Community solution for Kafka integration, seeking feedback and ecosystem integration

[kingsley-123]

Problem Statement

Many data engineering teams need to integrate Dagster with Kafka for real-time data pipelines, but there hasn't been an official or comprehensive community solution. After encountering this gap in my own work, I built a complete integration that I'd like to share with the community.
Solution: dagster-kafka
I've developed and published a comprehensive Kafka integration for Dagster that addresses the full spectrum of production needs:

📦 Now available on PyPI: pip install dagster-kafka

Key Features

1. Multiple serialization formats: JSON, Avro (with Schema Registry), and Protobuf.
2. Enterprise security: Full SASL/SSL support for production clusters.
3. Dead Letter Queue handling: Advanced error handling with circuit breaker patterns.
4. Performance validated: Tested at 1,199 messages/second throughput.
5. Production tooling: Complete CLI suite for DLQ management.
6. Schema evolution support: Comprehensive compatibility validation

Technical Architecture

The integration follows Dagster's native patterns using IOManagers and Resources, making it feel like a first-party integration. It supports both asset-based and op-based workflows.
Links:

GitHub: https://github.com/kingsley-123/dagster-kafka-integration
PyPI: https://pypi.org/project/dagster-kafka/

Questions for the Community

1. Roadmap alignment: Are there plans for official Kafka support? Happy to contribute or collaborate.
2. Ecosystem integration: Would this be suitable for featuring in Dagster's integration ecosystem documentation?
3. Technical feedback: Any suggestions for better alignment with Dagster's architectural patterns?
4. Community needs: What other Kafka-related features would be valuable?

Next Steps

I'm committed to maintaining and improving this integration based on community needs. Would love to discuss how this could best serve the Dagster ecosystem, whether as a community package or potentially contributing elements to the core project.
Looking forward to feedback and collaboration opportunities!