Configuring Aurora MySQL binary logging - Amazon Aurora
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Configuring Aurora MySQL binary logging

The binary log is a set of log files that contain information about data modifications made to an Aurora MySQL server instance. The binary log contains information such as the following:

  • Events that describe database changes such as table creation or row modifications

  • Information about the duration of each statement that updated data

  • Events for statements that could have updated data but didn't

The binary log records statements that are sent during replication. It is also required for some recovery operations. For more information, see The Binary Log and Binary Log Overview in the MySQL documentation.

Binary logs are accessible only from the primary DB instance, not from the replicas.

MySQL on Amazon Aurora supports the row-based, statement-based, and mixed binary logging formats. We recommend mixed unless you need a specific binlog format. For details on the different Aurora MySQL binary log formats, see Binary logging formats in the MySQL documentation.

If you plan to use replication, the binary logging format is important because it determines the record of data changes that is recorded in the source and sent to the replication targets. For information about the advantages and disadvantages of different binary logging formats for replication, see Advantages and disadvantages of statement-based and row-based replication in the MySQL documentation.


Setting the binary logging format to row-based can result in very large binary log files. Large binary log files reduce the amount of storage available for a DB cluster and can increase the amount of time to perform a restore operation of a DB cluster.

Statement-based replication can cause inconsistencies between the source DB cluster and a read replica. For more information, see Determination of safe and unsafe statements in binary logging in the MySQL documentation.

Enabling binary logging increases the number of write disk I/O operations to the DB cluster. You can monitor IOPS usage with the VolumeWriteIOPs CloudWatch metric.

To set the MySQL binary logging format
  1. Open the Amazon RDS console at

  2. In the navigation pane, choose Parameter groups.

  3. Choose the DB cluster parameter group, associated with the DB cluster, that you want to modify.

    You can't modify a default parameter group. If the DB cluster is using a default parameter group, create a new parameter group and associate it with the DB cluster.

    For more information on parameter groups, see Working with parameter groups.

  4. From Actions, choose Edit.

  5. Set the binlog_format parameter to the binary logging format of your choice (ROW, STATEMENT, or MIXED). You can also use the value OFF to turn off binary logging.


    Setting binlog_format to OFF in the DB cluster parameter group disables the log_bin session variable. This disables binary logging on the Aurora MySQL DB cluster, which in turn resets the binlog_format session variable to the default value of ROW in the database.

  6. Choose Save changes to save the updates to the DB cluster parameter group.

After you perform these steps, you must reboot the writer instance in the DB cluster for your changes to apply. In Aurora MySQL version 2.09 and lower, when you reboot the writer instance, all of the reader instances in the DB cluster are also rebooted. In Aurora MySQL version 2.10 and higher, you must reboot all of the reader instances manually. For more information, see Rebooting an Amazon Aurora DB cluster or Amazon Aurora DB instance.


Changing a DB cluster parameter group affects all DB clusters that use that parameter group. If you want to specify different binary logging formats for different Aurora MySQL DB clusters in an Amazon Region, the DB clusters must use different DB cluster parameter groups. These parameter groups identify different logging formats. Assign the appropriate DB cluster parameter group to each DB clusters. For more information about Aurora MySQL parameters, see Aurora MySQL configuration parameters.