Configuration): Initialize a new ProsodyClient with the given configuration.
• send<P>(topic: string, key: string, payload: P & JsonCompatible<P>, signal?: AbortSignal): Promise<void>: Send a statically checked JSON-compatible message to a specified topic.
• consumerState: ConsumerState: Get the current state of the consumer.
• sourceSystem: string: Get the source system identifier configured for the client.
• state<T>(subsystem: string, definition: ValueDefinition<T>): Promise<PublishedValue<T>>: Open a read-only published value.
• state<V>(subsystem: string, definition: MapDefinition<V>): Promise<PublishedMap<V>>: Open a read-only published map.
• state<T>(subsystem: string, definition: DequeDefinition<T>): Promise<PublishedDeque<T>>: Open a read-only published deque.
• subscribe<P = JsonValue>(eventHandler: EventHandler<P>): Promise<void>: Subscribe using a handler whose payload type flows into Message<P>.
• unsubscribe(): Promise<void>: Unsubscribe from messages and shut down the consumer.

EventHandler

Interface for handling messages and timers:

• EventHandler<P = JsonValue> carries the application payload type through to the message callback.
• onMessage?: (context: Context, message: Message<P>, signal: AbortSignal) => Promise<void>: Handles incoming messages
• onTimer?: (context: Context, timer: Timer, signal: AbortSignal) => Promise<void>: Handles timer events

Message

Represents a Kafka message with the following properties:

• topic: string: The name of the topic.
• partition: number: The partition number.
• offset: bigint: The message offset within the partition.
• timestamp: Date: The timestamp when the message was created or sent.
• key: string: The message key.
• payload: P: The statically typed message payload.

Message takes an optional payload type parameter, Message<P>, used by handlers and message-backed state collections to type payload. Unparameterized Message is Message<JsonValue>, preserving useful JSON safety without requiring an application-specific payload type.

JsonValue describes arbitrary JSON data. JsonCompatible<T> checks a known application type recursively, so ordinary interfaces work with send() while functions, undefined, Date, symbols, bigints, and invalid nested fields are reported by TypeScript before the message reaches the serializer.

Context

Represents the context of message processing:

• onCancel(): Promise<void>: A method that resolves when the context is cancelled.
• shouldCancel: boolean: A property indicating whether the context has been cancelled.

Timer scheduling methods:

• schedule(time: Date): Promise<void>: Schedules a timer to fire at the specified time
• clearAndSchedule(time: Date): Promise<void>: Clears all timers and schedules a new one
• unschedule(time: Date): Promise<void>: Removes a timer scheduled for the specified time
• clearScheduled(): Promise<void>: Removes all scheduled timers
• scheduled(): Promise<Date[]>: Returns an array of all scheduled timer times

Keyed-state binding:

• state(definition): ValueState<T> | MapState<V> | DequeState<T>: Binds a registered collection for the current event attempt, returning a typed handle (message definitions vend *State<Message<P>>). Throws PermanentStateError when the name was never registered, or when the definition's kind/payload disagrees with the collection's durably-registered schema. See the Keyed State API reference below.

Timer

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

• key: string: The entity key identifying what this timer belongs to
• time: Date: The time when this timer was scheduled to fire

Keyed State

Definition constructors (each returns a frozen definition object used both in Configuration.stateCollections and with context.state()):

• value<T = JsonValue>(name: string, options?: PublishedStateDefinitionOptions): ValueDefinition<T>
• map<V = JsonValue>(name: string, options?: MapDefinitionOptions): MapDefinition<V>
• deque<T = JsonValue>(name: string, options?: DequeDefinitionOptions): DequeDefinition<T>
• messageValue<P = JsonValue>(name: string, options?: StateDefinitionOptions): MessageValueDefinition<P>
• messageMap<P = JsonValue>(name: string, options?: MessageMapDefinitionOptions): MessageMapDefinition<P>
• messageDeque<P = JsonValue>(name: string, options?: MessageDequeDefinitionOptions): MessageDequeDefinition<P>

StateDefinitionOptions: { ttlSeconds?: number; readUncommitted?: boolean }. PublishedStateDefinitionOptions adds { published?: boolean; readCache?: { ttlMs: number } | false } for JSON definitions. Map and deque option types add keysetLimit and capacity, respectively; their message equivalents omit publication options.

ValueState<T>:

• get(): Promise<T | null>
• set(value: T): Promise<void>
• clear(): Promise<void>
• commit(): Promise<void>
• rollback(): Promise<void>

MapState<V> (keys are string):

• get(key: string): Promise<V | null>
• getMany(keys: readonly string[]): Promise<(V | null)[]>
• has(key: string): Promise<boolean>
• set(key: string, value: V): Promise<void>
• delete(key: string): Promise<void>
• clear(): Promise<void>
• entries(direction?: ScanDirection): AsyncIterableIterator<[string, V]>
• keys(direction?: ScanDirection): AsyncIterableIterator<string>
• values(direction?: ScanDirection): AsyncIterableIterator<V>
• [Symbol.asyncIterator](): AsyncIterableIterator<[string, V]>
• commit(): Promise<void>
• rollback(): Promise<void>

DequeState<T>:

• push(item: T): Promise<void>
• unshift(item: T): Promise<void>
• pop(): Promise<T | null>
• shift(): Promise<T | null>
• length(): Promise<number>
• isEmpty(): Promise<boolean>
• clear(): Promise<void>
• at(index: number): Promise<T | null>
• values(direction?: ScanDirection): AsyncIterableIterator<T>
• [Symbol.asyncIterator](): AsyncIterableIterator<T>
• commit(): Promise<void>
• rollback(): Promise<void>

ScanDirection: "forward" | "backward".

Published readers take the user key as their first argument. PublishedValue<T> provides get. PublishedMap<V> provides get, getMany, has, entries, keys, and values. PublishedDeque<T> provides at, length, isEmpty, and values. The scan methods return AsyncIterableIterator directly.

StateCollectionConfig (a stateCollections entry): { name: string; kind: "value" | "map" | "deque"; payload: "json" | "message"; ttlSeconds?: number; readUncommitted?: boolean; published?: boolean; readCache?: { ttlMs: number } | false; keysetLimit?: number; capacity?: number }. Publication and readCache are supported for JSON collections. The definition constructors produce objects assignable to this shape, so prefer them.

Errors:

• TransientStateError extends TransientError: the default — a temporary store read/write failure, or any caller mistake (a null/unrepresentable write, item-shape mismatch, non-integer deque index, invalid scan direction), rejected transient so it retries rather than discarding the message.
• PermanentStateError extends PermanentError: reserved for failures a retry cannot resolve in-process (unregistered/identity-mismatched collection, duplicate registration), or one a handler throws explicitly.
• isStateError(error: unknown): error is PermanentStateError | TransientStateError: type-guard narrowing an error to either state error class.

License

This project is licensed under the MIT License - see the LICENSE file for details.