Automating Kafka Schema Registration and Versioning

Question

Pulumi · Accepted Answer

In order to automate Kafka schema registration and versioning, you can use infrastructure as code (IaC) tools like Pulumi to programmatically manage your resources. In the context of Kafka, a schema defines the structure of your Kafka messages, which is essential for ensuring data compatibility across different services that produce and consume these messages. Managing schemas involves creating, updating, and versioning them as your data evolves over time.

With Pulumi, you can use various providers to interact with Kafka and its Schema Registry. For instance, Confluent Cloud offers managed Kafka services, including Schema Registry, which you can use to automate the management of your Kafka schemas.

Below is a Pulumi program in TypeScript that demonstrates how you could automate Kafka schema registration and versioning using the Confluent Cloud provider. This program will:

1. Create a Kafka cluster.
2. Create a Schema Registry in cluster mode.
3. Register a new schema with the registry.
4. Update the compatibility settings for a subject, which represents a schema in the registry.

```typescript
import * as confluentcloud from "@pulumi/confluentcloud";

// Create a Confluent Cloud Kafka cluster
const kafkaCluster = new confluentcloud.KafkaCluster("my-kafka-cluster", {
    environment: {
        id: "env-id", // replace 'env-id' with your Confluent Cloud environment ID
    },
    cloud: "aws",
    region: "us-west-2",
    availability: "LOW",
    standard: {
        encryptionKey: "key-id", // replace 'key-id' with your AWS KMS key ID
        network: {
            id: "net-id", // replace 'net-id' with your VPC ID
        },
    },
});

// Create a Schema Registry cluster in Confluent Cloud
const schemaRegistryClusterMode = new confluentcloud.SchemaRegistryClusterMode("my-schema-registry", {
    mode: "BASIC",
    credentials: {
        key: "your-key",    // replace 'your-key' with your Schema Registry API key
        secret: "your-secret", // replace 'your-secret' with your Schema Registry API secret
    },
    schemaRegistryCluster: {
        id: "schema-reg-cluster-id", // replace 'schema-reg-cluster-id' with your Schema Registry cluster ID
    },
});

// Assume you have a JSON schema string ready to be registered
const schemaString = JSON.stringify({
    type: "record",
    name: "User",
    fields: [
        { name: "name", type: "string" },
        { name: "age", type: "int" },
    ],
});

// Register a new schema for a subject "User" in the Schema Registry
const subjectConfig = new confluentcloud.SubjectConfig("user-schema", {
    credentials: {
        key: "your-key",    // replace 'your-key' with your Schema Registry API key
        secret: "your-secret", // replace 'your-secret' with your Schema Registry API secret
    },
    subjectName: "User",
    compatibilityLevel: "FULL", // set the compatibility level for schema validation
    schemaRegistryCluster: {
        id: schemaRegistryClusterMode.id,
    },
    schema: schemaString,
});

// Export important URLs or IDs
export const kafkaClusterId = kafkaCluster.id;
export const schemaRegistryClusterId = schemaRegistryClusterMode.id;
export const userSchemaId = subjectConfig.id;
```

### Explanation

1. **KafkaCluster** - Firstly, we create a Kafka cluster with the `confluentcloud.KafkaCluster` resource. The environment ID, AWS KMS encryption key ID, and your VPC ID are required parameters.
   
2. **SchemaRegistryClusterMode** - Next, we define a Schema Registry cluster in basic mode using the `confluentcloud.SchemaRegistryClusterMode` resource. We supply API key and secret for authentication.
   
3. **SubjectConfig** - With the Schema Registry set up, we use the `confluentcloud.SubjectConfig` resource to register a new schema for a subject (a subject is typically a Kafka topic, and in this case, it's "User"). We set the compatibility level to FULL, which means that all subsequent schema versions must be backward compatible with previous versions.

4. **Exports** - Lastly, we export the IDs of Kafka cluster, Schema Registry cluster, and the schema ID for external reference. These could be used in other parts of your infrastructure, integration testing, or outputted as part of a CI/CD pipeline.

This is a basic and straightforward example that should get you started with automating Kafka schema registration and versioning using Pulumi and Confluent Cloud. Make sure to replace the placeholder IDs and credentials (`env-id`, `key-id`, `net-id`, `your-key`, `your-secret`, and `schema-reg-cluster-id`) with your actual values. Also, remember that the provided schema is a simple example; your actual schema would likely be more complex and tailored to your needs.

You can find more information about the used resources and their properties within:
- [Confluent Cloud KafkaCluster docs](https://www.pulumi.com/registry/packages/confluentcloud/api-docs/kafkacluster/)
- [Confluent Cloud SchemaRegistryClusterMode docs](https://www.pulumi.com/registry/packages/confluentcloud/api-docs/schemaregistryclustermode/)
- [Confluent Cloud SubjectConfig docs](https://www.pulumi.com/registry/packages/confluentcloud/api-docs/subjectconfig/)

### Next Steps

After setting up schema registration and versioning, you might be interested in further automation steps like monitoring Kafka performance, automating topic creation, ACLs, and more. Pulumi's programming model allows you to codify these operations, enabling efficient management of your data streaming platform.