Scaling ElastiCache

5 minutes 5 Questions

Scaling ElastiCache is the process of adjusting the size and performance of your cache cluster to meet the changing demands of your application. You can scale your ElastiCache deployment horizontally by adding or removing cache nodes in the cluster, or vertically by changing the node type. Scaling horizontally helps distribute the data and traffic loads across multiple cache nodes, while scaling vertically provides more memory and computational resources for your cache engine. You can also use partitioning or sharding techniques to distribute data across multiple cache clusters for even greater scalability. Amazon ElastiCache provides APIs to automate the scaling process and ensure smooth cache cluster scaling without manual intervention.

Guide on Scaling ElastiCache

Amazon ElastiCache is an important service offered by AWS, focusing on enhancing the speed of web applications by allowing you to recover information from fast, managed, in-memory caches, rather than depending on slower disk-based databases.

What is Scaling ElastiCache?
Scaling Amazon ElastiCache is an activity that involves growing or shrinking your ElastiCache resources to match your application's demand. This ensures optimal performance and efficiency of your applications. It can be performed either manually or automatically.

Why is it important?
Scaling is crucial as it allows for a balance between the resources being used and the cost. Efficient use of ElastiCache helps reduce costs and improve performance of your apps. Depending on your traffic, you can increase or decrease resources.

How it works?
ElastiCache can be scaled in two major ways: Vertically(scaling up or down) where you increase or decrease the capacity of an existing node and Horizontally(scaling out or in) where you can increase of decrease the number of nodes in your ElastiCache cluster.

Exam Tips: Answering Questions on Scaling ElastiCache: Understanding the types of scaling and when to use them will be valuable in the exam. Be familiar with the process of scaling ElastiCache, both manually and automatically, as this is a common topic. Ensure you understand the implications of scaling (like possible downtime) on your applications.

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Question 1

During peak hours, a photo-sharing application experiences increased latency while accessing its caching layer. The application uses the default Amazon ElastiCache parameter group. To optimize performance, which configuration change should be implemented?

Enable write coalescing Enable the cache engine's slow query log Decrease the cache hit ratio Increase the maximum number of connections

Correct Answer: Increase the maximum number of connections

Increasing the maximum number of connections in the ElastiCache parameter group can help handle the increased load during peak hours. Slow query logs can help identify problematic queries, but not necessarily optimize performance. Decreasing the cache hit ratio or engine version would negatively impact performance. Write coalescing and cache snapshots are not related to performance optimization.

Question 2

An online store has implemented Amazon ElastiCache for Redis to cache frequently used data. They need to ensure the cache reliably scales horizontally with the increased read traffic. Which solution should be used?

Multi-AZ Read replicas Sharding Vertical scaling

Correct Answer: Read replicas

Read replicas allow horizontal scaling of read traffic in ElastiCache for Redis. Sharding is used for partitioning data among cluster nodes, while multi-AZ is for high availability. Vertical scaling involves resizing the node, and Global Datastore is for disaster recovery. A Cache Cluster is simply a collection of cache nodes in a region.

Question 3

A gaming company wants to reduce latency during periodic data retrieval updates. The gaming application uses Amazon ElastiCache for Redis with an m5.large node type. How can the company optimize performance?

Use global datastore Set up a cache cluster Add more read replicas Enable online resharding

Correct Answer: Enable online resharding

Enabling online resharding allows data to be distributed evenly across multiple shards, which improves performance by reducing the likelihood of hotspots. Setting up a cache cluster, using a global datastore, or adding more read replicas would not help with periodic data retrieval updates. Eventual consistency and disabling snapshots are not related to performance.

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