Developing Amazon Kinesis Streams Consumers Using the Amazon Kinesis Client Library
You can develop a consumer application for Amazon Kinesis Streams using the Amazon Kinesis Client Library (KCL). Although you can use the Streams API to get data from an Amazon Kinesis stream, we recommend using the design patterns and code for consumer applications provided by the KCL.
You can monitor the KCL with Amazon CloudWatch. For more information, see Monitoring the Amazon Kinesis Client Library with Amazon CloudWatch.
- Amazon Kinesis Client Library
- Role of the KCL
- Developing an Amazon Kinesis Client Library Consumer in Java
- Developing an Amazon Kinesis Client Library Consumer in Node.js
- Developing an Amazon Kinesis Client Library Consumer in .NET
- Developing an Amazon Kinesis Client Library Consumer in Python
- Developing an Amazon Kinesis Client Library Consumer in Ruby
Amazon Kinesis Client Library
The Amazon Kinesis Client Library (KCL) helps you consume and process data from an Amazon Kinesis stream. This type of application is also referred to as a consumer. The KCL takes care of many of the complex tasks associated with distributed computing, such as load-balancing across multiple instances, responding to instance failures, checkpointing processed records, and reacting to resharding. The KCL enables you to focus on writing record processing logic.
Note that the KCL is different from the Streams API that is available in the AWS SDKs. The Streams API helps you manage many aspects of Streams (including creating streams, resharding, and putting and getting records), while the KCL provides a layer of abstraction specifically for processing data in a consumer role. For information about the Streams API, see the Amazon Kinesis API Reference.
The KCL is a Java library; support for languages other than Java is provided using a multi-language interface called the MultiLangDaemon. This daemon is Java-based and runs in the background when you are using a KCL language other than Java. For example, if you install the KCL for Python and write your consumer app entirely in Python, you still need Java installed on your system because of the MultiLangDaemon. Further, MultiLangDaemon has some default settings you may need to customize for your use case, for example the AWS region it connects to. For more information about the MultiLangDaemon, go to the KCL MultiLangDaemon project page on GitHub.
At run time, a KCL application instantiates a worker with configuration information, and then uses a record processor to process the data received from an Amazon Kinesis stream. You can run a KCL application on any number of instances. Multiple instances of the same application coordinate on failures and load-balance dynamically. You can also have multiple KCL applications working on the same stream, subject to throughput limits.
Role of the KCL
The KCL acts as an intermediary between your record processing logic and Streams.
When you start a KCL application, it calls the KCL to instantiate a worker. This call provides the KCL with configuration information for the application, such as the stream name and AWS credentials.
The KCL performs the following tasks:
Connects to the stream
Enumerates the shards
Coordinates shard associations with other workers (if any)
Instantiates a record processor for every shard it manages
Pulls data records from the stream
Pushes the records to the corresponding record processor
Checkpoints processed records
Balances shard-worker associations when the worker instance count changes
Balances shard-worker associations when shards are split or merged