ServiceNow Sink Connector for Confluent Cloud¶
The fully-managed ServiceNow Sink connector for Confluent Cloud is used to capture Apache Kafka® records and sink them to a ServiceNow Table in real time. Data is consumed using the ServiceNow Table API.
Note
- This Quick Start is for the fully-managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see ServiceNow Sink Connector for Confluent Platform.
- 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 ServiceNow 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.
Automatically creates topics: The following three topics are automatically created when the connector starts:
- Success topic
- Error topic
- Dead letter queue (DLQ) topic
The suffix for each topic name is the connector’s logical ID. In the example below, there are the three connector topics and one pre-existing Kafka topic named pageviews.
If the records sent to the topic are not in the correct format, or if important fields are missing in the record, the errors are recorded in the error topic, and the connector continues to run.
Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
Supported data formats: The connector supports Avro, JSON Schema (JSON-SR), and Protobuf input formats. Schema Registry must be enabled to use these Schema Registry-based formats.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Limitations¶
Be sure to review the following information.
- For connector limitations, see ServiceNow Sink 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 Schema Registry Enabled Environments.
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud ServiceNow Sink 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), Microsoft Azure (Azure), or Google Cloud.
- An authorized ServiceNow user and credentials for the connector.
- The Confluent CLI installed and configured for the cluster. 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). See Schema Registry Enabled Environments for additional information.
- 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 ServiceNow Sink Connector screen, complete the following:
If you’ve already populated your Kafka topics, select the topics you want to connect from the Topics list.
To create a new topic, click +Add new topic.
- 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.
- In the ServiceNow Instance URL field, enter you ServiceNow Instance
URL, which can be in the format
https://dev1000.service-now.com/
. - In the ServiceNow table name field, enter your ServiceNow table name.
- Enter the ServiceNow basic authentication username in the ServiceNow Username field.
- In the ServiceNow Password field, enter the ServiceNow basic authentication password.
- Click Continue.
Note
Configuration properties that are not shown in the Cloud Console use the default values. See Configuration Properties for all property values and definitions.
Select the Input Kafka record value format (data coming from the Kafka topic): AVRO, JSON_SR, 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).
(Optional) 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.Show advanced configurations
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?.
HTTP request timeout (ms): The HTTP request timeout in milliseconds.
Maximum number of times to retry request: The maximum number of times to retry a request.
Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.
See Configuration Properties for all property values and definitions.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
- To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field.
- Click Continue.
Verify the connection details.
Click Launch.
The status for the connector should go from Provisioning to Running.
Step 5: Check for records¶
Verify that the ServiceNow table is getting updated.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.
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.
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.
{
"connector.class": "ServiceNowSink",
"input.data.format": "AVRO",
"name": "ServiceNowSink_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "****************",
"kafka.api.secret": "************************************************",
"servicenow.url": "<servicenow-URL>",
"servicenow.table": "<table-name>",
"servicenow.user": "<authorized-username>",
"servicenow.password": "<user-password>",
"tasks.max": "1",
"topics": "orders"
}
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, and PROTOBUF. You must have Confluent Cloud Schema Registry configured if using 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
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
servicenow.<>
Required ServiceNow connection details. The URL should be in the formathttps://dev1000.service-now.com/
."tasks.max"
: Enter the maximum number of tasks for the connector to use. More tasks may improve performance."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: 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 cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file servicenow-sink-config.json
Example output:
Created connector ServiceNowSink_0 lcc-do6vzd
Step 5: 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 | ServiceNowSink_0 | RUNNING | sink | |
Step 6: Check for records.¶
Verify that the ServiceNow table is updating.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.
Configuration Properties¶
Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors 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
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
Input messages¶
input.data.format
Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR and PROTOBUF. Note that you need to have Confluent Cloud Schema Registry configured
- 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
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
ServiceNow details¶
servicenow.url
ServiceNow Instance URL.
- Type: string
- Importance: high
servicenow.table
ServiceNow table name.
- Type: string
- Importance: high
servicenow.user
ServiceNow basic authentication username.
- Type: string
- Importance: high
servicenow.password
ServiceNow basic authentication password.
- Type: password
- Importance: high
connection.timeout.ms
HTTP request timeout in milliseconds.
- Type: int
- Default: 50000 (50 seconds)
- Importance: low
retry.max.times
Maximum number of times to retry request.
- Type: int
- Default: 3
- 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
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.