A solution architect would like to implement a caching solution for an application.
The application is read-heavy performing frequent read operations.
The application load is very unpredictable.
So the solution architect would like to be able to horizontally scale the caching system up and down as required, while keeping the infrastructure costs minimal.
What is the optimal solution to this problem?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: A.
Option A is CORRECT because ElastiCache for Redis (Cluster Mode Disabled) clusters support scaling up or down of read capacity by creating or deleting read replicas within the cluster.
Option B is incorrect because horizontally scaling ElastiCache for Redis (Cluster Mode Enabled) clusters can be a complex activity as it can require re-sharding of the clusters.
Therefore, this is not the ideal solution.
Option C is incorrect because Amazon DAX is a caching solution specific to DynamoDB.Option D is incorrect because Write-Through caching strategy is related to the consistency of data in cache in relation to the base source database.
It is not relevant to the scenario.
Reference:
https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Replication.Redis-RedisCluster.htmlThe optimal solution for the given scenario would be to deploy Amazon ElastiCache for Redis (Cluster Mode Enabled) cluster.
Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. Redis is an open-source in-memory data structure store used as a database, cache, and message broker.
The benefits of using ElastiCache for Redis (Cluster Mode Enabled) in this scenario are:
Scalability: Redis (Cluster Mode Enabled) allows horizontal scaling by distributing data across multiple nodes, making it easier to scale up and down as per the application load.
High Availability: Redis (Cluster Mode Enabled) provides high availability by automatically replicating data across multiple nodes.
Cost-Effective: Redis (Cluster Mode Enabled) provides a cost-effective solution for caching as it allows sharing of resources across multiple nodes.
Read-Heavy Workload: Redis (Cluster Mode Enabled) is optimized for read-heavy workloads, which makes it an ideal choice for caching read-intensive applications.
Predictability: Redis (Cluster Mode Enabled) allows easy prediction of cache size and usage patterns, which helps in minimizing infrastructure costs.
In contrast, Amazon ElastiCache for Redis (Cluster Mode Disabled) cluster is designed for use cases that require a smaller cache size with simple scaling requirements, and it is not suitable for unpredictable workloads.
Amazon DAX is a managed, in-memory cache for DynamoDB that provides low-latency access to data. However, it is not suitable for use cases where the workload is read-heavy and unpredictable, as it does not support horizontal scaling.
Write-Through caching strategy is a caching technique where all write operations are performed on the cache and the database simultaneously, which makes it suitable for write-heavy workloads. However, it is not suitable for the given scenario where the workload is read-heavy.
In conclusion, deploying Amazon ElastiCache for Redis (Cluster Mode Enabled) cluster is the optimal solution for this scenario due to its scalability, high availability, cost-effectiveness, suitability for read-heavy workloads, and predictability.