Kafka consultants

We can help you automate your business with Kafka and hundreds of other systems to improve efficiency and productivity. Get in touch if you’d like to discuss implementing Kafka.

Integration And Tools Consultants

Kafka

About Kafka

Apache Kafka is a distributed event streaming platform used for building real-time data pipelines and event-driven applications at scale. As an automation node, it allows workflows to produce messages to Kafka topics and consume messages from them, connecting your visual automation platform to high-throughput streaming data infrastructure without writing consumer or producer code from scratch.

Engineering teams, data platform operators, and organisations with event-driven architectures use the Kafka integration to bridge their streaming data infrastructure with business automation workflows. Instead of building custom consumer applications for every downstream action that needs to respond to Kafka events, the events trigger automated processing through a visual workflow builder that non-developers can maintain.

Osher integrates Kafka into enterprise automation architectures where high-volume, real-time data processing is a core requirement. Our n8n consulting team builds workflows that consume Kafka events for order processing, IoT sensor data routing, log analysis alerting, and real-time data synchronisation between systems that would otherwise require months of custom application development.

Kafka FAQs

Frequently Asked Questions

What can I do with Kafka in an automation workflow?

When should I use Kafka instead of standard webhooks or API polling?

Does the Kafka integration support authentication and encryption?

Can I consume from multiple Kafka topics in a single workflow?

How does the integration handle message processing failures?

Is Kafka suitable for small-scale automation, or is it only for enterprise use?

How it works

We work hand-in-hand with you to implement Kafka

Step 1

Gather Your Kafka Cluster Details

Collect the bootstrap server addresses, authentication credentials, and topic names for your Kafka cluster. If using a managed service like Confluent Cloud or Amazon MSK, retrieve the connection details from your provider’s dashboard.

Step 2

Configure Kafka Credentials

Add your Kafka connection details to your automation platform’s credential store. Specify the bootstrap servers, authentication method (SASL or SSL), and provide the necessary certificates or credentials.

Step 3

Set Up the Kafka Trigger or Producer Node

For consuming messages, add a Kafka Trigger node and specify the topic and consumer group. For producing messages, add a Kafka node and configure the target topic, key, and message format.

Step 4

Define Message Processing Logic

Parse incoming Kafka messages and route them through your workflow. Add nodes for data transformation, enrichment from external APIs, conditional routing based on message content, and writing results to target systems.

Step 5

Configure Error Handling and Dead Letter Routing

Set up error handling for malformed messages, processing failures, and downstream system outages. Route failed messages to a dead letter topic or error database for investigation and reprocessing.

Step 6

Test with Production-Like Data

Send test messages through your Kafka topic and verify the workflow processes them correctly. Monitor consumer lag, processing latency, and error rates before routing production traffic through the automation.

Transform your business with Kafka

Unlock hidden efficiencies, reduce errors, and position your business for scalable growth. Contact us to arrange a no-obligation Kafka consultation.