InfluxDB 2 Sink Connector for Confluent Cloud

Note

This is a Quick Start for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see InfluxDB Sink Connector for Confluent Platform.

The fully-managed Kafka Connect InfluxDB 2 Sink connector writes data from an Apache Kafka® topic to an InfluxDB bucket.

Features

The InfluxDB 2 Sink connector supports the following features:

  • At least once delivery: This connector guarantees that records from the Kafka topic are delivered at least once.
  • Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.

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.

Record structure

Each record is in JSON format. It can contain a number of InfluxdDB fields, a tag section ("tags"), and a measurement section ("measurement"). The following example shows the record structure required for the connector.

{
 "measurement":"measurement-name",
  "tags": {
    "tag1":"value1",
    "tag2":"value2"
  },
 "time-field":<timestamp-in-epochs>,
 "field1":<value>,
 "field2":<value>,
 ...
}

Note the following:

  • The "tags" section is optional. This section provides the list of tags associated with the set of fields. Each tag must be a key-value pair of type string.
  • The "measurement" field takes the name of the InfluxDB measurement. This field is optional. However, if you do not provide the measurement name here then you must specify the measurement name in the measurement.name.format configuration property. Also, specifying this field will override whatever is specified in the Kafka record.
  • You can use multiple fields in a record. Fields can be of type int, float, boolean or string.
  • You can designate one of the fields to have the record timestamp information using the event.time.fieldname configuration property. If left unspecified, the timestamp used is the Kafka record timestamp.
  • For AVRO, PROTOBUF, and JSON_SR the structure remains the same. Note that the corresponding schema must be in Schema Registry.

Quick Start

Use this quick start to get up and running with the Confluent Cloud InfluxDB 2 Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to an InfluxDB bucket.

Prerequisites
  • Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).

  • The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.

  • Authorized access to write data to InfluxDB. For more information, see writing data to InfluxDB.

    Note

    The connector requires --read-bucket and --write-bucket permissions for the bucket where it sends data. For more information, see influx auth create.

  • Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

  • At least one source Kafka topic must exist in your Confluent Cloud cluster before creating the sink connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster.

See the Quick Start for Confluent Cloud for installation instructions.

Step 2: Add a connector.

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector.

Click the InfluxDB 2 Sink connector card.

InfluxDB 2 Sink Connector Card

Step 4: Enter the connector details.

Note

  • Make sure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

At the Add InfluxDB 2 Sink Connector screen, complete the following:

If you’ve already populated your Kafka topics, select the topic(s) you want to connect from the Topics list.

To create a new topic, click +Add new topic.

Step 5: Check for files.

Verify that data is being produced at the InfluxDB host.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

Using the Confluent CLI

To set up and run the connector using the Confluent CLI, complete the following steps.

Note

Make sure you have all your prerequisites completed.

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 InfluxDB2Sink

Example output:

The following are required configs:
connector.class : InfluxDB2Sink
topics
input.data.format
name
kafka.api.key
kafka.api.secret
influxdb.url
influxdb.token
influxdb.org.id
influxdb.bucket

Step 3: Create the connector configuration file.

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

{
  "connector.class": "InfluxDB2Sink",
  "topics": "orders",
  "input.data.format": "JSON",
  "name": "InfluxDB2Sink_0",
  "kafka.api.key": "****************",
  "kafka.api.secret": "*********************************",
  "influxdb.url": "http://influxdb-test.com:8086",
  "influxdb.token": "***************************",
  "influxdb.org.id": "<organization-id>",
  "influxdb.bucket": "<bucket-name>",
  "tasks.max": "1",
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.
  • "topics": Enter the topic name or a comma-separated list of topic names.
  • "input.data.format" (data coming from the Kafka topic): Supports AVRO, PROTOBUF, JSON_SR (JSON Schema), or JSON (schemaless). A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
  • "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 or KAFKA_API_KEY (the default). To use an API key and secret, specify the configuration properties kafka.api.key and kafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the property kafka.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
    
  • "influxdb.url": Fully-qualified InfluxDB API URL used for establishing a connection. For example, http://influxdb-test.com:8086

  • "influxdb.token": Token to authenticate with the InfluxDB host.

  • "influxdb.org.id": The InfluxDB organization ID.

    Note

    The connector requires --read-bucket and write-bucket permissions for the bucket where it sends data. For more information, see influx auth create.

    For more information, see writing data to InfluxDB.

  • "influxdb.bucket": The bucket where the connector sends data.

  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks may improve performance.

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 3: 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 influxdb2-sink-config.json

Example output:

Created connector InfluxDB2Sink_0 lcc-do6vzd

Step 4: 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   | InfluxDB2Sink_0           | RUNNING | sink |       |

Step 5: Check for files.

Verify that data is being produced at the InfluxDB 2 host.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

Configuration Properties

Use the following configuration properties with this connector.

Note

These are properties for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see InfluxDB Sink Connector for Confluent Platform.

Which topics do you want to get data from?

topics

Identifies the topic name or a comma-separated list of topic names.

  • Type: list
  • Importance: high

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, or plain JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.

  • Type: string
  • Importance: high

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

InfluxDB

influxdb.url

Fully qualified InfluxDB API URL used for establishing connection.

  • Type: string
  • Importance: high
influxdb.token

Token to authenticate with influx db.

  • Type: password
  • Importance: high
influxdb.org.id

Organization ID.

  • Type: string
  • Importance: high

Write Configuration

influxdb.bucket

Bucket to which this connector will send the data to

  • Type: string
  • Importance: high
write.precision

Write precision of InfluxDB timestamp. Valid values are Seconds, Milliseconds, Microseconds, and Nanoseconds. Note that if the kafka record timestamp is used, instead of specifying a timestamp field, using ‘event.time.fieldname’, then the kafka timestamp(in Milliseconds) will be converted the precision defined here. Otherwise you must provide the correct time unit of the ‘event.time.fieldname’ here.

  • Type: string
  • Default: Milliseconds
  • Importance: medium
event.time.fieldname

The name of field in the Kafka record that contains the event time to be written to an InfluxDB data point. By default (if this config is unspecified), the timestamp written to InfluxDB is the Kafka record timestamp (when the Kafka record was created) which corresponds to the time that the event was processed.

  • Type: string
  • Importance: medium
measurement.name.format

A format string for the destination measurement name, which may contain ‘${topic}’ as a placeholder for the originating topic name.

For example, kafka_${topic} for the topic ‘orders’ will map to the measurement name ‘kafka_orders’. If the measurement name format is not provided the connector will use the ‘measurement’ field value present in the kafka message. If such a field is not present in the message the message will be sent to the dlq.

  • Type: string
  • Importance: medium
influxdb.gzip.enable

Flag to determine if gzip should be enabled.

  • Type: boolean
  • Default: false
  • Importance: low

Retries

retry.backoff.ms

Backoff time duration to wait before retrying

  • Type: int
  • Default: 1000 (1 second)
  • Importance: medium
max.retries

The maximum number of times to retry on errors before failing the task.

  • Type: int
  • Default: 10
  • Importance: medium

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.

../_images/topology.png