Which method is commonly used for ensuring data redundancy in cloud architectures?

Data replication across multiple regions is a widely adopted method for ensuring data redundancy in cloud architectures. This approach involves creating copies of data and distributing them across different geographic locations or data centers. By replicating data, organizations can safeguard against data loss due to hardware failures, cyber threats, or natural disasters affecting a single location. If one data center encounters issues, the replicated data in another region allows for immediate access and recovery, maintaining business continuity and ensuring reliable service availability.

Implementing data replication not only protects against outages but also enhances data accessibility, as users can retrieve data from the nearest region, significantly improving performance and experience. This strategy aligns with the principles of high availability and disaster recovery, making it a key component of robust cloud infrastructure design.

Other methods like backing up to local storage, single instance deployment, and compression techniques do not provide the same level of redundancy or resilience. Local backups can be vulnerable to the same threats affecting primary storage, while single instance deployment lacks the diversity needed for effective redundancy. Compression techniques, on the other hand, optimize storage but do not address the need for multiple copies in different locations to ensure data availability.