Prosody: Ruby Bindings for Kafka

Prosody offers Ruby 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 value/map/deque collections that survive across events, transactional by default
  • 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

Add this line to your application's Gemfile:

gem "prosody"

Or install directly:

gem install prosody

The gem ships RBS signatures for the public API. Prosody::EventHandler[Payload, Response] carries the payload type into Prosody::Message[Payload]. It also checks each handler response. State definitions carry their item types through context.state. A bare handler, message, definition, or state handle uses Prosody::json_value. See the typed examples for Ruby and companion RBS files checked by Steep.

Quick Start

require "prosody"

# Initialize the client with Kafka bootstrap server, consumer group, and topics
client = Prosody::Client.new(
  # Bootstrap servers should normally be set using the PROSODY_BOOTSTRAP_SERVERS environment variable
  bootstrap_servers: "localhost:9092",

  # To allow loopbacks, the source_system must be different from the group_id.
  # Normally, the source_system would be left unspecified, which would default to the group_id.
  source_system: "my-application-source",

  # The group_id should be set to the name of your application
  group_id: "my-application",

  # Topics the client should subscribe to
  subscribed_topics: "my-topic"
)

# Define a custom message handler
class MyHandler < Prosody::EventHandler
  def on_excise(context, message)
    puts "Excise key: #{message.key}"
    context.clear_scheduled
    nil
  end

  def on_message(context, message)
    # Process the received message
    puts "Received message: #{message.payload.inspect}"

    # Schedule a timer for delayed processing (requires Cassandra unless mock: true)
    if message.payload["schedule_followup"]
      future_time = Time.now + 30 # 30 seconds from now
      context.schedule(future_time)
    end
  end

  def on_timer(context, timer)
    # Handle timer firing
    puts "Timer fired for key: #{timer.key} at #{timer.time}"
  end
end

# Subscribe to messages using the custom handler
client.subscribe(MyHandler.new)

# Send a message to a topic
client.send_message("my-topic", "message-key", {"content" => "Hello, Kafka!"})
client.excise("my-topic", "obsolete-key")

# Ensure proper shutdown when done
client.shutdown

Excise records

Applications can copy event data into keyed state and external stores. A regulatory or contractual deletion must remove every copy for one key.

An excise record carries this deletion command. Kafka encodes the command as a key with no payload. During topic compaction, Kafka deletes earlier values for the key. Call excise(topic, key) to send the record. Prosody routes the record to on_excise. The handler must delete all consumer-owned data for the key.

Each handler must implement on_message, on_excise, and on_timer. Subscription fails before consumption if a method is missing.

If an excise record is a request, return a response from on_excise. Prosody uses this response as the subsystem result.

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
client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  defer_enabled: true,           # Enable deferral (default: true)
  defer_base: 1.0,               # Wait 1s before first retry
  defer_max_delay: 86400.0,      # Cap at 24 hours
  defer_failure_threshold: 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
client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  monopolization_enabled: true,     # Enable detection (default: true)
  monopolization_threshold: 0.9,    # Reject keys using >90% of window
  monopolization_window: 300.0      # 5-minute window
)

Handler Timeout

Handlers are automatically cancelled if they exceed a deadline:

client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  timeout: 30.0,             # Cancel after 30 seconds
  stall_threshold: 60.0      # Report unhealthy after 60 seconds
)

When a handler times out, context.should_cancel? returns true. The handler should exit promptly. If not specified, timeout defaults to 80% of stall_threshold.

Configuration

For the complete configuration reference, see CONFIGURATION.md.

Constructor options take precedence. Unset options use environment variables, then library defaults.

Logging

Prosody exposes a module-level logger used by both the native Rust extension and the Ruby async processor. By default it writes to $stdout at the INFO level.

# Read the current logger
Prosody.logger
# => #<Logger:... @level=1 ...>

# Assign a custom logger
Prosody.logger = Logger.new("log/prosody.log", level: Logger::DEBUG)

# Or silence logging entirely
Prosody.logger = Logger.new(File::NULL)

Set Prosody.logger before creating a Prosody::Client. The Rust runtime reads the logger on first client initialization and will use whatever logger is configured at that point.

Setting the logger back to nil restores the default:

Prosody.logger = nil
Prosody.logger.level  # => Logger::INFO

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:

client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  probe_port: 8000,        # Set to false to disable
  stall_threshold: 15.0    # 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 stall_threshold 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).

[!NOTE] Rails users: Because prosody-rb is built on the async gem, handlers run on fibers rather than threads. Rails defaults ActiveSupport's isolation level to :thread, which causes ActiveRecord connections to be shared across fibers and produces errors like:

ActiveRecord::StatementInvalid: Mysql2::Error: This connection is in use by: #<Fiber

Set the isolation level to :fiber in config/application.rb:

config.active_support.isolation_level = :fiber

Client Stall State

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

# Get the number of partitions currently assigned to this consumer
partition_count = client.assigned_partitions

# Check if the consumer has stalled partitions
if client.is_stalled?
  warn 'Consumer has stalled partitions'
end

Subsystems

A consumer group ID identifies a set of processes that share records and the keyed state that the group owns. A subsystem can include one or more services and consumer groups. If callers use these IDs, a refactor can require changes to each caller.

A subsystem gives requests and published state one stable public name. Callers use this name instead of consumer group IDs. You can change its services and consumer groups without changing callers. Prosody uses the first response to a subsystem request. For each published-state read, it uses one consumer group that publishes the collection.

Requests

Kafka decouples producers from consumers, so a send does not return consumer results. This asynchronous model lets each service process records independently. Some operations must wait for consumer results before they continue. A request recovers synchrony for the caller while consumers continue asynchronous processing.

Send a request from a handler or other application code. The Prosody client does not need an active subscription. The result hash uses canonical subsystem names as keys. Each value is a Success or Failure outcome. Use request_excise to send an excise record and collect the same outcome type.

Do not rely on hash order. The hash contains one entry for each selected subsystem. A missing response becomes a timeout Failure; Prosody does not omit the subsystem. The request raises an error for request-level failures, such as invalid input, a Kafka send failure, or shutdown. Do not wait for a request if the current consumer group must process it for the same key. That group cannot process it until the handler returns.

Message and excise handler return values become successful outcomes. Each return value must have a JSON representation.

Set subsystem to inventory on the client that subscribes this handler.

class InventoryHandler < Prosody::EventHandler
  def on_message(_context, message)
    {"accepted" => message.key}
  end

  def on_excise(_context, message)
    {"excised" => message.key}
  end

  def on_timer(_context, _timer)
  end
end

Send the request:

Set timeout in seconds.

subsystems = ["inventory", "billing"]
results = client.request(
  topic: "orders",
  key: "order-1",
  payload: {"type" => "order.created"},
  subsystems: subsystems,
  timeout: 2.0
)

results.each do |subsystem, outcome|
  if outcome.is_a?(Prosody::Failure)
    warn "#{subsystem}: #{outcome.error.message}"
  else
    puts "#{subsystem}: #{outcome.value}"
  end
end

The example can print these results:

inventory: {"accepted"=>"order-1"}
billing: no response arrived before the deadline

Each failure contains one typed response error.

Each response error has one message.

Advanced Usage

Pipeline Mode

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

# Initialize client in pipeline mode
client = Prosody::Client.new(
  mode: :pipeline,  # Explicitly set pipeline mode (this is the default)
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic"
)

Low-Latency Mode

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

# Initialize client in low-latency mode
client = Prosody::Client.new(
  mode: :low_latency,  # Set low-latency mode
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  failure_topic: "failed-messages"  # Specify a topic for failed messages
)

Best-Effort Mode

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

# Initialize client in best-effort mode
client = Prosody::Client.new(
  mode: :best_effort,  # Set best-effort mode
  group_id: "my-consumer-group",
  subscribed_topics: "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."
client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  allowed_events: ["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
client = Prosody::Client.new(
  group_id: "my-service",
  source_system: "my-service-producer",  # Must differ from group_id to allow loopbacks; defaults to group_id
  subscribed_topics: "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.

The deduplication system uses:

  • A global in-memory cache shared across all partitions, surviving partition reassignments within a process
  • A Cassandra-backed persistent store for cross-restart deduplication
# Messages with IDs are deduplicated per key
client.send_message("my-topic", "key1", {
  "id" => "msg-123",      # Message will be processed
  "content" => "Hello!"
})

client.send_message("my-topic", "key1", {
  "id" => "msg-123",      # Message will be skipped (duplicate)
  "content" => "Hello again!"
})

client.send_message("my-topic", "key2", {
  "id" => "msg-123",      # Message will be processed (different key)
  "content" => "Hello!"
})

Consumer deduplication is mandatory — it is the commit oracle that makes keyed state correct — so it cannot be disabled. idempotence_cache_size must be at least 1; setting it to 0 in the client configuration raises an ArgumentError:

client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  idempotence_cache_size: 0  # Rejected: consumer deduplication cannot be disabled
)

This applies to every client — Prosody::Client.new always builds a consumer, so 0 is rejected regardless of whether any topics are subscribed, and whether it is supplied in the client configuration or via PROSODY_IDEMPOTENCE_CACHE_SIZE.

To invalidate all previously recorded dedup entries (e.g. after a data migration), change the version string:

client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  idempotence_version: "2"  # Changing this invalidates all existing dedup records
)

The idempotence_ttl option controls how long dedup records are retained in Cassandra (default: 7 days):

client = Prosody::Client.new(
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic",
  idempotence_ttl: 86400.0  # Keep dedup records for 1 day
)

Note that the in-memory cache is best-effort. Duplicates can still occur across different process instances.

Keyed State

Many stream transformations must reason across multiple events or timer firings. Windows, state machines, aggregates, and complex event processing all require state.

A Kafka key identifies an entity, such as a customer or order. Keyed state gives each key independent working state for these transformations. With Cassandra, the state survives restarts and partition reassignment.

Prosody selects the current message or timer key. It processes one event at a time for that key but can process other keys concurrently. By default, Prosody commits pending keyed-state changes only when the handler succeeds. If the handler returns an error, Prosody discards those changes.

Give most collections a time to live (TTL). Set the TTL beyond the longest timer or workflow that uses the collection. Omit it when state must remain for inactive keys.

A counter for each key

Declare each collection once. Register it on the client. In a handler, get the current key's state from the event context:

COUNTER = Prosody.value("counter", ttl: 30 * 24 * 60 * 60)

class CountHandler < Prosody::EventHandler
  def on_message(context, _message)
    count = context.state(COUNTER)
    count.set((count.get || 0) + 1)
  end

  def on_excise(context, _message)
    context.state(COUNTER).clear
    nil
  end
  def on_timer(_context, _timer); end
end

client = Prosody::Client.new(
  group_id: "counters",
  subscribed_topics: "events",
  state_collections: [COUNTER]
)

Each Kafka key now has an independent counter. A counter expires when that key has no update for 30 days.

Window activity into one notification

This example sends the first event for a user immediately. It collects later events for five minutes and then sends one summary.

The user ID is the Kafka key. Each user has an independent window.

WINDOW = Prosody.value("window", ttl: 24 * 60 * 60)
PENDING = Prosody.message_deque("pending", capacity: 100, ttl: 24 * 60 * 60)

class ActivityHandler < Prosody::EventHandler
  def on_message(context, message)
    window = context.state(WINDOW)
    pending = context.state(PENDING)

    if window.get
      pending.push(message)
      return
    end

    notify(message.key, [message])
    window.set(true)
    context.clear_and_schedule(Time.now + 5 * 60)
  end

  def on_timer(context, timer)
    pending = context.state(PENDING)
    batch = []
    pending.each { |message| batch << message }

    notify(timer.key, batch) unless batch.empty?
    pending.clear
    context.state(WINDOW).clear
  end

  def on_excise(context, _message)
    context.state(PENDING).clear
    context.state(WINDOW).clear
    context.clear_scheduled
    nil
  end
end

See the complete, Steep-checked example for signatures, client setup, and notify: examples/keyed_state_windowing.rb and examples/keyed_state_windowing.rbs.

Why this works:

  • Register both definitions in state_collections before you subscribe. Keyed state uses Cassandra unless mock: true.
  • Use clear_and_schedule, not schedule, so a retried event does not add another timer for the same key.
  • capacity: 100 and the one-day TTL bound the saved backlog. Overflow drops the oldest message because this example only appends.
  • A message_deque requires the original Kafka messages during the window. Use deque when topic retention or compaction cannot provide them.
  • Prosody runs one handler at a time for each key, so a user's message and timer handlers cannot overlap.
  • A notification is outside the state transaction. A retry can send it again. Use a stable operation ID to reject duplicate notifications.

Collections and handles

A definition sets a collection's durable name, kind, and options. Register it once. Pass it to context.state in a handler.

Do not reuse a durable name for a different collection kind or payload type. Create handles inside the handler. Do not retain handles or iterators.

State operations look synchronous. They yield the current fiber while Prosody performs the work.

Collection JSON payload Kafka message Main operations
Value Prosody.value Prosody.message_value get, set, clear
Ordered string map Prosody.map Prosody.message_map get, get_many, key?, set, delete, each_pair, each_key, clear
Deque Prosody.deque Prosody.message_deque push, unshift, pop, shift, get, length, each, clear

Map and deque scans return enumerators when called without a block. Map keys are strings.

nil means absence. Do not store this value. Use clear or delete.

When keyed-state changes become visible

By default, retries do not see pending state from a failed attempt. Reads in a handler see its earlier keyed-state writes. Prosody commits pending changes when the event succeeds and discards them when the handler raises.

This transaction applies only to keyed state. Some workflows need state changes before the handler ends, so each collection also provides explicit controls:

  • read_uncommitted: true persists keyed-state changes before Prosody records the event as complete. If the process stops between these steps, Prosody can process the same event again. The retry sees state changes from the earlier attempt. You must make these keyed-state changes idempotent. Each retry must produce the same state.
  • commit commits the collection's pending changes before the handler ends. A later handler failure does not remove them.
  • rollback discards pending changes since the last commit. It cannot undo committed changes.

Published state

Some callers need only the current value for a key. They can accept a stale value or a race with a concurrent update.

Use topics and event sourcing when a consumer must process each state change in order. Use published state for direct, read-only lookup of persisted keyed state. The caller does not need to consume the owner's topics or maintain a separate lookup store.

Configure the subsystem name on each publisher. Enable publication on the collection definition. Register the definition on the Prosody client:

CURRENT_ORDER = Prosody.value("current-order", published: true)

owner = Prosody::Client.new(
  group_id: "order-writer",
  subsystem: "checkout",
  state_collections: [CURRENT_ORDER]
)

# The handler uses the key from its current event.
current_order = context.state(CURRENT_ORDER)
current_order.set({"sku" => "book"})

Read published state from a handler or other application code. The Prosody client does not need an active subscription.

Use the subsystem and the same definition to open a reader:

order_reader = client.state("checkout", CURRENT_ORDER)
current_order = order_reader.get("customer-123")

The reader cannot see pending changes that exist only in a handler. It cannot change the collection. Each read takes an explicit key because no handler supplies one.

Map and deque readers fetch data in chunks. They do not load the complete collection before iteration starts. Readers return an Enumerator without a block.

Use reverse_each_pair, reverse_each_key, reverse_each_value, or reverse_each for reverse traversal.

The default cache window is five seconds. Set read_cache: to select a different window. Set read_cache: false to bypass the cache.

To stop publication, deploy the definition with published: false. Keep the definition registered during that deployment. Keep the subsystem configured during that deployment.

Timer Functionality

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

class MyHandler < Prosody::EventHandler
  def on_message(context, message)
    # Schedule a timer to fire in 30 seconds
    future_time = Time.now + 30
    context.schedule(future_time)

    # Schedule multiple timers
    one_minute = Time.now + 60
    two_minutes = Time.now + 120
    context.schedule(one_minute)
    context.schedule(two_minutes)

    # Check what's scheduled
    scheduled_times = context.scheduled
    puts "Scheduled timers: #{scheduled_times.length}"
  end

  def on_timer(context, timer)
    puts "Timer fired!"
    puts "Key: #{timer.key}"
    puts "Scheduled time: #{timer.time}"
  end

  def on_excise(context, _message)
    context.clear_scheduled
    nil
  end
end

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
  • clear_and_schedule(time): Clears all timers and schedules a new one
  • unschedule(time): Removes a timer scheduled for the specified time
  • clear_scheduled: Removes all scheduled timers
  • scheduled: Returns an array of all scheduled timer times

Timer Object

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

  • key (String): The entity key identifying what this timer belongs to
  • time (Time): 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:

client = Prosody::Client.new(
  bootstrap_servers: "localhost:9092",
  group_id: "my-application",
  subscribed_topics: "my-topic",
  cassandra_nodes: "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)
client = Prosody::Client.new(
  bootstrap_servers: "localhost:9092",
  group_id: "my-application",
  subscribed_topics: "my-topic",
  mock: true  # No Cassandra required in mock mode
)

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 Ruby.

Required Gems

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

gem 'opentelemetry-sdk', '~> 1.10'
gem 'opentelemetry-api', '~> 1.7'
gem 'opentelemetry-exporter-otlp', '~> 0.31'

Initializing Tracing

To initialize tracing in your application:

require 'opentelemetry/sdk'
require 'opentelemetry/exporter/otlp'

OpenTelemetry::SDK.configure do |c|
  c.service_name = 'my-service-name'
  c.add_span_processor(
    OpenTelemetry::SDK::Trace::Export::BatchSpanProcessor.new(
      OpenTelemetry::Exporter::OTLP::Exporter.new
    )
  )
end

tracer = OpenTelemetry.tracer_provider.tracer('my-service-name')

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:

class MyHandler < Prosody::EventHandler
  def initialize
    @tracer = OpenTelemetry.tracer_provider.tracer('my-service-name')
  end

  def on_message(context, message)
    @tracer.in_span('process-message') do |span|
      # Process the received message
      span.add_event('message.received', attributes: {
        'message.payload' => message.payload.to_json
      })
    end
  end

  def on_excise(_context, _message); end
  def on_timer(_context, _timer); end
end

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 message_spans / PROSODY_MESSAGE_SPANS and timer_spans / PROSODY_TIMER_SPANS options. Accepted values: 'child', 'follows_from'.

Best Practices

Ensuring Thread-Safe Handlers

Your event handler methods will be called concurrently. Avoid using mutable shared state across event handler calls. If you must use shared state, use appropriate synchronization primitives.

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., INSERT ... ON CONFLICT DO UPDATE in PostgreSQL).

  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.

Application shutdown

A Prosody client runs a subscription, timers, and other services in the background. Before an application terminates, it must stop all client services. unsubscribe stops only the active subscription.

Call shutdown when the application terminates. It stops all client services and rejects new operations. Call unsubscribe only when the application will use the client again. You do not need to call unsubscribe before shutdown.

client.shutdown

Handle application shutdown with signal handlers:

require "prosody"

client = Prosody::Client.new(
  bootstrap_servers: "localhost:9092",
  group_id: "my-consumer-group",
  subscribed_topics: "my-topic"
)

# Create the shutdown queue.
shutdown = Queue.new

# Register the signal handlers.
Signal.trap("INT") { shutdown.push(nil) }
Signal.trap("TERM") { shutdown.push(nil) }

# Subscribe with the application handler.
client.subscribe(MyHandler.new)

# Wait for a shutdown signal.
shutdown.pop

# Shut down the client.
puts "Client shutdown starts."
client.shutdown

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.

The error classes and classification methods apply to on_message, on_excise, and on_timer.

Use the Prosody::EventHandler error classification methods:

class MyHandler < Prosody::EventHandler
  # Mark TypeErrors and NoMethodErrors as permanent (not retryable)
  permanent :on_message, TypeError, NoMethodError

  # Mark JSON::ParserError as transient (retryable)
  transient :on_message, JSON::ParserError

  def on_message(context, message)
    # Your message handling logic here
    # TypeError and NoMethodError will be treated as permanent
    # JSON::ParserError will be treated as transient
    # All other exceptions will be treated as transient (default behavior)
  end

  def on_excise(_context, _message); end
  def on_timer(_context, _timer); end
end

Best practices:

  • 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, timeout, or shutdown. During shutdown, handlers run freely for most of the shutdown_timeout before the cancellation signal fires—giving in-flight work time to complete. When cancelled, your handler receives Async::Stop at the next yield point (I/O operation, sleep, etc.).

Best practices:

  1. Use ensure blocks for resource cleanup—they run even when Async::Stop is raised.
  2. For CPU-bound loops that don't yield, check context.should_cancel? periodically.
  3. Exit promptly when cancelled to avoid rebalancing delays.
class MyHandler < Prosody::EventHandler
  def on_message(context, message)
    resource = acquire_resource
    begin
      items = message.payload["items"]
      items.each do |item|
        # For CPU-bound work, check cancellation periodically
        return if context.should_cancel?

        process_item(item)
      end
    ensure
      # Always runs, even on Async::Stop
      release_resource(resource)
    end
  end

  def on_excise(_context, _message); end
  def on_timer(_context, _timer); end
end

If you catch Async::Stop and don't re-raise it, Prosody considers the task successful:

def on_message(context, message)
  do_work
rescue Async::Stop
  # Custom cleanup on cancellation
  cleanup
  raise  # Re-raise to signal cancellation to Prosody
end

Failing to handle cancellation properly can lead to resource leaks or delayed rebalancing.

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 architectures.
    • Linux musl builds for the same architectures.
    • macOS builds for x86_64 and arm64 architectures.
    • Windows builds for x64 architecture.

  4. Artifact Upload: Each build job uploads its artifacts (Ruby native extensions) to GitHub Actions.

  5. Publication: If all builds are successful, the final step publishes the built gems.

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.

Ensure you have thoroughly tested your changes before merging to main.

API Reference

Prosody::Client

  • new(config) or new(**options): Create a client from a Configuration, hash, or keyword options.
  • send_message(String topic, String key, Prosody::json_value payload): Send a JSON-serializable message.
  • excise(String topic, String key): Send an excise record for a key.
  • request(topic:, key:, payload:, subsystems:, timeout:): Return one outcome for each subsystem.
  • request_excise(topic:, key:, subsystems:, timeout:): Return one excise outcome for each subsystem.
  • consumer_state: Get the client state (:shut_down, :unconfigured, :configured, or :running).
  • source_system: Get the source system identifier configured for the client.
  • state(subsystem, definition): Open a typed, read-only published value, map, or deque.
  • subscribe(handler): Start event processing with the specified handler.
  • unsubscribe: Stop the consumer. You can subscribe again later.
  • shutdown: Stop all client services. Concurrent and repeated calls wait for the same operation.
  • assigned_partitions: Get the number of partitions currently assigned to this consumer.
  • is_stalled?: Check if the consumer has stalled partitions.

Prosody::AdminClient

  • new(bootstrap_servers): Create an admin client for the specified Kafka servers.
  • create_topic(name, partitions, replication_factor): Create a Kafka topic.
  • delete_topic(name): Delete a Kafka topic.

Prosody::EventHandler

A base class for user-defined handlers. Its RBS payload parameter flows into Message#payload; a bare handler defaults to Prosody::json_value.

class MyHandler < Prosody::EventHandler
  # Optional error classification
  permanent :on_message, TypeError
  transient :on_message, JSON::ParserError

  def on_message(context, message)
    # Implement your message handling logic here
  end

  def on_timer(context, timer)
    # Implement your timer handling logic here
  end

  def on_excise(_context, _message)
    # Implement your excise handling logic here
  end
end

on_message, on_excise, and on_timer are the handler callbacks. The permanent and transient methods classify selected exceptions.

Prosody::Message

Prosody::Message[Payload] represents a Kafka message. Payload defaults to Prosody::json_value (nil, booleans, numbers, strings, arrays, and string-keyed hashes, recursively). The parameter is static documentation and does not perform runtime validation.

For a type-safe handler, describe the JSON record and specialize the handler in your application's RBS:

type order_event = { "order_id" => String, "total" => Integer }
type response = { "accepted" => bool }

class OrderHandler < Prosody::EventHandler[order_event, response]
  def on_message: (Prosody::Context, Prosody::Message[order_event]) -> response
  def on_excise: (Prosody::Context, Prosody::ExciseMessage) -> response
end

Ruby can then use message.payload["order_id"] as a String and message.payload["total"] as an Integer. See examples/keyed_state.rb and its companion examples/keyed_state.rbs for payload typing that also flows through message-backed state.

Messages have the following attributes:

  • topic (String): The name of the topic.
  • partition (Integer): The partition number.
  • offset (Integer): The message offset within the partition.
  • timestamp (Time): The timestamp when the message was created or sent.
  • key (String): The message key.
  • payload (Payload): The JSON-deserialized message payload.

Prosody::ExciseMessage

An ExciseMessage has topic, partition, offset, timestamp, and key attributes. It has no payload attribute.

Prosody::Context

Represents the current event context:

  • should_cancel?: Check if cancellation has been requested (includes timeout and shutdown).
  • on_cancel: Wait until cancellation occurs.
  • state(definition): Bind a registered collection for the current attempt. An unregistered or mismatched definition raises PermanentStateError. See Keyed State.

Timer scheduling methods:

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

Prosody::Timer

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

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

Requests

  • Prosody::Success[Value]: Contains the response in value.
  • Prosody::Failure: Contains a response error in error.
  • Prosody::HandlerError, Timeout, FormatMismatch, and MalformedResponse: The possible response errors.
  • Prosody::response_error: The union of all response error types.
  • Prosody::outcome[Value]: A Success[Value] or Failure.

Keyed State

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

  • Prosody.value(name, ttl: nil, read_uncommitted: nil, published: nil, read_cache: nil)
  • Prosody.map(name, ttl: nil, keyset_limit: nil, read_uncommitted: nil, published: nil, read_cache: nil)
  • Prosody.deque(name, ttl: nil, capacity: nil, read_uncommitted: nil, published: nil, read_cache: nil)
  • Prosody.message_value(name, ttl: nil, read_uncommitted: nil)
  • Prosody.message_map(name, ttl: nil, keyset_limit: nil, read_uncommitted: nil)
  • Prosody.message_deque(name, ttl: nil, capacity: nil, read_uncommitted: nil)

Each constructor returns a StateDefinition. It exposes name, kind, payload, all supplied options, and to_state_config.

Published readers take the user key as their first argument. Prosody::PublishedValue provides get.

Prosody::PublishedMap provides get, get_many, key?, has_key?, include?, and member?.

It provides each or each_pair, each_key, and each_value. The reverse methods are reverse_each_pair, reverse_each_key, and reverse_each_value.

Prosody::PublishedDeque provides get, length or size, empty?, first, last, each, and reverse_each.

Traversal methods return an Enumerator without a block.

Prosody::ValueState:

  • get / value, set(value) / value=, clear, commit, and rollback

Prosody::MapState (keys are String):

  • get / [], get_many, set / []=, store, delete, and clear
  • key?, has_key?, include?, member?, dig, slice, values_at, fetch, and fetch_values
  • each / each_pair, each_key, and each_value, including each reverse form
  • commit and rollback

Prosody::DequeState:

  • push, append, <<, unshift, prepend, pop, and shift
  • length / size, empty?, get, fetch, first, last, and clear
  • each / reverse_each, commit, and rollback

Errors:

  • Prosody::TransientStateError < Prosody::TransientError: Reports a keyed-state error that Prosody can retry.
  • Prosody::PermanentStateError < Prosody::PermanentError: Reports a keyed-state error that another attempt cannot resolve.
  • Prosody::NullValueError < Prosody::TransientStateError: raised when a nil is written; use clear/delete instead.

Handler error types:

  • Prosody::Error: Base Prosody error.
  • Prosody::EventHandlerError: Base class for classified handler errors.
  • Prosody::TransientError: Marks an error as retriable.
  • Prosody::PermanentError: Marks an error as final.

Configuration

Prosody::Configuration.new accepts a hash or block. Its public properties match the settings in Configuration. to_hash returns a configuration hash.

Logging and telemetry

  • Prosody.logger: Get the current logger or create the default logger.
  • Prosody.logger=: Replace the current logger. Assign nil to restore the default.
  • Prosody.flush_telemetry: Export pending telemetry.
  • Prosody.shutdown_telemetry: Export pending telemetry and stop its providers.

Sentry

  • Prosody::SentryIntegration.enabled?: Test whether Sentry integration is active.
  • Prosody::SentryIntegration.capture_exception(exception, context = {}): Report an exception with optional context.