## Format

All events are streamed to the broker as serialized dictionaries every time the tracker updates its state. An example event emitted from the `default` tracker looks like this:

```json
{
    "sender_id": "default",
    "timestamp": 1528402837.617099,
    "event": "bot",
    "text": "what your bot said",
    "data": "some data about e.g. attachments",
    "metadata": {
          "a key": "a value"
     }
}
```

The `event` field takes the event's `type_name` (for more on event types, check out the [events](/content/docs/reference/integrations/action-server/events/index.html) docs).

## Kafka Event Broker

[Kafka](https://kafka.apache.org/) is recommended for all assistants at scale. Kafka is a **requirement** when streaming events to Rasa Pro Services or Rasa Studio.

Rasa uses the [confluent-kafka](https://docs.confluent.io/platform/current/clients/confluent-kafka-python/html/index.html#) library, a Kafka client written in Python.

### Configuration

To use Kafka as an event broker in Rasa, you need to set it as an `event_broker` in your `endpoints.yml` file. For Kafka, Rasa supports following properties in `event_broker` section:

endpoints.yml

```yaml
event_broker:
  type: kafka
  url: localhost:9092  # required, url to your kafka broker

# Optional properties
  topic: rasa_core_events # topic to which events are published
  security_protocol: "SASL_PLAINTEXT" # security protocol to use, available options are: PLAINTEXT, SASL_PLAINTEXT, SSL, SASL_SSL
  partition_by_sender: False # should events be partitioned by sender id
  client_id: # ID to use for the producer of the events

# SASL configuration, optional
  sasl_mechanism: "PLAIN" # SASL mechanism to use, available options are: PLAIN, GSSAPI, OAUTHBEARER, SCRAM-SHA-256, SCRAM-SHA-512
  sasl_username: # username to use for authentication, only if security_protocol is SASL_PLAINTEXT or SASL_SSL
  sasl_password: # password to use for authentication, only if security_protocol is SASL_PLAINTEXT or SASL_SSL

# TLS configuration, optional
  ssl_cafile: # path to the CA certificate file, only if security_protocol is SSL or SASL_SSL
  ssl_certfile: # path to the client certificate file, only if security_protocol is SSL or SASL_SSL and Kafka is configured to use client authentication
  ssl_keyfile: # path to the client key file, only if security_protocol is SSL or SASL_SSL and Kafka is configured to use client authentication
  ssl_check_hostname: False # whether to check the hostname of the broker against the certificate, default is True

# PII management configuration, optional
  stream_pii: False # whether to stream PII events, default is True
  anonymization_topics: # list of topics to publish anonymized events to, default is []
   - anonymized_topic_1
```

#### Partition Key

Rasa's Kafka producer can optionally be configured to partition messages by conversation ID. This can be configured by setting `partition_by_sender` in the `endpoints.yml` file to True. By default, this parameter is set to `False` and the producer will randomly assign a partition to each message.

#### Authentication and Authorization

Rasa's Kafka producer accepts the following types of security protocols: `SASL_PLAINTEXT`, `SSL`, `PLAINTEXT` and `SASL_SSL`.

For development environments, or if the brokers servers and clients are located into the same machine, you can use simple authentication with `SASL_PLAINTEXT` or `PLAINTEXT`. By using this protocol, the credentials and messages exchanged between the clients and servers will be sent in plaintext. Thus, this is not the most secure approach, but since it's simple to configure, it is useful for simple cluster configurations. `SASL_PLAINTEXT` protocol requires the setup of the `username` and `password` previously configured in the broker server.

If the clients or the brokers in the kafka cluster are located in different machines, it's important to use the `SSL` or `SASL_SSL` protocol to ensure encryption of data and client authentication. After generating valid certificates for the brokers and the clients, the path to the certificate and key generated for the producer must be provided as arguments, as well as the CA's root certificate.

If using the `GSSAPI` SASL mechanism, you will need to additionally install [python-gssapi](https://pypi.org/project/python-gssapi/) and the necessary C library Kerberos dependencies.

##### Using IAM roles to authenticate to AWS Managed Streaming for Apache Kafka (MSK)

You can use IAM authentication to connect to AWS MSK without needing to provide a username and password.

If your Rasa instance is running on an AWS service that supports IAM roles (e.g. EC2), you can use IAM authentication to connect to an AWS MSK cluster without needing to provide a username and password.

To do so, you need to ensure that your MSK cluster is configured to allow IAM authentication. Ensure that the topic(s) you want to use are created on the MSK cluster. You also need to set up your Rasa instance with an appropriate IAM role that has permissions to access the MSK cluster.

The IAM role should include the following permissions:

```text
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "kafka-cluster:Connect",
                "kafka-cluster:DescribeCluster"
            ],
            "Resource": [
                "arn:aws:kafka:<region_name>:<account_id>:cluster/<cluster_name>/<cluster_uuid>"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "kafka-cluster:*Topic*",
                "kafka-cluster:WriteData",
                "kafka-cluster:ReadData"
            ],
            "Resource": [
                "arn:aws:kafka:<region_name>:<account_id>:topic/<cluster_name>/*"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "kafka-cluster:AlterGroup",
                "kafka-cluster:DescribeGroup"
            ],
            "Resource": [
                "arn:aws:kafka:<region_name>:<account_id>:group/<cluster_name>/*"
            ]
        }
    ]
}
```

Once you have set up the IAM role and configured your AWS MSK cluster, you can configure the following environment variables in your Rasa instance:

- `IAM_CLOUD_PROVIDER`: Set this to `aws`.
- `AWS_DEFAULT_REGION`: Set this to the AWS region where your MSK cluster is located.
- `KAFKA_MSK_AWS_IAM_ENABLED`: Set this to `true` to enable IAM authentication for MSK connections, otherwise leave it unset or set to `false`.

You also need to configure the Kafka event broker in your `endpoints.yml` file to use the `SASL_SSL` security protocol and `OAUTHBEARER` SASL mechanism, as well as provide the path to the root certificate from Amazon Trust Services in the `ssl_cafile` property.

endpoints.yml

```yaml
event_broker:
    type: kafka
    url: <your-msk-broker-url>
    topic: rasa_core_events
    security_protocol: "SASL_SSL"
    sasl_mechanism: "OAUTHBEARER"
    ssl_cafile: <path-to-amazon-trust-services-root-certificate>
    partition_by_sender: true
    client_id: <your-client-id>
    ssl_check_hostname: true
```

When you start your Rasa instance, it will use the IAM role to generate temporary credentials to log in to the AWS MSK cluster instead of using static credentials. The temporary credentials will be automatically refreshed every 15 minutes.

### Example Configurations

#### Without authentication

To set up Rasa with Kafka which does not require authentication nor TLS handshake, use the following config as an example:

endpoints.yml

```yaml
event_broker:
  type: kafka
  security_protocol: PLAINTEXT
  topic: topic
  url: localhost
```

To set up Rasa with Kafka which does not require authentication but uses TLS handshake, use the following config as an example:

endpoints.yml

```yaml
event_broker:
  type: kafka
  security_protocol: SSL
  topic: topic
  url: localhost
  ssl_cafile: CARoot.pem
  ssl_certfile: certificate.pem
  ssl_keyfile: key.pem
  ssl_check_hostname: True
```

#### With authentication

To set up Rasa with Kafka which requires authentication but does not use TLS handshake, use the following config as an example:

endpoints.yml

```yaml
event_broker:
  type: kafka
  security_protocol: SASL_PLAINTEXT
  topic: topic
  url: localhost
  sasl_username: username
  sasl_password: password
  sasl_mechanism: PLAIN
```

To set up Rasa with Kafka which requires authentication and uses TLS handshake, use the following config as an example:

endpoints.yml

```yaml
event_broker:
  type: kafka
  security_protocol: SASL_SSL
  topic: topic
  url: localhost
  sasl_username: username
  sasl_password: password
  sasl_mechanism: PLAIN
  ssl_cafile: CARoot.pem
  ssl_certfile: certificate.pem
  ssl_keyfile: key.pem
  ssl_check_hostname: True
```

Make sure that the SASL mechanism is set according to the broker configuration. You can also use `GSSAPI`, `OAUTHBEARER`, `SCRAM-SHA-256` or `SCRAM-SHA-512` if your broker is configured to use it for the exposed URL endpoint.

### Sending Events to Multiple Queues

Kafka does not allow you to configure multiple topics. However, multiple consumers can read from the same queue as long as they are in different consumer groups. Each consumer group will process all events independent of each other.

#### Disabling Publishing of Un-anonymised Events

You can configure the event broker to not publish un-anonymised events to the configured topic. This is done by setting the `stream_pii` parameter in the `endpoints.yml` file to `false`.

#### Sending Anonymized Events

If you have the PII management capability enabled, you can configure the event broker to publish anonymised events to a different topic. This is done by setting the `anonymization_topics` parameter in the `endpoints.yml` file to a list of topics.

### Non-Blocking Publishing

You can configure Kafka to publish events without blocking the event loop by setting `type: concurrent_kafka` instead of `type: kafka`. By default, `type: kafka` publishes events synchronously on the event loop. Each publish call waits for the Kafka broker to acknowledge the event before returning. For latency-sensitive deployments, use `type: concurrent_kafka` instead.

endpoints.yml

```yaml
event_broker:
  type: concurrent_kafka
  url: localhost:9092
  topic: rasa_core_events

# All options from type: kafka are supported
  security_protocol: "SASL_PLAINTEXT"
  sasl_mechanism: "PLAIN"
  sasl_username: myuser
  sasl_password: mypassword
  partition_by_sender: True

# Additional option: number of background publish threads (default: 1)
  executor_max_workers: 1
```

Ordering with multiple workers

When `executor_max_workers` is greater than 1, concurrent retries can reorder events for the same sender. Set `partition_by_sender: True` to ensure events for a given conversation always land on the same Kafka partition, but note that retry races between threads may still affect ordering within a partition. For strict ordering guarantees, keep `executor_max_workers: 1` (the default).

## Pika Event Broker for RabbitMQ

Rasa uses [Pika](https://pika.readthedocs.io/), the Python client library for [RabbitMQ](https://www.rabbitmq.com/).

### Configuration

To use RabbitMQ as an event broker in Rasa, you need to set it as an `event_broker` in your `endpoints.yml` file. For RabbitMQ, Rasa supports following properties in `even_broker` section:

endpoints.yml

```yaml
event_broker:
  type: pika
  host: # required, hostname of your RabbitMQ broker e.g. localhost
  port: 5672 # port of your RabbitMQ broker e.g. 5672
  exchange_name: "rasa-exchange" # exchange name to use for publishing events
  username: # required, username to use for authentication
  password: # required, password to use for authentication
  connection_attempts: 20 # number of connection attempts to make before giving up
  retry_delay_in_seconds: 5 # time to wait before retrying connection attempts
  raise_on_failure: False #whether to raise an exception on connection failure
  should_keep_unpublished_messages: True # whether to keep unpublished messages in memory
  queues: # list of queues to publish events to"
    - rasa_core_events # default
  stream_pii: False # whether to publish un-anonymised events to the configured queues. defaults to True
  anonymization_queues: # list of queues to publish anonymized events to. defaults to []
    - anonymized_event_queue
```

Additionally, you can use TLS with RabbitMQ by setting the following environment variables:

- `RABBITMQ_SSL_CLIENT_CERTIFICATE`: path to the SSL client certificate
- `RABBITMQ_SSL_CLIENT_KEY`: path to the SSL client key

### Example Configurations

To set up Rasa with Pika for RabbitMQ use the following config as an example:

endpoints.yml

```yaml
event_broker:
  type: pika
  url: localhost
  username: username
  password: password
  queues:
    - queue-1
  exchange_name: exchange
```

### Adding a Pika Event Broker in Python

Here is how you add it using Python code:

```python
import asyncio

from rasa.core.brokers.pika import PikaEventBroker
from rasa.core.tracker_store import InMemoryTrackerStore

pika_broker = PikaEventBroker('localhost',
                              'username',
                              'password',
                              queues=['rasa_events'],
                              event_loop=event_loop
                              )
asyncio.run(pika_broker.connect())

tracker_store = InMemoryTrackerStore(domain=domain, event_broker=pika_broker)
```

### Implementing a Pika Event Consumer

You need to have a RabbitMQ server running, as well as another application that consumes the events. This consumer to needs to implement Pika's `start_consuming()` method with a `callback` action. Here's a simple example:

```python
import json
import pika

def _callback(ch, method, properties, body):
        print("Received event {}".format(json.loads(body)))

if __name__ == "__main__":

credentials = pika.PlainCredentials("username", "password")

connection = pika.BlockingConnection(
        pika.ConnectionParameters("rabbit", credentials=credentials)
    )

channel = connection.channel()
    channel.basic_consume(queue="rasa_events", on_message_callback=_callback, auto_ack=True)
    channel.start_consuming()
```

### Sending Events to Multiple Queues

You can specify multiple event queues to publish events to. This should work for all event brokers supported by Pika (e.g. RabbitMQ).

#### Disabling Publishing of Un-anonymised Events

By default, Rasa will publish un-anonymised events to the configured queues. If you want to disable this and only publish anonymized events, set `stream_pii: false` in your `event_broker` configuration.

#### Publishing Anonymized Events

If you want to publish anonymized events to a different queue, you can set the `anonymization_queues` property in your `event_broker` configuration.

## SQL Event Broker

It is possible to use an SQL database as an event broker. Connections to databases are established using [SQLAlchemy](https://www.sqlalchemy.org/), a Python library which can interact with many different types of SQL databases.

To set up Rasa with SQL event broker the following steps are required:

1. Add required configuration to your `endpoints.yml`

When using SQLite:

endpoints.yml

```yaml
event_broker:
  type: SQL
  dialect: sqlite
  db: events.db
```

When using PostgreSQL:

endpoints.yml

```yaml
event_broker:
  type: SQL
  url: 127.0.0.1
  port: 5432
  dialect: postgresql
  username: myuser
  password: mypassword
  db: mydatabase
```

2. To start the Rasa server using your SQL backend, add the `--endpoints` flag.

```bash
rasa run -m models --endpoints endpoints.yml
```

## FileEventBroker

It is possible to use the `FileEventBroker` as an event broker. This implementation will log events to a file in json format.

You can provide a path key in the `endpoints.yml` file if you wish to override the default file name: `rasa_event.log`.

## Custom Event Broker

If you need an event broker which is not available out of the box, you can implement your own by extending the base class `EventBroker`.

To set up Rasa with your custom event broker the following steps are required:

1. Add required configuration to your `endpoints.yml`

endpoints.yml

```yaml
event_broker:
  type: path.to.your.module.Class
  url: localhost
  a_parameter: a value
  another_parameter: another value
```

2. To start the Rasa server using your custom backend, add the `--endpoints` flag.

```bash
rasa run -m models --endpoints endpoints.yml
```