# Apache Kafka 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 helm repo add fiddler https://helm.fiddler.ai/stable/ helm repo update kubectl -n kafka create secret generic fiddler-credentials --from-literal=auth= helm install fiddler-kafka fiddler/fiddler-kafka \ --devel \ --namespace kafka \ --set fiddler.url=https:// \ --set fiddler.org= \ --set fiddler.project_id= \ --set fiddler.model_id= \ --set fiddler.ts_field=timestamp \ --set fiddler.ts_format=INFER \ --set kafka.host=kafka \ --set kafka.port=9092 \ --set 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 { “feature_1”: 20.7, “feature_2”: 45000, “feature_3”: true, “output_column”: 0.79, “target_column”: 1, “ts”: 1637344470000, } ``` --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.fiddler.ai/integrations/data-platforms-and-pipelines/data-platforms/kafka-integration.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.