Maximising Kafka Performance with Clustering

Maximising Kafka

What is Kafka clustering?

Kafka clustering, often referred to as a Kafka cluster, is a configuration that deploys multiple Kafka broker instances in a distributed manner to create an accessible and fault-tolerant Apache Kafka infrastructure.

Kafka is an open-source streaming platform widely used for real-time data streaming, processing, and event-driven applications. Clustering is a key strategy that ensures Kafka’s reliability, scalability, and performance across a variety of use cases. So, combined together, Kafka clustering is a group of Kafka servers that work together to handle all the data (incoming and outgoing) streams in the Kafka system. Every server (broker) is an independent process running on a different machine, communicating with other servers (brokers) through a reliable high-speed network.
To know more about Kafka, you can refer to this blog.

Exploring Apache Kafka: A High-Throughput Distributed Streaming Platform

Why use Kafka Clustering?

Kafka clustering is easy to implement and you can apply it in your project. It deploys multiple Kafka brokers and Zookeeper nodes on multiple machines. This strategic approach offers benefits such as stability, scalability and improved performance. This setup also requires at least two environments for Kafka clustering to work effectively.
Here, we’ll use two machines for Kafka clustering as an example, server1IPAddress and server2IPAddress of the respective machine IP addresses for our configuration. We can use the same pattern with more machine for clustering and improve Kafka performance and stability.

Use of Kafka clustering

Configuring Zookeeper:

  • Edit Zookeeper configuration: Edit the Zookeeper file, which is in the Zookeeper conf directory and is created at the time of Zookeeper installation.
  • Add server entries: Add an entry to the zookeeper.properties file for each server in the cluster. It is very important to ensure that dataDir points to the correct Zookeeper data directory on each server.


  • Expand the cluster: To scale the cluster, simply add entries like server.3=server3 IP Address to each server zookeeper properties file.
  • Start Zookeeper: After modifying the configuration files, initialise Zookeeper on each server with the appropriate command.
  • bin/zookeeper-server-start.sh config/zookeeper.properties

Configure Kafka:

Edit server properties:

  • Kafka requires adjustments in the server.properties file for each machine in the cluster.
  • Assign a unique broker.id on each machine in the cluster. This identifier must be increment by 1 for each new machine added to provide a unique identity.
  • For machine 1:


  • For machine 2:


  • Set the zookeeper: connect field with the IP addresses of all computers in the cluster next to the Zookeeper port. This field must have the same value on all machines and must be updated each time a new machine joins the cluster.
  • Run Kafka: Once Apache Kafka linking is done, run it on each server using below command.
  • bin/kafka-server-start.sh config/server.properties

Scalability and performance

  • Apache Kafka cluster provides the flexibility to scale your infrastructure to meet the changing needs. The more machines integrated into the cluster, the better the performance and stability of Kafka. By reducing the risk of single points of failure, clustering also ensures continuous data availability.
  • Clustering is strongly recommended in production environments. Running Kafka on a single machine can create a single point of failure that can put your entire Kafka cluster linking at risk.
  • For optimal performance and fault tolerance, you can configure partition and replication policies in Kafka and Zookeeper. However, these strategies may increase storage and computational requirements depending on the approach chosen.


Kafka clustering is a key strategy for ensuring the stability and performance of a Kafka deployment. By deploying Kafka brokers and Zookeeper nodes on multiple machines, you can achieve high availability, scalability, and reliability for streaming data. Looking for the apache kafka developer to handle your development needs? Connect with us! We at Ficode have expert developers who possess years of experience in handling all your business requirements.


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