Chapter 1. Developing clients overview
Develop Kafka client applications for your AMQ Streams installation that can produce messages, consume messages, or do both. You can develop client applications for use with AMQ Streams on OpenShift or AMQ Streams on RHEL.
Messages comprise an optional key and a value that contains the message data, plus headers and related metadata. The key identifies the subject of the message, or a property of the message. You must use the same key if you need to process a group of messages in the same order as they are sent.
Messages are delivered in batches. Messages contain headers and metadata that provide details that are useful for filtering and routing by clients, such as the timestamp and offset position for the message.
Kafka provides client APIs for developing client applications. Kafka producer and consumer APIs are the primary means of interacting with a Kafka cluster in a client application. The APIs control the flow of messages. The producer API sends messages to Kafka topics, while the consumer API reads messages from topics.
AMQ Streams supports clients written in Java. How you develop your clients depends on your specific use case. Data durability might be a priority or high throughput. These demands can be met through configuration of your clients and brokers. All clients, however, must be able to connect to all brokers in a given Kafka cluster.
1.1. Supporting a HTTP client
As an alternative to using the Kafka producer and consumer APIs in your client, you can set up and use the AMQ Streams Kafka Bridge. The Kafka Bridge provides a RESTful interface that allows HTTP-based clients to interact with a Kafka cluster. It offers the advantages of a web API connection to Strimzi, without the need for client applications that need to interpret the Kafka protocol. Kafka uses a binary protocol over TCP.
For more information, see Using the AMQ Streams Kafka Bridge.
1.2. Tuning your producers and consumers
You can add more configuration properties to optimize the performance of your Kafka clients. You probably want to do this when you’ve had some time to analyze how your client and broker configuration performs.
For more information, see Kafka configuration tuning.
1.3. Monitoring client interaction
Distributed tracing facilitates the end-to-end tracking of messages. You can enable tracing in Kafka consumer and producer client applications.
For more information, see the documentation for distributed tracing in the following guides:
When we use the term client application, we’re specifically referring to applications that use Kafka producers and consumers to send and receive messages to and from a Kafka cluster. We are not referring to other Kafka components, such as Kafka Connect or Kafka Streams, which have their own distinct use cases and functionality.
