Chapter 1, Configuring Kafka, explains the basic recipes used to get started with Apache Kafka. It discusses how to install, configure, and run Kafka. It also discusses how to do basic operations with a Kafka broker.
Chapter 2, Kafka Clusters, covers how to make three types of clusters: single-node single-broker cluster, single-node multiple-broker cluster, and multiple-node multiple-broker cluster.
Chapter 3, Message Validation, in this chapter having an enterprise service bus, one of the tasks is related to data validation, this is filtering some events from an input message stream. This chapter is about the programming of this validation.
Chapter 4, Message Enrichment, details how the next task of an enterprise service bus is related to message enrichment, which means having an individual message, obtaining additional information, and incorporating it into the message stream.
Chapter 5, The Confluent Platform, shows how to operate and monitor a Kafka system with the Confluent Platform. It also explains how to use the Schema Registry, the Kafka REST Proxy, and Kafka Connect.
Chapter 6, Kafka Streams, explains how to obtain information about a group of messages (a message stream) and additional information such as aggregation and composition of messages using Kafka Streams.
Chapter 7, Managing Kafka, talks about the command-line tools developed by the authors of Kafka to make a sysadmin team's life easier when debugging, testing, and running a Kafka cluster.
Chapter 8, Operating Kafka, explains the different operations that can be done on a Kafka cluster. These tools cannot be used daily, but they help the DevOps team manage Kafka clusters.
Chapter 9, Monitoring and Security, has a first half that talks about various statistics, how they are exposed, and how to monitor them with tools such as Graphite and Ganglia. Its second part is about security—in a nutshell, how to implement SSL authentication, SASL/Kerberos authentication, and SASL/plain authentication.
Chapter 10, Third-Party Tool Integration, talks about other real-time data processing tools and how to use Apache Kafka to make a data processing pipeline with them. Tools such as Hadoop, Flume, Gobblin, Elastic, Logstash, Spark, Storm, Solr, Akka, Cassandra, Mesos, and Beam are covered in this chapter.
