Backup and Restore Strategies for Cassandra Clusters with Medusa

Introduction

Cassandra, a highly scalable NoSQL database, is widely adopted for its ability to handle large volumes of data across distributed clusters. However, ensuring data integrity and availability remains a critical challenge, particularly in environments like Bloomberg, where high availability and regulatory compliance are paramount. Traditional backup methods often fall short in addressing dynamic cluster architectures and storage efficiency. This article explores how Bloomberg leveraged Medusa, a specialized Cassandra backup tool, to overcome these challenges and implement a robust backup and restore strategy.

Technical Overview

Cassandra Backup Challenges

Cassandra’s native backup tools, such as nodetool snapshot, provide basic snapshot capabilities but lack advanced features for managing large-scale clusters. Bloomberg’s previous backup system relied on custom tools, resulting in manual recovery processes, high storage costs, and limited observability. These limitations hindered scalability and compliance with evolving regulatory requirements.

Medusa: A Purpose-Built Solution

Medusa, developed by Spotify, is designed specifically for Cassandra, offering features such as full and differential backups, remote storage integration, and automated cleanup. It supports restoring data to clusters with identical or different topologies, making it ideal for dynamic environments. Medusa’s containerized deployment model aligns with modern infrastructure practices, enabling seamless integration with orchestration tools.

Key Features and Implementation

Backup Mechanisms

• Full and Differential Backups: Medusa generates full backups of SSTable files and differential backups that only store changes since the last snapshot, reducing storage overhead.
• Remote Storage: Backups are stored in S3-compatible storage, optimizing cost and scalability.
• Automated Cleanup: The Purge feature manages retention policies, deleting obsolete backups based on quantity or time thresholds.

Recovery Workflow

1. Orchestrator Coordination: The orchestrator initiates the recovery process, specifying cluster nodes and backup IDs.
2. Containerized Execution: The Container Agent launches Cassandra containers, configuring metadata and token assignments.
3. Data Restoration: Medusa downloads backup files, reconstructing the cluster topology and ensuring data integrity.

Containerization and Integration

Cassandra runs as a container, with Medusa CLI deployed as a sidecar container. The Metadata Service provides cluster configuration details, enabling dynamic backup and recovery. This architecture simplifies management and ensures compatibility with Kubernetes or Docker-based deployments.

Advantages and Challenges

Benefits

• Automation: Medusa eliminates manual intervention, reducing recovery time and operational complexity.
• Cost Efficiency: Differential backups minimize redundant data, lowering storage and network costs.
• Scalability: Remote storage and containerization support large-scale clusters without infrastructure constraints.

Challenges

• Storage Management: Ensuring data consistency during purging requires careful tracking of SSTable references.
• Recovery Limitations: Current recovery processes are restricted to immutable cluster configurations, limiting flexibility.

Conclusion

Medusa addresses critical gaps in Cassandra’s native backup capabilities, offering a scalable, automated solution for modern clusters. By integrating with containerized environments and leveraging differential backups, Bloomberg achieved efficient data protection while complying with regulatory standards. As Cassandra continues to evolve, tools like Medusa will remain essential for balancing performance, cost, and reliability in distributed systems.