Question: What is a distributed cache in AWS and how can it be implemented?


Distributed caching in AWS primarily involves two services: Amazon ElastiCache and DynamoDB Accelerator (DAX).

Amazon ElastiCache supports two open-source in-memory caching engines: Memcached and Redis. This service improves application performance by storing critical pieces of data in memory for low-latency access.

DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache that can reduce Amazon DynamoDB response times from milliseconds to microseconds, even at millions of requests per second.

Implementing Distributed Cache using ElastiCache:

Here's an example showcasing how to create a new Redis cluster:

aws elasticache create-cache-cluster --cache-cluster-id my-cluster \ --engine redis --cache-node-type cache.t2.micro --num-cache-nodes 1 \ --region us-west-2

This command creates a simple Redis cluster in the region "us-west-2" with one node of type "cache.t2.micro" and assigns it the identifier "my-cluster".

You can then connect to this cluster using a Redis client and the endpoint provided by AWS.

Implementing Distributed Cache using DAX:

For creating a DAX cluster you need to use the create-cluster command as shown below:

aws dax create-cluster --cluster-name mydaxcluster --iam-role-arn myDAXRoleARN \ --node-type dax.r4.large --replication-factor 3 --region us-west-2

The above command creates a DAX cluster named "mydaxcluster" in the "us-west-2" region with three nodes of type "dax.r4.large". The role ARN "myDAXRoleARN" must be an existing IAM role with appropriate permissions.

Thereafter, to use the newly created DAX cluster, you would modify your application's code to use the DAX client instead of the standard DynamoDB client and provide DAX cluster URL as your service endpoint.

Remember, both ElastiCache and DAX have their own use cases and constraints so they should be chosen based on the specific needs of your application.

Note: You need to have appropriate permissions and roles setup in AWS to execute these commands. AWS CLI configured on your local machine or EC2 instances is required.

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