This section describes the Kafka agents. The agents are used to forward and collect messages using Kafka. Kafka is a cluster-based software that is executed outside of . Kafka uses a high throughput publish-subscriber messaging model. It persists all messages and by design, it decouples the publisher from the subscriber. That means that the forwarding agent will keep writing to the log even if the collection agents terminate.
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The Kafka agents enable you to configure workflows with improved scalability and fault tolerance. As part of the data collection, data is written to Kafka to secure it from being lost if a failure occurs, and each topic can be set up to be replicated across several servers.
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Example of Kafka workflows
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Using Kafka provides the capability to scale as required. One of the many ways to scale a Kafka cluster is when you create your Kafka configuration. It is recommended that when creating your Kafka configuration, you consider how many partitions you may eventually require and require and add more than you may may currently require, as this will make it easier to scale up at a later stage.
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Example of Scaling a Kafka Cluster
You can also refer to http://kafka.apache.org for guidance on scaling using partitions.
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| The IP and port of a Zookeeper node in the cluster. To find the connection details to all Zookeeper nodes, run the mzsh command
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| The service id is the Kafka service name defined in
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Example of reference to embedded Zookeeper service instance
is the equivalent of
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