> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fiddler.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Apache Kafka

> Dive into Fiddler’s Kafka connector services. Learn about prerequisites, installation, and limitations to manage production events and publish them to Fiddler.

Fiddler Kafka connector is an optional Fiddler service that connects to a [Kafka topic](https://kafka.apache.org/documentation/#intro_concepts_and_terms) containing production events for a model, and publishes the events to Fiddler.

### Kafka Integration Pre-requisites

We assume that the user has an account with Fiddler, has already created a project, and onboarded a model.

#### Installation

For Fiddler on-premises installations, the Kafka connector runs on Kubernetes in your environment. It is packaged as a Helm chart for quick installation:

```shell theme={null}
helm repo add fiddler https://helm.fiddler.ai/stable/

helm repo update

kubectl -n kafka create secret generic fiddler-credentials --from-literal=auth=<API-KEY>

helm install fiddler-kafka fiddler/fiddler-kafka 
    --devel 
    --namespace kafka 
    --set fiddler.url=https://<FIDDLER-URL> 
    --set fiddler.org=<ORG> 
    --set fiddler.project_id=<PROJECT-ID> 
    --set fiddler.model_id=<MODEL-ID> 
    --set fiddler.ts_field=timestamp 
    --set fiddler.ts_format=INFER 
    --set kafka.host=kafka 
    --set kafka.port=9092 
    --set kafka.topic=<KAFKA-TOPIC> 
    --set kafka.security_protocol=SSL 
    --set kafka.ssl_cafile=cafile 
    --set kafka.ssl_certfile=certfile 
    --set kafka.ssl_keyfile=keyfile 
    --set-string kafka.ssl_check_hostname=False

```

This creates a deployment that reads event data from the Kafka topic and publishes it to the configured Fiddler model. The deployment can be scaled as needed; however, note that if the Kafka topic is not partitioned, scaling will not result in any gains.

#### Limitations

1. The connector assumes that there is a single dedicated topic containing production events for a given model. Multiple deployments can be created, one for each model, and scaled independently.
2. The connector assumes that events are published as JSON-serialized dictionaries of key-value pairs. Support for other formats can be added on request. As an example, a Kafka message should look like the following:

```json theme={null}
{
    “feature_1”: 20.7,
    “feature_2”: 45000,
    “feature_3”: true,
    “output_column”: 0.79,
    “target_column”: 1,
    “ts”: 1637344470000,
}

```