Amazon CloudWatch Logs Source Connector for Confluent Cloud¶
Note
If you are installing the connector locally for Confluent Platform, see Amazon CloudWatch Logs Source Connector for Confluent Platform.
The Kafka Connect Amazon CloudWatch Logs Source connector for Confluent Cloud imports
data from Amazon CloudWatch Logs,
and then writes the data into an Apache Kafka® topic. The connector sources data from
a single log group and can write to one topic per log stream. There is a Kafka
topic format property (CLI property kafka.topic.format
) you can use to
customize the topic names for each log stream.
The connector can start at one task to support all import data and can scale up to one task per log stream. One task per log stream raises the performance up to the greatest number of log streams that Amazon supports (100,000 logs per second or 10 MB per second).
Features¶
The Amazon CloudWatch Logs Source connector provides the following features:
- At least once delivery: The connector guarantees that records are delivered at least once to the Kafka topic.
- Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance. The connector can start at one task to support all import data and can scale up to one task per log stream. One task per log stream raises the performance up to the greatest number of log streams that Amazon supports (100,000 logs per second or 10 MB per second).
- Customize topic format: The connector sources data from a single log group and can write to one topic per log stream. There is a Kafka topic format property (CLI property
kafka.topic.format
) you can use to customize the topic names for each log stream. - Supported data formats: The connector supports Avro, JSON Schema (JSON-SR), and JSON (schemaless) output formats. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro and JSON Schema). See Environment Limitations for additional information.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.
Limitations¶
Be sure to review the following information.
- For connector limitations, see Amazon CloudWatch Logs Source Connector limitations.
- If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
- If you plan to use Confluent Cloud Schema Registry, see Environment Limitations.
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud Amazon CloudWatch Logs Source connector. The quick start provides the basics of selecting the connector and configuring it to stream events.
- Prerequisites
Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS).
The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
For networking considerations, see Networking and DNS Considerations. To use static egress IPs, see Static Egress IP Addresses.
An AWS account configured with Access Keys. You use these access keys when setting up the connector. Note the IAM identity must have the following minimum permissions (IAM policies):
logs:GetLogEvents
logs:DescribeLogStreams
For details, see Using identity-based policies (IAM policies) for CloudWatch Logs.
Amazon CloudWatch connection details. For more information, see log groups and log streams.
Using the Confluent Cloud Console¶
Step 1: Launch your Confluent Cloud cluster.¶
See the Quick Start for Apache Kafka using Confluent Cloud for installation instructions.
Step 2: Add a connector.¶
In the left navigation menu, click Data integration, and then click Connectors. If you already have connectors in your cluster, click + Add connector.
Step 4: Set up the connection.¶
Note
- Make sure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
- Enter a connector Name.
- Select the way you want to provide Kafka Cluster credentials. You can either select a service account resource ID or you can enter an API key and secret (or generate these in the Cloud Console).
- Enter the Kafka Topic Format. Topic format to use for generating the names of the Kafka topics. This format string can contain
${log-group}
and${log-stream}
as a placeholder for the original log group and log stream names. For example,confluent.${log-group}.${log-stream}
for the log grouplog-group-1
and log streamlog-stream-1
maps to the topic nameconfluent.log-group-1.log-stream-1
. - Select the Output Kafka record value format (data going to the Kafka topic): AVRO, JSON_SR (JSON Schema), or JSON (schemaless). Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro and JSON_SR). See Environment Limitations for additional information.
- Enter your AWS credentials. For information about how to set these up, see Access Keys.
- Enter the Amazon CloudWatch connection details:
- CloudWatch Logs Endpoint URL: For example,
https://logs.us-east-1.amazonaws.com
. For additional information, see Amazon CloudWatch Logs endpoints and quotas. - CloudWatch Logs Group Name: Name of the log group on Amazon CloudWatch where the log streams are contained.
- CloudWatch Log Stream Name(s): List of the log stream(s) on Amazon CloudWatch where you want to track log records. If the field is left empty, all log streams under the log group are tracked.
- AWS Poll Interval in Milliseconds: Time in milliseconds (ms) the connector waits between polling the endpoint for updates. The default value is
1000
ms (1 second).
- CloudWatch Logs Endpoint URL: For example,
- Enter the number of tasks to use with the connector. The connector supports running one or more tasks. The connector can start at one task to support all import data and can scale up to one task per log stream. One task per log stream can raise the performance, up to the greatest number of log streams that Amazon supports (100,000 logs per second or 10 MB per second).
- Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.
See Configuration Properties for all property values and descriptions.
Step 6: Check the connector status.¶
The status for the connector should go from Provisioning to Running.
Step 7: Check for records.¶
Verify that records are being produced at the Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.
Using the Confluent CLI¶
Complete the following steps to set up and run the connector using the Confluent CLI.
Note
- Make sure you have all your prerequisites completed.
- The example commands use Confluent CLI version 2. For more information see, Confluent CLI v2.
Step 1: List the available connectors.¶
Enter the following command to list available connectors:
confluent connect plugin list
Step 2: Show the required connector configuration properties.¶
Enter the following command to show the required connector properties:
confluent connect plugin describe <connector-catalog-name>
For example:
confluent connect plugin describe CloudWatchLogsSource
Example output:
Following are the required configs:
connector.class: CloudWatchLogsSource
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
output.data.format
aws.access.key.id
aws.secret.access.key
aws.cloudwatch.logs.url
aws.cloudwatch.log.group
tasks.max
Step 3: Create the connector configuration file.¶
Create a JSON file that contains the connector configuration properties. The
following entry shows a typical connector configuration. When launched, the
connector consumes data from streams stream-1
and stream-2
of log group
cloudwatch-group
. It produces the data to Kafka topic
logs.cloudwatch-group.stream-1
and topic logs.cloudwatch-group.stream-2
.
{
"name": "CloudWatchLogsSourceConnector_0",
"config": {
"connector.class": "CloudWatchLogsSource",
"name": "CloudWatchLogsSourceConnector_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key>",
"kafka.api.secret": "<my-kafka-api-secret>",
"kafka.topic.format": "logs.${log-group}.${log-stream}",
"output.data.format": "JSON",
"aws.access.key.id": "<INSERT AWS API KEY>",
"aws.secret.access.key": "<INSERT AWS API SECRET>",
"aws.cloudwatch.logs.url": "https://logs.us-east-1.amazonaws.com",
"aws.cloudwatch.log.group": "cloudwatch-group",
"aws.cloudwatch.log.streams": "stream-1, stream-2",
"aws.poll.interval.ms": "1500",
"tasks.max": "1"
}
}
Note the following property definitions:
"connector.class"
: Identifies the connector plugin name."name"
: Sets a name for your new connector.
"kafka.auth.mode"
: Identifies the connector authentication mode you want to use. There are two options:SERVICE_ACCOUNT
orKAFKA_API_KEY
(the default). To use an API key and secret, specify the configuration propertieskafka.api.key
andkafka.api.secret
, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.service.account.id=<service-account-resource-ID>
. To list the available service account resource IDs, use the following command:confluent iam service-account list
For example:
confluent iam service-account list Id | Resource ID | Name | Description +---------+-------------+-------------------+------------------- 123456 | sa-l1r23m | sa-1 | Service account 1 789101 | sa-l4d56p | sa-2 | Service account 2
"kafka.topic.format"
: Topic format to use for generating the names of the Kafka topics. This format string can contain${log-group}
and${log-stream}
as a placeholder for the original log group and log stream names. For example,confluent.${log-group}.${log-stream}
for the log grouplog-group-1
and log streamlog-stream-1
maps to the topic nameconfluent.log-group-1.log-stream-1
."output.data.format"
: Enter an output data format (data going to the Kafka topic): AVRO, JSON_SR (JSON Schema), or JSON (schemaless). Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro and JSON_SR). See Environment Limitations for additional information."aws.access.key.id"
and"aws.secret.access.key"
: Enter the AWS Access Key ID and Secret. For information about how to set these up, see Access Keys."aws.cloudwatch.logs.url"
: For example,https://logs.us-east-1.amazonaws.com
. For additional information, see Amazon CloudWatch Logs endpoints and quotas."aws.cloudwatch.log.group"
: Name of the log group on Amazon CloudWatch where the log streams are contained."aws.cloudwatch.log.streams"
: List of the log stream(s) on Amazon CloudWatch where you want to track log records. If the property is not used, all log streams under the log group are tracked."aws.poll.interval.ms"
: Time in milliseconds (ms) the connector waits between polling the endpoint for updates. The default value is1000
ms (1 second)."tasks.max"
: Enter the number of tasks to use with the connector. The connector supports running one or more tasks. The connector can start at one task to support all import data and can scale up to one task per log stream. One task per log stream can raise the performance, up to the greatest number of log streams that Amazon supports (100,000 logs per second or 10 MB per second).
Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.
See Configuration Properties for all property values and descriptions.
Step 4: Load the properties file and create the connector.¶
Enter the following command to load the configuration and start the connector:
confluent connect create --config <file-name>.json
For example:
confluent connect create --config cloudwatch-logs-source-config.json
Example output:
Created connector CloudWatchLogsSourceConnector_0 lcc-do6vzd
Step 5: Check the connector status.¶
Enter the following command to check the connector status:
confluent connect list
Example output:
ID | Name | Status | Type | Trace
+------------+----------------------------- --+---------+--------+-------+
lcc-do6vzd | CloudWatchLogsSourceConnector_0 | RUNNING | source | |
Step 6: Check for records.¶
Verify that records are being produced at the Kafka topics logs.cloudwatch-group.stream-1
and logs.cloudwatch-group.stream-2
.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.
Configuration Properties¶
Use the following configuration properties with this connector.
How should we connect to your data?¶
name
Sets a name for your connector.
- Type: string
- Valid Values: A string at most 64 characters long
- Importance: high
Kafka Cluster credentials¶
kafka.auth.mode
Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.
- Type: string
- Default: KAFKA_API_KEY
- Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
- Importance: high
kafka.api.key
- Type: password
- Importance: high
kafka.service.account.id
The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
- Type: string
- Importance: high
kafka.api.secret
- Type: password
- Importance: high
How do you want to define topic names?¶
kafka.topic.format
Topic format to use for generating the names of the Apache Kafka® topics to publish data to. This format string can contain ${log-group} and ${log-stream} as a placeholder for the original log group and log stream names.
- Type: string
- Default: ${log-group}.${log-stream}
- Importance: high
Output messages¶
output.data.format
Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO and JSON_SR.
- Type: string
- Importance: high
AWS Credentials¶
aws.access.key.id
The Amazon Access Key used to connect to Amazon CloudWatch.
- Type: password
- Importance: high
aws.secret.access.key
The Amazon Secret Key used to connect to Amazon CloudWatch.
- Type: password
- Importance: high
How should we connect to Amazon CloudWatch Logs?¶
aws.cloudwatch.logs.url
The URL to use as the endpoint for connecting to Amazon CloudWatch for Logs. For example, https://logs.us-east-1.amazonaws.com.
- Type: string
- Importance: high
CloudWatch Logs details¶
aws.cloudwatch.log.group
Name of the log group on Amazon CloudWatch under which the desired log streams are contained.
- Type: string
- Importance: high
aws.cloudwatch.log.streams
List of the log stream(s) on Amazon CloudWatch under which the desired log records are sent through. If the field is left empty, all log streams under the log group will be tracked.
- Type: list
- Importance: high
aws.poll.interval.ms
Time in milliseconds to wait between two consecutive polls to the Amazon CloudWatch endpoint.
- Type: int
- Default: 1000 (1 second)
- Valid Values: [0,…]
- Importance: high
Number of tasks for this connector¶
tasks.max
- Type: int
- Valid Values: [1,…]
- Importance: high
Next Steps¶
See also
For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.