Deciphering Amazon Aurora MySQL’s storage space usage on Amazon Web Services

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Deciphering Amazon Aurora MySQL’s storage space usage on Amazon Web Services



Amazon Aurora is a managed relational database service that combines the scalability of high-end commercial databases with the cost-effectiveness of open-source databases. The MySQL-Compatible Edition is attractive for businesses using MySQL.

There are two types of storage in Amazon Aurora MySQL: cluster volume storage and local storage. The cluster volume storage is spread across three Availability Zones within an AWS Region for durability, fault tolerance, and high availability. It stores tables, indexes, metadata, and logs. Local storage is used for temporary files and non-InnoDB tables.

User tables and indexes take up most of the storage space in a database. Aurora uses InnoDB as its storage engine, which stores tables in tablespaces. Dropping, truncating, or optimizing tables can free up space in the volume, gradually reducing storage costs.

Temporary tables, both internal and user-created, are also stored in Aurora. In version 2, internal temporary tables use a shared temporary tablespace, while in version 3, they use session temporary tablespaces. Understanding the differences in storage handling between versions is crucial for monitoring storage consumption.

Binary logs and relay logs are important for replication in Aurora MySQL. Enabling binary logs allows for replication to other databases. CloudWatch metrics can be used to monitor the size and number of binary logs. Relay logs may occupy storage space if replication is configured but not active.

Aurora clones allow for quick duplication of clusters using a copy-on-write protocol. Additional storage is allocated only when changes are made to the source or clone clusters. CloudWatch metrics can help monitor local storage and cluster volume utilization in Aurora.

Overall, understanding storage utilization in an Aurora MySQL cluster is essential for managing costs and ensuring optimal performance. Utilizing database queries, configurations, and CloudWatch metrics can help identify storage usage patterns and address potential issues. For more information on working with Amazon Aurora MySQL, refer to AWS documentation.

Article Source
https://aws.amazon.com/blogs/database/understanding-amazon-aurora-mysql-storage-space-utilization/