This chapter covers
- Failure mitigation strategies in Kafka
- Data loss risks and strategies for fault tolerance
- MirrorMaker’s synchronization of topics and access control lists
- Architectures for improved disaster recovery
In this chapter, we delve into the crucial topic of disaster management in Kafka. When disaster strikes and systems fail, the consequences can be severe: financial losses from interrupted business operations, damaged customer relationships due to service outages, and potential regulatory compliance violations in case of data loss.
Organizations may also suffer lasting reputation damage if they can’t quickly recover from failures. These business risks make effective disaster management essential. We’ll explore how to mitigate various types of failures, whether they stem from network problems, compute failures, or persistent storage problems, to ensure both system reliability and data integrity.
Understanding the nature of potential disasters allows organizations to differentiate between critical and less critical scenarios, enabling them to prioritize their strategies effectively. We’ll explore the various options available for disaster recovery, including the limitations of traditional backup strategies and the need for robust solutions that minimize data loss and inconsistencies.