Replication with Amazon Aurora MySQL
The Aurora MySQL replication features are key to the high availability and performance of your cluster. Aurora makes it easy to create or resize clusters with up to 15 Aurora Replicas.
All the replicas work from the same underlying data. If some database instances go offline, others remain available to continue processing queries or to take over as the writer if needed. Aurora automatically spreads your read-only connections across multiple database instances, helping an Aurora cluster to support query-intensive workloads.
In the following topics, you can find information about how Aurora MySQL replication works and how to fine-tune replication settings for best availability and performance.
Topics
- Using Aurora Replicas
- Replication options for Amazon Aurora MySQL
- Performance considerations for Amazon Aurora MySQL replication
- Zero-downtime restart (ZDR) for Amazon Aurora MySQL
- Configuring replication filters with Aurora MySQL
- Monitoring Amazon Aurora MySQL replication
- Using local write forwarding in an Amazon Aurora MySQL DB cluster
- Replicating Amazon Aurora MySQL DB clusters across AWS Regions
- Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binary log replication)
- Using GTID-based replication
Using Aurora Replicas
Aurora Replicas are independent endpoints in an Aurora DB cluster, best used for scaling read operations and increasing availability. Up to 15 Aurora Replicas can be distributed across the Availability Zones that a DB cluster spans within an AWS Region. Although the DB cluster volume is made up of multiple copies of the data for the DB cluster, the data in the cluster volume is represented as a single, logical volume to the primary instance and to Aurora Replicas in the DB cluster. For more information about Aurora Replicas, see Aurora Replicas.
Aurora Replicas work well for read scaling because they are fully dedicated to read operations on your cluster volume. Write operations are managed by the primary instance. Because the cluster volume is shared among all instances in your Aurora MySQL DB cluster, no additional work is required to replicate a copy of the data for each Aurora Replica. In contrast, MySQL read replicas must replay, on a single thread, all write operations from the source DB instance to their local data store. This limitation can affect the ability of MySQL read replicas to support large volumes of read traffic.
With Aurora MySQL, when an Aurora Replica is deleted, its instance endpoint is removed immediately, and the Aurora Replica is removed from the reader endpoint. If there are statements running on the Aurora Replica that is being deleted, there is a three minute grace period. Existing statements can finish gracefully during the grace period. When the grace period ends, the Aurora Replica is shut down and deleted.
Important
Aurora Replicas for Aurora MySQL always use the REPEATABLE READ default transaction isolation
level for operations on InnoDB tables. You can use the SET TRANSACTION ISOLATION LEVEL command
to change the transaction level only for the primary instance of an Aurora MySQL DB cluster. This restriction
avoids user-level locks on Aurora Replicas, and allows Aurora Replicas to scale to support thousands of active
user connections while still keeping replica lag to a minimum.
Note
DDL statements that run on the primary instance might interrupt database connections on the associated Aurora Replicas. If an Aurora Replica connection is actively using a database object, such as a table, and that object is modified on the primary instance using a DDL statement, the Aurora Replica connection is interrupted.
Note
The China (Ningxia) Region does not support cross-Region read replicas.
Replication options for Amazon Aurora MySQL
You can set up replication between any of the following options:
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Two Aurora MySQL DB clusters in different AWS Regions, by creating a cross-Region read replica of an Aurora MySQL DB cluster.
For more information, see Replicating Amazon Aurora MySQL DB clusters across AWS Regions.
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Two Aurora MySQL DB clusters in the same AWS Region, by using MySQL binary log (binlog) replication.
For more information, see Replication between Aurora and MySQL or between Aurora and another Aurora DB cluster (binary log replication).
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An RDS for MySQL DB instance as the source and an Aurora MySQL DB cluster, by creating an Aurora read replica of an RDS for MySQL DB instance.
You can use this approach to bring existing and ongoing data changes into Aurora MySQL during migration to Aurora. For more information, see Migrating data from an RDS for MySQL DB instance to an Amazon Aurora MySQL DB cluster by using an Aurora read replica.
You can also use this approach to increase the scalability of read queries for your data. You do so by querying the data using one or more DB instances within a read-only Aurora MySQL cluster. For more information, see Scaling reads for your MySQL database with Amazon Aurora.
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An Aurora MySQL DB cluster in one AWS Region and up to five Aurora read-only Aurora MySQL DB clusters in different Regions, by creating an Aurora global database.
You can use an Aurora global database to support applications with a world-wide footprint. The primary Aurora MySQL DB cluster has a Writer instance and up to 15 Aurora Replicas. The read-only secondary Aurora MySQL DB clusters can each be made up of as many as 16 Aurora Replicas. For more information, see Using Amazon Aurora Global Database.
Note
Rebooting the primary instance of an Amazon Aurora DB cluster also automatically reboots the Aurora Replicas for that DB cluster, to re-establish an entry point that guarantees read/write consistency across the DB cluster.
Performance considerations for Amazon Aurora MySQL replication
The following features help you to fine-tune the performance of Aurora MySQL replication.
The replica log compression feature automatically reduces network bandwidth for replication messages. Because each message is transmitted to all Aurora Replicas, the benefits are greater for larger clusters. This feature involves some CPU overhead on the writer node to perform the compression. It's always enabled in Aurora MySQL version 2 and version 3.
The binlog filtering feature automatically reduces network bandwidth for replication messages. Because the Aurora Replicas don't use the binlog information that is included in the replication messages, that data is omitted from the messages sent to those nodes.
In Aurora MySQL version 2, you can control this feature by changing the aurora_enable_repl_bin_log_filtering
parameter. This parameter is on by default. Because this optimization is intended to be transparent, you might turn off this
setting only during diagnosis or troubleshooting for issues related to replication. For example, you can do so to match the
behavior of an older Aurora MySQL cluster where this feature was not available.
Binlog filtering is always enabled in Aurora MySQL version 3.
Monitoring Amazon Aurora MySQL replication
Read scaling and high availability depend on minimal lag time. You can monitor how far an Aurora Replica is lagging behind the
primary instance of your Aurora MySQL DB cluster by monitoring the Amazon CloudWatch AuroraReplicaLag metric. The
AuroraReplicaLag metric is recorded in each Aurora Replica.
The primary DB instance also records the AuroraReplicaLagMaximum and AuroraReplicaLagMinimum Amazon CloudWatch
metrics. The AuroraReplicaLagMaximum metric records the maximum amount of lag between the primary DB instance and
each Aurora Replica in the DB cluster. The AuroraReplicaLagMinimum metric records the minimum amount of lag between
the primary DB instance and each Aurora Replica in the DB cluster.
If you need the most current value for Aurora Replica lag, you can check the AuroraReplicaLag metric in Amazon CloudWatch. The
Aurora Replica lag is also recorded on each Aurora Replica of your Aurora MySQL DB cluster in the
information_schema.replica_host_status table. For more information on this table, see information_schema.replica_host_status.
For more information on monitoring RDS instances and CloudWatch metrics, see Monitoring metrics in an Amazon Aurora cluster.
