The Kafka Connect Kinesis Source Connector is used to pull data from Amazon
Kinesis and persist the data to an Apache Kafka® topic.
Examples
Streaming ETL Demo
To evaluate the Kafka Connect Kinesis source connector, AWS S3 sink connector,
Azure Blob sink connector, and GCP GCS sink connector in an end-to-end
streaming deployment, refer to the Cloud ETL demo on
GitHub. This demo also allows you to evaluate the real-time data processing
capabilities of ksqlDB.
Property-based example
This configuration is used typically along with standalone
workers.
name=KinesisSourceConnector1
connector.class=io.confluent.connect.kinesis.KinesisSourceConnector
tasks.max=1
aws.access.key.id=< Optional Configuration >
aws.secret.key.id=< Optional Configuration >
kafka.topic=< Required Configuration >
kinesis.stream=< Required Configuration >
kinesis.region=< Optional Configuration - defaults to US_EAST_1 >
confluent.topic.bootstrap.servers=localhost:9092
confluent.topic.replication.factor=1
REST-based example
This configuration is used typically along with distributed
workers. Write the following JSON to
connector.json, configure all of the required values, and use the command
below to post the configuration to one the distributed connect worker(s). Check
here for more information about the Kafka Connect REST
API
Connect distributed REST-based example:
{
"config" : {
"name" : "KinesisSourceConnector1",
"connector.class" : "io.confluent.connect.kinesis.KinesisSourceConnector",
"tasks.max" : "1",
"aws.access.key.id" : "< Optional Configuration >",
"aws.secret.key.id" : "< Optional Configuration >",
"kafka.topic" : "< Required Configuration >",
"kinesis.stream" : "< Required Configuration >"
}
}
Use curl to post the configuration to one of the Kafka Connect Workers. Change
http://localhost:8083/ the endpoint of one of your Kafka Connect worker(s).
Create a new connector:
curl -s -X POST -H 'Content-Type: application/json' --data @connector.json http://localhost:8083/connectors
Update an existing connector:
curl -s -X PUT -H 'Content-Type: application/json' --data @connector.json http://localhost:8083/connectors/KinesisSourceConnector1/config
Quick Start
The Kinesis connector is used to import data from Kinesis streams, and write
them into a Kafka topic. Before you begin, create a Kinesis stream and have a
user profile with read access to it.
Preliminary Setup
Navigate to your Confluent Platform installation directory and run this
command to install the latest connector version.
confluent-hub install confluentinc/kafka-connect-kinesis:latest
You can install a specific version by replacing latest with a version number.
For example:
confluent-hub install confluentinc/kafka-connect-kinesis:1.1.1-preview
Adding a new connector plugin requires restarting Connect. Use the Confluent CLI
to restart Connect.
Tip
The command syntax for the Confluent CLI development commands changed in 5.3.0.
These commands have been moved to confluent local. For example, the syntax for confluent start is now
confluent local services start. For more information, see confluent local.
confluent local services connect stop && confluent local services connect start
Your output should resemble:
Using CONFLUENT_CURRENT: /Users/username/Sandbox/confluent-snapshots/var/confluent.NuZHxXfq
Starting Zookeeper
Zookeeper is [UP]
Starting Kafka
Kafka is [UP]
Starting Schema Registry
Schema Registry is [UP]
Starting Kafka REST
Kafka REST is [UP]
Starting Connect
Connect is [UP]
Check if the Kinesis plugin has been installed correctly and picked up by the
plugin loader:
curl -sS localhost:8083/connector-plugins | jq .[].class | grep kinesis
"io.confluent.connect.kinesis.KinesisSourceConnector"
Kinesis Setup
You can use the AWS Management Console to set up your Kinesis stream,
or by completing the following steps:
Sign up for an AWS account.
Set up your AWS credentials.
Important
Be sure to set the following permissions in your AWS Kinesis policy:
"Action": [ "kinesis:DescribeStream", "kinesis:GetShardIterator", "kinesis:GetRecords" ]
Create a Kinesis stream.
aws kinesis create-stream --stream-name my_kinesis_stream --shard-count 1
Insert records
into your stream.
aws kinesis put-record --stream-name my_kinesis_stream --partition-key 123 --data test-message-1
The previous example shows that a record containing partition key 123 and
text test-message-1 is inserted into a stream, my_kinesis_stream.
Source Connector Configuration
Start the services using the Confluent CLI:
confluent local services start
Create a configuration file named kinesis-source-config.json with the following
contents.
{
"name": "kinesis-source",
"config": {
"connector.class": "io.confluent.connect.kinesis.KinesisSourceConnector",
"tasks.max": "1",
"kafka.topic": "kinesis_topic",
"kinesis.region": "US_WEST_1",
"kinesis.stream": "my_kinesis_stream",
"confluent.license": "",
"name": "kinesis-source",
"confluent.topic.bootstrap.servers": "localhost:9092",
"confluent.topic.replication.factor": "1"
}
}
The important configuration parameters used here are:
kinesis.stream.name: The Kinesis Stream to subscribe to.
kafka.topic: The Kafka topic in which the messages received from Kinesis are produced.
tasks.max: The maximum number of tasks that should be created for
this connector. Each Kinesis shard is allocated to a single
task. If the number of shards specified exceeds the number of tasks,
the connector throws an exception and fails.
kinesis.region: The region where the stream exists. Defaults to US_EAST_1 if not specified.
You may pass your AWS credentials to the Kinesis connector through
your source connector configuration. To pass AWS credentials in the
source configuration set the aws.access.key.id and the aws.secret.key.id: parameters.
"aws.acess.key.id":<your-access-key>
"aws.secret.key.id":<your-secret-key>
Run this command to start the Kinesis source connector.
Caution
You must include a double dash (--) between the topic name and your flag. For more information,
see this post.
confluent local services connect connector load source-kinesis --config source-kinesis-config.json
To check that the connector started successfully view the Connect
worker’s log by running:
confluent local services connect log
Start a Kafka Consumer in a separate terminal session to view the data exported by
the connector into the kafka topic
bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic kinesis_topic --from-beginning
Finally, stop the Confluent services using the command:
Remove unused resources
Delete your stream and clean up resources to avoid incurring any
unintended charges.
aws kinesis delete-stream --stream-name my_kinesis_stream
AWS Credentials
By default, the kinesis connector looks for kinesis credentials in the following
locations and in the following order:
The AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables accessible to the Connect worker processes where the connector will be deployed. These variables are recognized by the AWS CLI and all AWS SDKs (except for the AWS SDK for .NET). You use export to set these variables.
export AWS_ACCESS_KEY_ID=<your_access_key_id>
export AWS_SECRET_ACCESS_KEY=<your_secret_access_key>
The AWS_ACCESS_KEY and AWS_SECRET_KEY can be used instead, but are not recognized by the AWS CLI.
The aws.accessKeyId and aws.secretKey Java system properties on the Connect worker processes where the connector will be deployed. However, these variables are only recognized by the AWS SDK for Java and are not recommended.
The ~/.aws/credentials file located in the home directory of the operating system user that runs the Connect worker processes. These credentials are recognized by most AWS SDKs and the AWS CLI. Use the following AWS CLI command to create the credentials file:
You can also manually create the credentials file using a text editor. The file should contain lines in the following format:
[default]
aws_access_key_id = <your_access_key_id>
aws_secret_access_key = <your_secret_access_key>
Note
When creating the credentials file, make sure that the user creating the credentials file is the same user that runs the Connect worker processes and that the credentials file is in this user’s home directory. Otherwise, the kinesis connector will not be able to find the credentials.
See AWS Credentials File Format for additional details.
Choose one of the above to define the AWS credentials that the kinesis connectors use, verify the credentials implementation is set correctly, and then restart all of the Connect worker processes.
Note
Confluent recommends using either Environment variables or a Credentials file because these are the most straightforward, and they can be checked using the AWS CLI tool before running the connector.
All kinesis connectors run in a single Connect worker cluster and use the same credentials. This is sufficient for many use cases. If you want more control, refer to the following section to learn more about controlling and customizing how the kinesis connector gets AWS credentials.
Caution
If you configure one of the AWS key and AWS secret key implementations (as
detailed above), credentials can not also be supplied through the following
Credentials Providers or by using the Trusted Account
Credentials implementation. Attempting
to provide credentials using multiple implementations will cause
authentication failure.
Credentials Providers
A credentials provider is a Java class that implements the com.amazon.auth.AWSCredentialsProvider interface in the AWS Java library and returns AWS credentials from the environment. By default the kinesis connector configuration property kinesis.credentials.provider.class uses the com.amazon.auth.DefaultAWSCredentialsProviderChain class. This class and interface implementation chains together five other credential provider classes.
The com.amazonaws.auth.DefaultAWSCredentialsProviderChain implementation looks for credentials in the following order:
Environment variables using the com.amazonaws.auth.EnvironmentVariableCredentialsProvider class implementation. This implementation uses environment variables AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY. Environment variables AWS_ACCESS_KEY and AWS_SECRET_KEY are also supported by this implementation; however, these two variables are only recognized by the AWS SDK for Java and are not recommended.
Java system properties using the com.amazonaws.auth.SystemPropertiesCredentialsProvider class implementation. This implementation uses Java system properties aws.accessKeyId and aws.secretKey.
Credentials file using the com.amazonaws.auth.profile.ProfileCredentialsProvider class implementation. This implementation uses a credentials file located in the path ~/.aws/credentials. This credentials provider can be used by most AWS SDKs and the AWS CLI. Use the following AWS CLI command to create the credentials file:
You can also manually create the credentials file using a text editor. The file should contain lines in the following format:
[default]
aws_access_key_id = <your_access_key_id>
aws_secret_access_key = <your_secret_access_key>
Note
When creating the credentials file, make sure that the user creating the credentials file is the same user that runs the Connect worker processes and that the credentials file is in this user’s home directory. Otherwise, the Kinesis connector will not be able to find the credentials.
See AWS Credentials File Format for additional details.
Using Trusted Account Credentials
This connector can assume a role and use credentials from a separate trusted
account. This is a default feature provided with recent versions of this
connector that include an updated version of the AWS SDK.
After you create the trust relationship, an IAM user or an application from the trusted account can
use the AWS Security Token Service (AWS STS)
AssumeRole API operation. This operation provides temporary security credentials that enable
access to AWS resources for the connector. For details, see
Creating a Role to Delegate Permissions to an IAM User.
- Example:
Profile in ~/.aws/credentials:
[default]
role_arn=arn:aws:iam::037803949979:role/kinesis_cross_account_role
source_profile=staging
role_session_name = OPTIONAL_SESSION_NAME
[staging]
aws_access_key_id = <STAGING KEY>
aws_secret_access_key = <STAGING SECRET>
To allow the connector to assume a role with the right permissions, set the
Amazon Resource Name (ARN)
for this role. Additionally, you must choose between source_profile or credential_source
as the way to get credentials that have permission to assume the role, in the environment where the
connector is running.
Note
When setting up trusted account credentials, be aware that the approach of loading profiles from
both ~/.aws/credentials and ~/.aws/config does not work when configuring this connector.
Assumed role settings and credentials must be placed in the ~/.aws/credentials file.
Using Other Implementations
You can use a different credentials provider. To do this, set the kinesis.credentials.provider.class property to the name of any class that implements the com.amazon.auth.AWSCredentialsProvider interface.
Important
If you are using a different credentials provider, do not include the aws.acess.key.id and aws.secret.key.id in the connector configuration file. If these parameters are included, they will override the custom credentials provider class.
Complete the following steps to use a different credentials provider:
Find or create a Java credentials provider class that implements the com.amazon.auth.AWSCredentialsProvider interface.
Put the class file in a JAR file.
Place the JAR file in the share/java/kafka-connect-kinesis directory on all Connect workers.
Restart the Connect workers.
Change the kinesis connector property file to use your custom credentials. Add the provider class entry kinesis.credentials.provider.class=<className> in the kinesis connector properties file.
Important
You must use the fully qualified class name in the <className> entry.