Existing applications that use Redis can use ElastiCache with little to no modification. Your applications simply need information about the hostnames and port numbers of the ElastiCache nodes you have deployed.
ElastiCache for Redis has several features that help make the service more reliable for critical production deployments:
Automatic detection and recovery from cache node failures.
Multi-AZ for failed primary cluster to read replica in Redis clusters that support replication.
Redis (cluster mode enabled) supports splitting your data into up to 500 shards.
For Redis version 3.2 and later, all versions support encryption-in-transit and encryption-at-rest encryption with authentication. This support helps you create HIPAA-compliant applications.
Flexible node and cluster Availability Zone placement for increased fault tolerance.
Integration with other AWS services such as Amazon EC2, Amazon CloudWatch, AWS CloudTrail, and Amazon SNS. This integration helps provide a managed caching solution that is both high performance and highly secure.
ElastiCache for Redis manages backups, software patching, automatic failure detection and recovery.
You can have automatic backups performed when you need them, or manually create your own backup snapshot. You can use these backups to restore the cluster. The ElastiCache for Redis recovery process works reliably and efficiently.
You can get high availability with a primary instance and a synchronous secondary instance that you can fail over to when problems arise. You can also use read replicas to increase read scale.
You can control access to your ElastiCache for Redis clusters by using AWS Identity and Access Management to define users and permissions. You can also help protect your clusters by placing them in a virtual private cloud (VPC).
With Global Datastore for Redis, you can work with fully managed, fast, reliable and secure replication across AWS regions. With this feature, you can create cross-region read replica clusters for ElastiCache for Redis to enable low-latency reads and disaster recovery across AWS regions.
Data tiering provides a price and performance option for Redis workloads by using cheaper Solid State Drives (SSDs) on each node of the cluster in addition to storing data in memory. It's ideal for workloads that regularly access up to 20 percent of their total data set, and for applications that can tolerate additional latency when accessing data on an SSD. For more information, see Data layering
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