Skip to main content
Connic

Apache Kafka

By Connic

Subscribe an agent to a topic and every message becomes a run. Publish the agent's output back to another topic for downstream consumers. Consumer groups, offsets, and reconnection are handled.

InboundOutbound

Overview

The Kafka connector is a managed consumer and producer for your agents. Point an inbound connector at your brokers and a topic, and every message on that topic becomes an agent run: JSON object messages arrive with their top-level fields intact, anything else is wrapped under a message key, and each run carries the topic, partition, offset, timestamp, and message key as _kafka metadata.

You skip the consumer service you would otherwise operate. Connic manages the consumer group, tracks offsets, reconnects with exponential backoff, and picks up configuration changes. Add an outbound connector and completed results are produced to a destination topic, so a full consume, process, produce pipeline needs no code beyond the agent itself.

How it works

1

Create an inbound consumer

Add an Apache Kafka connector from your agent's Connector Flow in Inbound (Consumer) mode. Enter your bootstrap servers and the topic to consume, plus an optional consumer group ID and auto offset reset (latest for new messages only, earliest to start from the beginning).

2

Configure security

Choose PLAINTEXT, SSL, SASL_PLAINTEXT, or SASL_SSL. For managed Kafka like Confluent, MSK, or Aiven, use SASL_SSL with SCRAM-SHA-256. For TLS and mutual TLS, paste certificate and key PEM contents directly into the form.

3

Link agents, optionally produce results

Each message on the topic is dispatched to all linked agents. To publish results downstream, add an outbound connector with bootstrap servers and a destination topic; completed run outputs are produced there automatically.

What you can build

Patterns teams ship in production. No queues, workers, or schedulers to run.

Trigger

Message posted

topic: user.content.created
Agent Action

Agent scores each post for toxicity and policy fit, and either publishes, queues for review, or hides it — all before the comment renders to other users.

Message payload and consumer semantics

JSON object messages are dispatched with their top-level fields as the payload, plus a _kafka block with topic, partition, offset, timestamp, and key. Non-JSON values arrive under a message key, and compaction tombstones still trigger runs with message: null, so your agent can react to deletions using _kafka.key. Consumer groups behave the way you expect: connectors with different group IDs each see every message, and connectors sharing a group ID split the load.

Every consumed message becomes a normal agent run, with full traces, token and cost tracking, and the same guardrails and approval rules as any other trigger. A high-volume topic does not become a black box.

Producing results back

Outbound connectors publish results when linked agents complete. Only runs with status completed are published; failed and cancelled runs are skipped. When a run was triggered by an inbound message with a key, the result is produced with the same key, preserving ordering within partitions across the whole pipeline; runs without an inbound key use the run ID. Messages are produced with full replication acknowledgment and automatic retries. See payload formats and an end-to-end pipeline in the Kafka docs.

Information

Publisher
By Connic
Category
Connectors
Modes
Inbound, Outbound
Documentation
Apache Kafka docs

Frequently Asked Questions

How do I trigger an AI agent from a Kafka topic?

Create an Apache Kafka connector in Inbound (Consumer) mode with your bootstrap servers and topic, then link it to an agent. Every message on the topic triggers a run on all linked agents, with the message body as payload and Kafka metadata attached under _kafka. The Kafka connector reference covers payload formats and the end-to-end pipeline.

Which Kafka security setups are supported?

PLAINTEXT, SSL, SASL_PLAINTEXT, and SASL_SSL, with PLAIN, SCRAM-SHA-256, or SCRAM-SHA-512 as SASL mechanisms. Mutual TLS is supported by pasting CA, client certificate, and client key PEM contents into the connector form. For managed Kafka services, SASL_SSL with SCRAM-SHA-256 is the recommended setup.

Can the agent publish results back to a Kafka topic?

Yes. Add an outbound connector with a destination topic and completed run results are produced there, including the agent output, run metadata, and token usage. Results reuse the inbound message key when there is one, so partition ordering carries through the pipeline.
Need Apache Kafka in a production agent flow?

Bring the event source, payload shape, result destination, and any private-network or approval requirements. We will map Apache Kafka to the right Connic connector mode, deployment path, and observability setup.

Talk to Sales