Project Name
Enhance Healthcare Data Management with Kafka to RedPanda Data Migration
Overview
Our client belongs to the healthcare industry whose main aim is to transition from Kafka to RedPanda as their data streaming tool within the Big Data ecosystem. They work on reducing the complexity and lowering the costs compared to their current managed Kafka solution. To work on this transition, they need a real-time data migration from Kafka to RedPanda. The main aim of this project is to simplify the infrastructure, improve performance, and optimize data processing.
Challenges
- While migrating the data from Kafka to RedPanda needs careful planning it also handles issues related to data replication, offsets, and state.
- Full compatibility issues arise during the migration process as a major challenge.
Our Solution
The Ksolves team provided a comprehensive solution to the client that includes the mentioned steps:
Validation and Monitoring
- To ensure successful data replication, a similar topic is created in RedPanda.
- The status of the connectors was continuously monitored using specialized monitoring tools like Prometheus and Grafana, which provided real-time insights into the replication process.
- Data consistency was validated by comparing records in both Kafka and Red Panda.
Data Replication with MirrorMaker 2.0
We selected MirrorMaker 2.0 (MM2) as the primary tool for data replication due to its ability to replicate data between Kafka and Red Panda clusters seamlessly. MM2 supports the Kafka Connect framework.
- MirrorSourceConnector: Set up to replicate data from the Kafka cluster to Red Panda. Configured to handle offset translation and exactly-once delivery semantics.
- MirrorCheckpointConnector: Managed checkpoints to ensure offset translation and failover support.
- MirrorHeartbeatConnector: Provided replication latency measurements and ensured continuous replication.
Error Handling:
The migration strategy incorporated robust error-handling mechanisms to manage potential data replication issues. This included:
- Automatic Failover: In case of replication failures or disruptions, the system was designed to automatically switch to a backup replication process, minimizing downtime and preventing data loss.
- Error Logging: Any errors or anomalies detected during the replication process were logged.
- Retry failed messages: All the failed messages are monitored and stored and later sent over to Red Panda.
Data Flow Diagram
Conclusion
The Kafka to RedPanda data migration strategy executed successfully shows RedPanda’s capability to replace Kafka with enhanced performance and lower complexity. By utilizing MirrorMaker 2.0 for data replication, the data migration is carried out with minimal issues to ensure data integrity and operational continuity.
In addition, this transition works on optimizing the client’s messaging infrastructure and also improves the effectiveness of RedPanda in modernizing data streaming platforms.
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