Message Bus

The MessageBus is a fundamental component of the platform, facilitating communicate between various system components through message passing. This approach enables a loosely coupled architecture, where components can interact without strong dependencies. Messages exchanged via the message bus can be categorized into three distinct types:

  • Data

  • Events

  • Commands

Data and signal publishing

While the message bus is considered a lower-level component, users typically interact with it indirectly. Actor and Strategy classes provide two convenience methods built on top of the underlying MessageBus , for easier custom data and signal publishing:

def publish_data(self, data_type: DataType, data: Data) -> None:
def publish_signal(self, name: str, value, ts_event: int | None = None) -> None:

Direct access

For advanced users and specific use cases, direct access to the message bus is available from within Actor and Strategy classes through the self.msgbus reference, which exposes the message bus interface directly. To publish a custom message, simply provide a topic as a str and any Python object as the message payload, for example:

self.msgbus.publish("MyTopic", "MyMessage")

External publishing

The MessageBus can be ‘backed’ with any database or message broker technology which has an integration written for it, this then allows external publishing of messages.


Currently Redis is supported for all serializable messages which are published.

Under the hood, when a backing database (or any other compatible technology) is configured, all outgoing messages are first serialized. These serialized messages are then transmitted via a Multiple-Producer Single-Consumer (MPSC) channel to a separate thread, which is implemented in Rust. In this separate thread, the message is written to its final destination, which is presently Redis streams.

This design is primarily driven by performance considerations. By offloading the I/O operations to a separate thread, we ensure that the main thread remains unblocked and can continue its tasks without being hindered by the potentially time-consuming operations involved in interacting with a database or client.


Most Nautilus built-in objects are serializable, dictionaries dict[str, Any] containing serializable primitives, as well as primitive types themselves such as str , int , float , bool and bytes . Additional custom types can be registered by calling the following registration function from the serialization subpackage:

def register_serializable_object(
    to_dict: Callable[[Any], dict[str, Any]],
    from_dict: Callable[[dict[str, Any]], Any],
  • obj The object to register

  • to_dict The delegate to instantiate a dict of primitive types from the object

  • from_dict The delegate to instantiate the object from a dict of primitive types


The message bus external backing technology can be configured by importing the MessageBusConfig object and passing this to your TradingNodeConfig . Each of these config options will be described below.

...  # Other config omitted
    types_filter=[QuoteTick, TradeTick],

Database config

A DatabaseConfig must be provided, for a default Redis setup on the local loopback you can pass a DatabaseConfig() , which will use defaults to match.


Two encodings are currently supported by the built-in Serializer used by the MessageBus :

  • JSON ( json )

  • MessagePack ( msgpack )

Use the encoding config option to control the message writing encoding.


The msgpack encoding is used by default as it offers the most optimal serialization and memory performance. It’s recommended to use json encoding for human readability when performance is not a primary concern.

Timestamp formatting

By default timestamps are formatted as UNIX epoch nanosecond integers. Alternatively you can configure ISO 8601 string formatting by setting the timestamps_as_iso8601 to True .

Message stream keys

Message stream keys are essential for identifying individual trader nodes and organizing messages within streams. They can be tailored to meet your specific requirements and use cases. In the context of message bus streams, a trader key is typically structured as follows:


The following options are available for configuring message stream keys:

Trader prefix

If the key should begin with the trader string.

Trader ID

If the key should include the trader ID for the node.

Instance ID

Each trader node is assigned a unique ‘instance ID,’ which is a UUIDv4. This instance ID helps distinguish individual traders when messages are distributed across multiple streams. You can include the instance ID in the trader key by setting the use_instance_id configuration option to True . This is particularly useful when you need to track and identify traders across various streams in a multi-node trading system.

Streams prefix

The streams_prefix string allows you to group all streams for a single trader instance, or organize messages related to a group of trader instances. By configuring this grouping behavior, pass a string to the streams_prefix configuration option (with other prefixes false).

Types filtering

When messages are published on the message bus, they are serialized and written to a stream, provided that a backing for the message bus has been configured and enabled. However, in some cases, you may want to filter out certain types of messages from being externally published to prevent the stream from being ‘flooded’ with data, such as quotes or other high-frequency information.

To enable this filtering mechanism, pass a list of type objects to the types_filter parameter in the message bus configuration, specifying which types of messages should be excluded from external publication.

from nautilus_trader.config import MessageBusConfig
from import TradeTick
from import QuoteTick

# Create a MessageBusConfig instance with types filtering
message_bus = MessageBusConfig(
    types_filter=[QuoteTick, TradeTick]

Stream auto-trimming

The autotrim_mins configuration parameter allows you to specify the lookback window in minutes for automatic stream trimming in your message streams. Automatic stream trimming helps manage the size of your message streams by removing older messages, ensuring that the streams remain manageable in terms of storage and performance.


The current Redis implementation will maintain the autotrim_mins as a maximum width (plus roughly a minute, as streams are trimmed no more than once per minute). Rather than for instance a maximum lookback window based on the current wall clock time.