Delivering data from Yandex Managed Service for Apache Kafka® using Yandex Data Transfer

Written by

Yandex Cloud

Updated at September 25, 2025

Required paid resources
Getting started
Create a target stream in Data Streams
Set up and activate the transfer
Test the transfer
Delete the resources you created

A stream in Data Streams can receive data from Apache Kafka® topics in real time.

To run data delivery:

If you no longer need the resources you created, delete them.

Required paid resources

The support cost includes:

Managed Service for Apache Kafka® cluster fee: Covers the use of computational resources allocated to hosts (including ZooKeeper hosts) and disk storage (see Apache Kafka® pricing).
Fee for public IP addresses if public access is enabled for cluster hosts (see Virtual Private Cloud pricing).
Managed Service for YDB database fee. The charge depends on the usage mode:
- For the serverless mode, you pay for data operations and the amount of stored data.
- For the dedicated instance mode, you pay for the use of computing resources, dedicated DBs, and disk space.
Learn more about the Managed Service for YDB pricing plans here.
Data Streams fee, which depends on the pricing mode:
- Provisioned capacity pricing mode: You pay for the number of write units and resources allocated for data streaming.
- On-demand pricing mode:
  - If the DB operates in serverless mode, the data stream is charged according to the YDB serverless mode pricing policy.
  - If the DB operates in dedicated instance mode, the data stream is not charged separately (you only pay for the DB, see the pricing policy).
Learn more about the Data Streams pricing plans here.

Getting started

Set up your data pipeline infrastructure:
Manually

Terraform
1. Create a Managed Service for Apache Kafka® source cluster with any suitable configuration.
2. Create a Managed Service for YDB database in any suitable configuration.
3. In the source cluster, create a topic named sensors.
4. In the source cluster, create a user with the ACCESS_ROLE_PRODUCER and ACCESS_ROLE_CONSUMER permissions for the new topic.
1. If you do not have Terraform yet, install it.
2. Get the authentication credentials. You can add them to environment variables or specify them later in the provider configuration file.
3. Configure and initialize a provider. There is no need to create a provider configuration file manually, you can download it.
4. Place the configuration file in a separate working directory and specify the parameter values. If you did not add the authentication credentials to environment variables, specify them in the configuration file.
5. Download the data-transfer-mkf-ydb.tf configuration file to the same working directory.
  
  This file describes:
  - Network.
  - Subnet.
  - Security group and the rule required to connect to a Managed Service for Apache Kafka® cluster.
  - Managed Service for Apache Kafka® source cluster.
  - Apache Kafka® topic.
  - Apache Kafka® user.
  - Managed Service for YDB database.
  - Transfer.
6. In the data-transfer-mkf-ydb.tf file, specify these variables:
  - source_kf_version: Apache Kafka® version in the source cluster.
  - source_user_name: Username for connection to the Apache Kafka® topic.
  - source_user_password: User password.
  - target_db_name: Managed Service for YDB database name.
  - transfer_enabled: Set to 0 to ensure that no transfer is created until you create endpoints manually.
7. Make sure the Terraform configuration files are correct using this command:
  terraform validate
  Terraform will display any configuration errors detected in your files.
8. Create the required infrastructure:
  1. Run this command to view the planned changes:
    
    terraform plan
    
    If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.
  2. If everything looks correct, apply the changes:
    
    Run this command:
    
    terraform apply
    
    Confirm updating the resources.
    
    Wait for the operation to complete.
  All the required resources will be created in the specified folder. You can check resource availability and their settings in the management console.
The source cluster's new Apache Kafka® topic, sensors, will receive test data from car sensors in JSON format:
```
{
    "device_id":"iv9a94th6rzt********",
    "datetime":"2020-06-05 17:27:00",
    "latitude":"55.70329032",
    "longitude":"37.65472196",
    "altitude":"427.5",
    "speed":"0",
    "battery_voltage":"23.5",
    "cabin_temperature":"17",
    "fuel_level":null
}
```
Install these tools:
- kafkacat: For reading from and writing to Apache Kafka® topics.
```
sudo apt update && sudo apt install --yes kafkacat
```
  Make sure you can use it to connect to the Managed Service for Apache Kafka® source cluster over SSL.
- jq for stream processing of JSON files.
```
sudo apt update && sudo apt-get install --yes jq
```

Create a target stream in Data Streams

Create a target stream in Data Streams for a Managed Service for YDB database.

Set up and activate the transfer

Create an Apache Kafka® source endpoint:

Endpoint parameters:

Connection type: Managed Service for Apache Kafka cluster

Select a source cluster from the list and specify its connection settings.

Advanced settings → Conversion rules

Conversion rules: json

Data scheme: You can specify a schema in two ways:

Field list

Set a list of topic fields manually:

Name	Type	Key
`device_id`	`STRING`	Yes
`datetime`	`STRING`
`latitude`	`DOUBLE`
`longitude`	`DOUBLE`
`altitude`	`DOUBLE`
`speed`	`DOUBLE`
`battery_voltage`	`DOUBLE`
`cabin_temperature`	`UINT16`
`fuel_level`	`UINT16`

JSON specification

Create and upload a data schema file in JSON format, json_schema.json:

json_schema.json

[
    {
        "name": "device_id",
        "type": "string",
        "key": true
    },
    {
        "name": "datetime",
        "type": "string"
    },
    {
        "name": "latitude",
        "type": "double"
    },
    {
        "name": "longitude",
        "type": "double"
    },
    {
        "name": "altitude",
        "type": "double"
    },
    {
        "name": "speed",
        "type": "double"
    },
    {
        "name": "battery_voltage",
        "type": "double"
    },
    {
        "name": "cabin_temperature",
        "type": "uint16"
    },
    {
        "name": "fuel_level",
        "type": "uint16"
    }
]

Create an endpoint for the Yandex Data Streams target:

Connection settings:
- Database: Select the Managed Service for YDB database from the list.
- Stream: Specify the name of the stream in Data Streams.
- Service account ID: Select or create a service account with the yds.editor role.
Create a transfer:
Manually

Terraform
1. Create a transfer of the Replication type that will use the created endpoints.
  
  If you want to transform data during the transfer, specify the relevant transformers in the transfer settings:
2. Activate the transfer.
1. In the data-transfer-mkf-ydb.tf file, specify these variables:
  - source_endpoint_id: ID of the source endpoint.
  - target_endpoint_id: ID of the target endpoint.
  - transfer_enabled: Set to 1 to create a transfer.
2. If you want to transform data during the transfer, add the transformation section with a list of the transformers you need to the yandex_datatransfer_transfer resource:
  resource "yandex_datatransfer_transfer" "mkf-ydb-transfer" { ... transformation { transformers{ <transformer_1> } transformers{ <transformer_2> } ... transformers{ <transformer_N> } } }
  The following transformer types are available:
  For more information on configuring transformers, see this Terraform provider article.
3. Validate your Terraform configuration files using this command:
  terraform validate
  Terraform will display any configuration errors detected in your files.
4. Create the required infrastructure:
  1. Run this command to view the planned changes:
    
    terraform plan
    
    If you described the configuration correctly, the terminal will display a list of the resources to update and their parameters. This is a verification step that does not apply changes to your resources.
  2. If everything looks correct, apply the changes:
    
    Run this command:
    
    terraform apply
    
    Confirm updating the resources.
    
    Wait for the operation to complete.
  The transfer will activate automatically upon creation.

Test the transfer

Wait for the transfer status to change to Replicating.

Make sure the data from the topic in the Managed Service for Apache Kafka® source cluster moves to the specified stream in Data Streams:

Create a file named sample.json with test data:

{
    "device_id": "iv9a94th6rzt********",
    "datetime": "2020-06-05 17:27:00",
    "latitude": 55.70329032,
    "longitude": 37.65472196,
    "altitude": 427.5,
    "speed": 0,
    "battery_voltage": 23.5,
    "cabin_temperature": 17,
    "fuel_level": null
}

{
    "device_id": "rhibbh3y08qm********",
    "datetime": "2020-06-06 09:49:54",
    "latitude": 55.71294467,
    "longitude": 37.66542005,
    "altitude": 429.13,
    "speed": 55.5,
    "battery_voltage": null,
    "cabin_temperature": 18,
    "fuel_level": 32
}

{
    "device_id": "iv9a94th6r********",
    "datetime": "2020-06-07 15:00:10",
    "latitude": 55.70985913,
    "longitude": 37.62141918,
    "altitude": 417.0,
    "speed": 15.7,
    "battery_voltage": 10.3,
    "cabin_temperature": 17,
    "fuel_level": null
}

Send data from sample.json to the Managed Service for Apache Kafka® sensors topic using jq and kafkacat:

jq -rc . sample.json | kafkacat -P \
   -b <broker_host_FQDN>:9091 \
   -t sensors \
   -k key \
   -X security.protocol=SASL_SSL \
   -X sasl.mechanisms=SCRAM-SHA-512 \
   -X sasl.username="<username_in_source_cluster>" \
   -X sasl.password="<user_password_in_source_cluster>" \
   -X ssl.ca.location=/usr/local/share/ca-certificates/Yandex/YandexInternalRootCA.crt -Z

The data is sent on behalf of the created user. To learn more about setting up an SSL certificate and using kafkacat, see Connecting to a Apache Kafka® cluster from applications.

Make sure the data from the source has been moved to the Data Streams stream:

Management console

AWS CLI

In the management console, select Data Streams.
Select the target stream from the list and navigate to Data viewer.
Make sure shard-000000 now contains messages with the source table rows. For a closer look at the messages, click .

Install the AWS CLI.
Configure the environment for Data Streams.
Read the stream data using:
- AWS CLI.
- AWS SDK.

Delete the resources you created

Note

Before deleting the resources, deactivate the transfer.

Some resources incur charges. To avoid unnecessary charges, delete the resources you no longer need:

Delete the transfer.
Delete the source and target endpoints.
If you created a service account when creating the target endpoint, delete it.

Delete other resources using the method matching their creation method:

Manually

Terraform

In the terminal window, go to the directory containing the infrastructure plan.

Warning

Make sure the directory has no Terraform manifests with the resources you want to keep. Terraform deletes all resources that were created using the manifests in the current directory.
Delete resources:
1. Run this command:
```
terraform destroy
```
2. Confirm deleting the resources and wait for the operation to complete.
All the resources described in the Terraform manifests will be deleted.

Delivering data from Yandex Managed Service for Apache Kafka® using Yandex Data Transfer

Required paid resourcesRequired paid resources

Getting startedGetting started

Create a target stream in Data StreamsCreate a target stream in Data Streams

Set up and activate the transferSet up and activate the transfer

Test the transferTest the transfer

Delete the resources you createdDelete the resources you created