AWS Aurora is AWS's database with an architecture designed for cloud computing technologies. One of it's differences is that data is stored in a storage architecture similar to S3, in a cluster volume, which is a single, utilizes solid state disk (SSD) drives and consists of copies of the data across multiple Availability Zones in a single region. That has a few advantages, such as durability and also the fact that is distributed through in entire region, not just an AZ, helping with consistency between replicas and performance.
In case you have read replicas and your Master fails, one of them will become Master without downtime.
If you don't have a read replica, a new Master instance will be created and the process is really fast. Since data is on clusterized across the region, not on the server's disk, the process is fast, but there is downtime.
As AWS says:
To increase availability, you can use Aurora Replicas as failover
targets. That is, if the primary instance fails, an Aurora Replica is
promoted to the primary instance with only a brief interruption during
which read and write requests made to the primary instance fail with
an exception. If your Aurora DB cluster does not include any Aurora
Replicas, then the primary instance is recreated during a failure
event. However, promoting an Aurora Replica is much faster than
recreating the primary instance. For high-availability scenarios, we
recommend that you create one or more Aurora Replicas, of the same DB
instance class as the primary instance, in different Availability
Zones for your Aurora DB cluster. For more information on Aurora
Replicas as failover targets, see Fault Tolerance for an Aurora DB
Cluster.
You can read more on: http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Aurora.Replication.html"