We’re excited to announce support for Kafka Schema Registry in DigitalOcean’s Managed Kafka service, giving developers a powerful way to manage and validate schemas in their event-driven applications. Kafka Schema Registry, also referred to as Karapace, is a centralized service for managing and validating schemas for Kafka messages. It helps to ensure that data produced to and consumed from Kafka topics adheres to a defined structure, preventing data compatibility issues.

Why use Schema Registry?

For a developer, Kafka Schema Registry provides robust schema governance and standardized HTTP access for Kafka services, improving data integrity, developer productivity, and system interoperability. This helps to empower DevOps teams to build reliable, evolving event-driven applications by ensuring data integrity through centralized schema management and validation. Schema Registry simplifies the Kafka integration across diverse systems in a more secure way.

Ultimately, this tool brings structure to your Kafka topics. It lets you define, version, and validate message schemas so that producers and consumers can stay in sync, even as your data evolves. It helps prevent breaking changes, making debugging easier, and keeps your Kafka pipelines reliable at scale. Please note that Kafka Schema Registry is only available for Kafka customers with a dedicated CPU environment. To learn more about our CPU-optimized Droplets, visit our Droplets homepage or our [product documentation.

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Features of Kafka Schema Registry

• Schema registration & validation:

• Helps to improve data consistency and reduces runtime errors caused by mismatched data formats, leading to more stable applications.

• Schema evolution & compatibility control:

• Allows producer and consumer applications to evolve independently without breaking each other, facilitating agile development and reducing deployment risks.

• Centralized schema storage:

• Helps to provide a clear, organized, and accessible repository for all schemas, making it easier for developers to understand data structures and reducing duplicated effort.

• REST Proxy for Kafka:

• Lowers the barrier to entry for interacting with Kafka from diverse platforms and applications (e.g., web frontends, scripting languages, legacy systems) that cannot easily use native Kafka clients.

Common Developer Use Cases

Here are some specific use cases and their unique benefits:

• Microservices Communication: Prevents runtime errors by helping to ensure that producer and consumer microservices have a shared understanding of the message format.

• Data Contracts and Versioning: Enables safe evolution of data structures, allowing producer applications to update schemas without disrupting downstream consumers who may expect older versions.

• ETL and Analytics Pipelines: Helps to ensure data quality and prevents job failures by validating that incoming data adheres to the expected structure before it enters the pipeline.

• API Gateways: Deliver consistent, reliable data to external clients while removing the guesswork and working to ensure predictable, structured payloads for every request.

  Machine Learning Workflows: Helps to ensure the structural integrity of training and inference data, which is crucial for model reproducibility and effective debugging.

Getting Started

You can enable Schema Registry from the DigitalOcean Cloud Console or via API when provisioning a Kafka cluster. You’ll get access to a dedicated Schema Registry endpoint that works seamlessly with a Kafka producer and consumer clients. To get started, try these links:

• Spin up a Kafka cluster

• Already have an account? Log in

• Explore our Managed Kafka service

• Watch our fireside chat with Kafka expert

• Contact sales