HTTP Sink V2 Connector for Confluent Cloud¶
The fully-managed HTTP Sink V2 connector for Confluent Cloud integrates Apache Kafka® with an API using HTTP or HTTPS. It allows you to configure one or more APIs seamlessly with an OpenAPI/Swagger specification file, reducing overall configuration time and helping you achieve better performance when compared to the HTTP Sink Connector for Confluent Cloud. In this page, you will find all the features the HTTP Sink V2 connector offers and discover everything you need to begin using the connector.
Note
If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.
Features¶
The HTTP Sink V2 connector includes the following features:
Multiple API path support: The connector allows you to configure up to 15 API paths having the same base URL and authentication mechanism.
OpenAPI Specification-based configuration: The connector provides seamless configuration through an OpenAPI specification file.
Secure access and data exchange: The connector supports the following authentication mechanisms:
- Basic
- Bearer
- OAuth 2.0 Client Credentials grant flow
Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the Manage CSFLE for connectors.
API error reporting management: You can configure the connector to notify you when an API error occurs through email or through the Confluent Cloud user interface. You also can configure the connector to ignore when an API error occurs.
API validation: The connector allows you to test the API using a test record and view the test API response logs in the Confluent Cloud user interface.
Template variables: The connector allows you to specify template variables, such as
${topic}
and${key}
, along with fields from the Kafka record for use in an HTTP request:- Headers
- Query parameters
- Path parameters
- Body parameters
The connector constructs a unique URL using these parameters and enables substitution of template variables in headers, parameters, and body content.
Supported data formats: The connector supports Avro, Bytes, JSON (schemaless), JSON Schema, and Protobuf data formats. Schema Registry must be enabled to use a Schema Registry-based format like Avro, JSON Schema, or Protobuf. For additional information, see Schema Registry Enabled Environments.
Custom offset support: The connector allows you to configure custom offsets using the Confluent Cloud user interface to prevent data loss and data duplication.
Configurable retry functionality: The connector allows you to customize retry settings based on your requirements.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Manage CSFLE¶
If you plan to enable CSFLE for the HTTP Sink V2 connector, take care of the following sensitive information that may get written to your Kafka topics:
Warning
- Error topic: The error topic may include sensitive data from the API response.
- Success topic: The success topic may include sensitive data from the API response.
Limitations¶
Be sure to review the following information.
- For connector limitations, see HTTP Sink V2 Connector limitations.
- If you plan to use one or more Single Message Transformations (SMTs), see SMT Limitations.
- If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud HTTP Sink V2 connector.
- Prerequisites
- Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud).
- The Confluent CLI installed and configured for the cluster. For help, see Install the Confluent CLI.
- Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). For more information, see Schema Registry Enabled Environments.
- OpenAPI Specification file version 3.0.
- Relevant authentication credentials for both Kafka and your data system.
- 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 4: Enter the connector details¶
Note
- Ensure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
At the Add HTTP Sink V2 Connector screen, complete the following:
Enter the following details:
- Provide the connector name in the Connector name field.
- Add the OpenAPI specification file (OAS 3.0 or higher) by adding a URL
endpoint or by uploading a YAML/JSON formatted specification file. Note
that you can convert Swagger 1.x or 2.0 definitions to OpenAPI 3.0
using the Swagger Converter.
- To add a URL endpoint, enter the URL in the Add via URL field. Note that the maximum file size is 3 MB.
- To upload a YAML/JSON formatted specification file, select Add a file, then click Upload file to upload the file. Note that the maximum file size is 1 MB.
- Select the Input Kafka record value format (data coming from the Kafka topic): AVRO, BYTES, JSON, JSON_SR (JSON Schema), or PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON Schema, or Protobuf). For more information, see Schema Registry Enabled Environments. Note that to consume STRING data, select schemaless JSON.
- Select the way you want to provide Kafka Cluster credentials. You can
choose one of the following options:
- My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.
- Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.
- Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.
- Click Continue.
Server connection.
- Enter your API Base URL in the URL field. The HTTP API Base URL.
For example:
http://example.com/absenceManagement/v1
.
Authentication.
Enter the following authentication details to use for the server connection. Note that you can change the authentication type of the endpoint by clicking Change method. Supported methods are:
The connector authenticates with a username and password. If you select Basic, enter the following details:
- Username: The username to be used with an endpoint requiring authentication.
- Password: The password to be used with an endpoint requiring authentication.`
Enter the following details:
- Bearer token: The bearer authentication token to be used with an endpoint requiring bearer token-based authentication.
This is the default. The endpoint requires no authentication.
Client Credentials grant flow
The connector authenticates using OAuth credentials. Enter the following details:
- Client ID: The client ID used when fetching the OAuth2 token.
- Client secret: The secret used when fetching the OAuth2 token.
- Client authentication mode: Specifies how to encode the Client
ID and Client Secret in the OAuth2 authorization request. If set to
header
, the credentials are encoded as an'Authorization: Basic <base-64 encoded client_id:client_secret>'
HTTP header. If set tourl
, then Client ID and Client Secret are sent as URL encoded parameters. - Scope: The scope parameter sent when fetching the OAuth2 token.
- Token property name: The name of the property containing the
OAuth2 token returned by the OAuth2 token URL. Defaults to
access_token
. - Token server URL: The URL to be used for fetching the OAuth2 token.
(Optional) To customize SSL for your HTTP URL, enable Customize SSL and configure the following SSL settings accordingly:
- SSL Protocol: Enter the protocol to use for SSL connections.
- Key store: Upload the key store file containing the server certificate.
- Key store password: Enter the password used to access the key store.
- Key password: Enter the password for the private key in the key store file.
- Trust store: Upload the trust store file containing a server CA certificate.
- Trust store password: Enter the trust store password containing a server CA certificate.
Click Authenticate. Follow the authentication steps. If successful, you should see a message similar to “Authenticated successfully”.
- Select one or more endpoint paths for connector requests. You can
select up to 15 paths. Add any resource IDs or sub-resource IDs as
needed for the API endpoint path. The connector supports
GET
,POST
,PUT
, andPATCH
operations. - Click Continue.
On the Configuration page, configure the following.
Select topics
Choose the topic(s) you want to get data from. After selecting the desired topic(s), click on the Request configuration tab.
- Under Path variables, configure the HTTP path parameters to
be added to the request. Parameter values can be templated with
different template values like
${key}
,${topic}
, or other field references from the Kafka record. - Under Query parameters, configure the HTTP parameters to be added to the request.
- Under Headers, configure the HTTP headers to be included in each request.
- In the Body field, enter the payload to be sent along with the HTTP request. By default, the sink record will be formatted as is and sent as a body. If the body field is configured, then the sink record will be mapped to the configured body after appropriate template substitutions, if applicable. This configuration will be useful if you need to convert the sink record to a different format than the original.
- Click on the Settings tab.
For Behavior for null valued records, select how to handle records with a non-null key and a null value (that is–Kafka tombstone records). Valid options are
IGNORE
,DELETE
andFAIL
. Defaults toIGNORE
.(Optional) Add additional settings, by clicking Show additional settings.
(Optional) Configure the following advanced configurations:
Advanced configurations
Schema context
Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.
Error configurations
Behavior on errors: Select the error handling behavior setting for handling error responses from HTTP requests. Valid options are
Fail connector
andIgnore errors
. This defaults toFail connector
which is recommended.Error record format: Dictates the content of records produced to the error topic. If set to
Error string
the value is a human readable string describing the failure. The value will include some or all of the following information if available: http response code, reason phrase, submitted payload, URL, response content, exception and error message. If set tohttp_response
, the value would be the plain response content for a failed record.
Consumer configurations
Max poll interval(ms): The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to
300000
milliseconds (5 minutes). milliseconds (5 minutes). The minimum and maximum values allowed are60000
(1 minute) and1800000
(30 minutes), respectively.Max poll records: The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to
500
records. The minimum and maximum values allowed are1
and500
, respectively.
Data decryption
Enable Client-Side Field Level Encryption for data decryption. Specify a Service Account to access the Schema Registry and associated encryption rules or keys with that schema. Select the connector behavior (
ERROR
orNONE
) on data decryption failure. If set toERROR
, the connector fails and writes the encrypted data in the DLQ. If set toNONE
, the connector writes the encrypted data in the target system without decryption. For more information on CSFLE setup, see Manage CSFLE for connectors.
Procession position
Define a specific offset position for this connector to being processing from. If adding a new offset manually, refer to Sink connectors.
For all property values and definitions, see Configuration Properties.
(Optional) If you wish to test the API, click on the Test tab and follow the instructions. Else, continue to the next step.
Click Continue.
200 OK
response. Click
Close. For more help with using the Test API, see the
Test API section.- To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field. Note that the number of tasks should be greater than or equal to the number of HTTP APIs you configured.
- Click Continue.
Verify the connection details.
Click Launch connector.
The status for the connector should go from Provisioning to Running.
Step 5: Check for records¶
Verify that records are being produced at the endpoint.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Note that Dead Letter Queue (DLQ), success, and error topics are automatically created for the connector. For more details, see View Connector Dead Letter Queue Errors in Confluent Cloud.
Using the Confluent CLI¶
To set up and run the connector using the Confluent CLI, complete the following steps, but ensure you have met all prerequisites.
Step 1: List the available connectors¶
Enter the following command to list available connectors:
confluent connect plugin list
Step 2: List the connector configuration properties¶
Enter the following command to show the connector configuration properties:
confluent connect plugin describe <connector-plugin-name>
The command output shows the required and optional configuration properties.
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.
{
"topics": "topic_0",
"schema.context.name": "default",
"value.subject.name.strategy": "TopicNameStrategy",
"input.data.format": "AVRO",
"connector.class": "HttpSinkV2",
"name": "HttpSinkV2Connector_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key>",
"kafka.api.secret": "<my-kafka-api-secret>",
"max.poll.interval.ms": "300000",
"max.poll.records": "500",
"tasks.max": "1",
"http.api.base.url": "http://example.com/absenceManagement/v1",
"auth.type": "NONE",
"https.ssl.enabled": "false",
"https.host.verifier.enabled": "true",
"behavior.on.error": "FAIL",
"apis.num": "1",
"api1.http.request.method": "POST",
"api1.http.connect.timeout.ms": "30000",
"api1.http.request.timeout.ms": "30000",
"api1.behavior.on.null.values": "IGNORE",
"api1.max.retries": "5",
"api1.request.body.format": "JSON",
"api1.retry.backoff.policy": "EXPONENTIAL_WITH_JITTER",
"api1.max.batch.size": "1",
"api1.retry.backoff.ms": "3000",
"api1.retry.on.status.codes": "400-",
"api1.http.request.headers.separator": "|",
"api1.http.request.parameters.separator": "&",
"api1.batch.separator": ",",
"api1.batch.json.as.array": "false",
"api1.http.path.parameters.separator": "|",
"api1.test.api": "false",
"api1.allow.get.request.body": "false",
}
Note the following property definitions:
"connector.class"
: Identifies the connector plugin name."input.data.format"
: Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, or BYTES. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON Schema, or Protobuf). Note that you can select schemaless JSON to consume STRING data."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
"request.method"
: Enter an HTTP API Request Method:PUT
,POST
,GET
, orPATCH
. Defaults toPOST
."topics"
: Enter the topic name or a comma-separated list of topic names.
Note
(Optional) To enable CSFLE for data encryption, specify the following properties:
csfle.enabled
: Flag to indicate whether the connector honors CSFLE rules.sr.service.account.id
: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.csfle.onFailure
: Configures the connector behavior (ERROR
orNONE
) on data decryption failure. If set toERROR
, the connector fails and writes the encrypted data in the DLQ. If set toNONE
, the connector writes the encrypted data in the target system without decryption.
For more information on CSFLE setup, see Manage CSFLE for connectors.
Single Message Transforms: For details about adding SMTs using the CLI, see the Single Message Transforms (SMT) documentation. For all property values and descriptions, see Configuration Properties.
Step 3: Load the properties file and create the connector¶
Enter the following command to load the configuration and start the connector:
confluent connect cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file http-sink-v2-config.json
Example output:
Created connector HttpSinkV2Connector_0 lcc-do6vzd
Step 4: Check the connector status¶
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type | Trace |
+------------+-------------------------------+---------+------+-------+
lcc-do6vzd | HttpSinkV2Connector_0 | RUNNING | sink | |
Step 5: Check for records¶
Verify that records are populating the endpoint.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Note that Dead Letter Queue (DLQ), success, and error topics are automatically created for the connector. For more details, see View Connector Dead Letter Queue Errors in Confluent Cloud.
Test API¶
Use the Test API functionality to test the API with a sample record and view the logs directly in the Confluent Cloud user interface.
Important
- This feature is only available for publicly accessible endpoints.
- Invoking the Test API on an API may change data on the end system, depending on the API’s behavior.
When using this feature with the HTTP Sink V2 connector, add your details to the following fields:
${topic}: Topic that the API is expected to consume from. Note that the connector will not actually read anything from the topic, and the topic name configured here will be used wherever you have configured the
${topic}
template variable.Test message: This message should reflect the data present in the Kafka topic. You must configure the expected Kafka key, headers, and values as applicable depending on the
value
ofrequest.body.format
.By default,
request.body.format
is set to JSON format. In this case,value
should be a valid JSON string escaped and enclosed as a string, as shown below:{ "key": "key1", "headers": [ { "header1": "h1" }, { "header2": "h2" } ], "value": "{\"msg\": \"hello world\"}" }
When
request.body.format
set to string format, you can usevalue
as any string, as shown below:{ "key": "key1", "headers": [ { "header1": "h1" }, { "header2": "h2" } ], "value": "hello world" }
Configuration Properties¶
Use the following configuration properties with the fully-managed HTTP V2 Sink connector.
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
Schema Config¶
schema.context.name
Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.
- Type: string
- Default: default
- Importance: medium
value.subject.name.strategy
Determines how to construct the subject name under which the value schema is registered with Schema Registry.
- Type: string
- Default: TopicNameStrategy
- Valid Values: RecordNameStrategy, TopicNameStrategy, TopicRecordNameStrategy
- Importance: medium
Input messages¶
input.data.format
Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or BYTES. 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
- Default: JSON
- 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
Kafka API Key. Required when kafka.auth.mode==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
Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
- Type: password
- Importance: high
Reporter¶
report.errors.as
Dictates the content of records produced to the error topic. If set to
Error string
the value would be a human readable string describing the failure. The value will include some or all of the following information if available: http response code, reason phrase, submitted payload, url, response content, exception and error message. If set to http_response, the value would be the plain response content for the request which failed to write the record. In both modes, any information about the failure will also be included in the error records headers.- Type: string
- Default: Error string
- Importance: low
Consumer configuration¶
max.poll.interval.ms
The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).
- Type: long
- Default: 300000 (5 minutes)
- Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters
- Importance: low
max.poll.records
The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.
- Type: long
- Default: 500
- Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters
- Importance: low
Number of tasks for this connector¶
tasks.max
Maximum number of tasks for the connector.
- Type: int
- Valid Values: [1,…]
- Importance: high
Authentication¶
http.api.base.url
The HTTP API Base URL. For example: http://example.com/absenceManagement/v1.
- Type: string
- Importance: high
auth.type
Authentication type of the endpoint. Valid values are
NONE
,BASIC
,OAUTH2
(Client Credentials grant type only),BEARER
.- Type: string
- Default: NONE
- Importance: high
connection.user
The username to be used with an endpoint requiring basic authentication.
- Type: string
- Importance: medium
connection.password
The password to be used with an endpoint requiring basic authentication.
- Type: password
- Importance: medium
bearer.token
The bearer authentication token to be used with an endpoint requiring bearer token based authentication.
- Type: password
- Importance: medium
oauth2.token.url
The URL to be used for fetching the OAuth2 token. Client Credentials is the only supported grant type.
- Type: string
- Importance: medium
oauth2.client.id
The client id used when fetching the OAuth2 token.
- Type: string
- Importance: medium
oauth2.client.secret
The client secret used when fetching the OAuth2 token.
- Type: password
- Importance: medium
oauth2.token.property
The name of the property containing the OAuth2 token returned by the OAuth2 token URL (defaults to access_token).
- Type: string
- Default: access_token
- Importance: medium
oauth2.client.scope
The scope parameter sent to the service when fetching the OAuth2 token.
- Type: string
- Default: any
- Importance: medium
oauth2.client.auth.mode
Specifies how to encode
client_id
andclient_secret
in the OAuth2 authorization request. If set toheader
, the credentials are encoded as an ‘Authorization: Basic <base-64 encoded client_id:client_secret>’ HTTP header. If set to ‘url’, thenclient_id
andclient_secret
are sent as URL encoded parameters.- Type: string
- Default: header
- Importance: medium
oauth2.client.headers
HTTP headers to be included in the OAuth2 client endpoint. Individual headers should be separated by |
- Type: password
- Importance: low
https.ssl.enabled
Whether or not to connect to the endpoint via SSL.
- Type: boolean
- Default: false
- Importance: medium
https.ssl.keystorefile
The key store containing the server certificate.
- Type: password
- Importance: low
https.ssl.keystore.password
The store password for the key store file.
- Type: password
- Importance: high
https.ssl.key.password
The password for the private key in the key store file.
- Type: password
- Importance: high
https.ssl.truststorefile
The trust store containing a server CA certificate.
- Type: password
- Importance: high
https.ssl.truststore.password
The trust store password containing a server CA certificate.
- Type: password
- Importance: high
https.ssl.protocol
The protocol to use for SSL connections
- Type: string
- Default: TLSv1.3
- Importance: medium
Behavior On Error¶
behavior.on.error
Error handling behavior setting for handling error response from HTTP requests.
- Type: string
- Default: FAIL
- Importance: low
APIs¶
apis.num
The number of http(s) APIs to configure. This value should be less than or equal to 15
- Type: int
- Default: 1
- Importance: high
API-1 Configs¶
api1.http.api.path
The HTTP API path together with the ‘http.api.base.url’ will form the complete HTTP(S) URL. This path can be templated with offset information. For example:
/resource1/${offset}
where${offset}
will be substituted with the offset generated from the previous request’s response (or if it’s the first request, from ‘http.initial.offset’).- Type: string
- Importance: high
api1.topics
List of topics for this API
- Type: list
- Default: “”
- Importance: high
api1.http.request.headers
HTTP headers to be included in each request. Header names and values should be separated by :. Distinct headers should be separated by |. For example: From:abcxyz@confluent.io|Content-Length:348.
- Type: string
- Importance: medium
api1.http.request.method
- Type: string
- Default: POST
- Importance: high
api1.http.request.parameters
HTTP parameters to be added to each request. Parameter names and values should be separated by
=
. Distinct parameters should be separated by&
.- Type: string
- Importance: medium
api1.http.connect.timeout.ms
The time in milliseconds to wait for a connection to be established
- Type: int
- Default: 30000 (30 seconds)
- Importance: medium
api1.http.request.timeout.ms
The time in milliseconds to wait for a request response from the server
- Type: int
- Default: 30000 (30 seconds)
- Importance: medium
api1.behavior.on.null.values
How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are
IGNORE
,DELETE
andFAIL
- Type: string
- Default: IGNORE
- Importance: low
api1.max.retries
The maximum number of times to retry on errors before failing the task.
- Type: int
- Default: 5
- Importance: medium
api1.request.body.format
Used to produce request body in either JSON or String format. The default value is JSON.
- Type: string
- Default: JSON
- Importance: medium
api1.batch.key.pattern
Pattern used to build the key for a given batch. ${key} and ${topic} can be used to include message attributes here
- Type: string
- Importance: high
api1.retry.backoff.policy
The backoff policy to use in terms of retry - CONSTANT_VALUE or EXPONENTIAL_WITH_JITTER
- Type: string
- Default: EXPONENTIAL_WITH_JITTER
- Importance: medium
api1.max.batch.size
The number of records accumulated in a batch before the HTTP API is invoked. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.
- Type: int
- Default: 1
- Importance: high
api1.retry.backoff.ms
The initial duration in milliseconds to wait following an error before a retry attempt is made. Subsequent backoff attempts can be a constant value or exponential with jitter (can be configured using api*.retry.backoff.policy parameter). Jitter adds randomness to the exponential backoff algorithm to prevent synchronized retries.
- Type: int
- Default: 3000 (3 seconds)
- Valid Values: [100,…]
- Importance: medium
api1.batch.prefix
Prefix added to record batches. This is applied once at the beginning of the batch of records
- Type: string
- Importance: high
api1.retry.on.status.codes
Comma-separated list of HTTP status codes or range of codes to retry on. Ranges are specified with start and optional end code. Range boundaries are inclusive. For instance, 400- includes all codes greater than or equal to 400. 400-500 includes codes from 400 to 500, including 500. Multiple ranges and single codes can be specified together to achieve fine-grained control over retry behavior. For example, 404,408,500- will retry on 404 NOT FOUND, 408 REQUEST TIMEOUT, and all 5xx error codes. Note that some status codes will always be retried, such as unauthorized, timeouts and too many requests.
- Type: string
- Default: 400-
- Importance: medium
api1.batch.suffix
Suffix added to record batches. This is applied once at the end of the batch of records
- Type: string
- Importance: high
api1.http.path.parameters
HTTP path parameters to be added to the request. Parameter names and values should be separated by
:
. Distinct parameters should be separated by|
. Parameter values can be templated with different template values like${key}
,${topic}
,${offset}
or other field references from kafka record.- Type: string
- Importance: medium
api1.batch.json.as.array
Whether or not to use an array to bundle json records. Only used when request.body.format is set to json. This can be disabled only when max.batch.size is set to 1.
- Type: boolean
- Default: false
- Importance: high
api1.http.request.body
The custom payload that will be send to the destination instead of record. The value can be templated with key, topic and any other record key (for example:
search_after: ${key}
) where${key}
will be substituted with the key obtained from the record.- Type: string
- Importance: medium
Next Steps¶
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.