Caching is an essential component in designing and building applications on Amazon Web Services (AWS). It plays a critical role in enhancing performance, scalability, and cost-efficiency. Therefore, understanding caching strategies is highly imperative for those preparing for the AWS Certified Solutions Architect – Associate (SAA-C03) exam. This article reviews this fundamental concept, its benefits and major AWS services that help implement caching to enhance cloud solutions’ performance.
1. Understanding Caching
Caching involves storing copies of files or data in a cache, or temporary storage location, so they can be accessed more quickly than if they were accessed directly from the original storage location. Data or files in a cache might include data shards or computation outputs that are costly to compute or retrieve and are likely to be used again. Caching can significantly improve the efficiency of system processes and the overall user experience.
2. Types of Caching in AWS
AWS provides various caching options designed to serve specific needs:
- In-Memory Caching: It utilizes services like Amazon ElastiCache offering fully managed Redis and Memcached. Perfectly suited for use cases such as caching, session storage, gaming, geospatial, real-time analytics, and queueing.
- Edge Caching: AWS CloudFront is the Content Delivery Network (CDN) service, which caches data to edge locations, so content is closer (in terms of latency) to the users.
- Database Query Caching: AWS offers RDS with query caching capabilities, causing frequent SQL queries to pull data from the cache instead of the database, optimizing performance.
3. Caching Strategies
Two fundamental caching strategies are Cache-Aside and Write-Through.
- Cache-Aside Strategy: Here, the application code checks the cache first when a request is received. If the cache doesn’t contain the data (a condition known as a cache miss), the application fetches data from the main store, writes it into the cache, and returns it to the requester. This approach means the cache is always updated with the most recent data.
- Write-Through Strategy: In this approach, any new or updated data is written to the cache and the main store simultaneously. This strategy minimizes the risk of data loss, which might occur if the cache data disappears before it’s written to the main store.
| Cache-Aside | Write-Through | |
|---|---|---|
| Operation | Checks cache first, if missed, retrieves from main store and updates cache. | Writes data to cache and main store simultaneously. |
| Data loss risk | Higher if cache disappears before being written to main store. | Lower as both cache and main store are written simultaneously. |
4. AWS Services for Implementing Caching Strategies
Several AWS services facilitate implementing caching strategies:
- Amazon ElastiCache: This service simplifies setting up, managing, and scaling distributed in-memory cache environments in the cloud. It integrates with popular open-source in-memory caching engines such as Memcached and Redis.
- AWS CloudFront: This CDN service can distribute data, videos, and APIs with low latency and high transfer speeds. Its edge caches store content closer to your users, reducing latency.
- Amazon RDS: The relational database service offers an in-memory caching layer that stores your most frequently accessed database items to improve overall application performance.
Understanding these caching strategies and AWS caching services is vital for those taking the AWS Certified Solutions Architect – Associate (SAA-C03) exam to design highly performant, scalable, and cost-efficient solutions. Moreover, the knowledge and skills obtained will be invaluable in real-world applications in building robust and high-performing cloud applications.
Practice Test
True or False: In AWS, cache eviction is the process of removing old data from cache to accommodate new data.
- True
- False
Answer: True
Explanation: When cache is at capacity, AWS employs a method called cache eviction to remove older data or less frequently accessed data to make room for new data.
True or False: AWS Elasticache is a service that makes it easier to launch, operate, and scale popular NoSQL databases in the cloud.
- True
- False
Answer: False
Explanation: This is a description of Amazon DynamoDB. AWS Elasticache improves the performance of web applications by allowing you to retrieve information from fast, in-memory caches, instead of relying entirely on slower disk-based databases.
Which type of cache is designed to catch and store the most recently requested data?
- A. Write-through cache
- B. Write-back cache
- C. LRU (Least Recently Used) cache
- D. Most Recently Used cache
Answer: C. LRU (Least Recently Used) cache
Explanation: LRU (Least Recently Used) cache is designed to remove the least recently used items first. This technique is typically used to manage memory within the cache.
True or False: AWS ElastiCache supports Memcached and Redis.
- True
- False
Answer: True
Explanation: AWS ElastiCache is a web service that makes it easy to deploy and run Memcached or Redis protocol-compliant server nodes in the cloud.
Which of the following is NOT a caching strategy in AWS?
- A. Write-through caching
- B. Write-back caching
- C. Write-around caching
- D. Write-in caching
Answer: D. Write-in caching
Explanation: The common caching strategies used in AWS are Write-through caching, Write-back caching, and Write-around caching. There is no such strategy as Write-in caching.
True or False: A cache miss occurs when the requested data is not found in the cache memory.
- True
- False
Answer: True
Explanation: A cache miss is a state where data is not found in the cache memory, causing the system to fetch the data from the original storage location, which can cause delays.
Which caching strategy is best to use when writes are much more common than reads?
- A. Write-through caching
- B. Write-back caching
- C. Write-around caching
- D. Read-through caching
Answer: B. Write-back caching
Explanation: In write-back caching, data is only written to the cache and the write to the main memory is postponed until necessary. This results in fewer writes and less write latency.
True or False: In the caching strategy “Write-back cache”, data is written to main memory as soon as it changes in the cache.
- True
- False
Answer: False
Explanation: In “Write-back cache”, data is written to cache first and then it is written to main memory later when system is less busy or as per the need.
True or False: In a “Write-around cache”, misses do not fill the cache, resulting in reduced cache churn.
- True
- False
Answer: True
Explanation: In a “Write-around cache”, data is written directly to permanent storage, bypassing the cache. This can reduce the cache becoming cluttered with write-intense operations.
In AWS ElastiCache, which caching engine provides persistent storage?
- A. Memcached
- B. Redis
- C. Both A and B
- D. Neither A nor B
Answer: B. Redis
Explanation: Among the two caching engines supported by AWS ElastiCache, Redis supports highly available and persistent storage, whereas Memcached does not.
Interview Questions
What is a cache hit in AWS?
A cache hit occurs when the data requested by your application is available in the Elasticache node’s in-memory cache.
What do TTL (Time to Live) settings pertain to in AWS caching strategy?
TTL settings control how long the data is stored in a cache before it’s automatically removed or updated.
How does cache eviction work in AWS?
When cache space is needed, AWS uses an eviction policy (like least recently used, or LRU) to determine which items to remove from the cache.
In AWS, what is meant by write-through cache?
Write-through cache refers to a caching strategy where data is simultaneously written to the cache and the backing store to ensure consistency.
Why would you use a lazy-loading strategy in AWS caching?
A lazy-loading strategy only loads data into the cache when necessary, reducing unnecessary use of memory resources.
What is the benefit of using cache clustering in AWS?
Cache clustering allows for horizontal scalability. If the existing cache nodes are not sufficient, you can simply add more.
How does in-memory caching improve application performance in AWS?
In-memory caching stores data in the RAM, reducing reliance on slower disk-based databases. This can lead to substantial improvements in application performance.
For caching, what is the function of Amazon CloudFront?
Amazon CloudFront is a content delivery service that caches content at edge locations, reducing latency and delivering content more quickly to end users.
What is write-around cache in AWS?
Write-around cache is a strategy where data is written directly to the backing store, bypassing the cache. This can be beneficial if cached data is unlikely to be re-read in the near future.
What is the purpose of AWS’s caching service, ElastiCache?
AWS ElastiCache improves the performance of web applications by allowing you to retrieve information from an in-memory caching system, instead of slower disk-based databases.
What is cache partitioning in the context of AWS caching strategies?
Cache partitioning or sharding, involves splitting the total cache size into smaller, more manageable pieces each aimed at storing a subset of the data.
What is the use of a distributed cache in AWS?
A distributed cache in AWS is used to store copies of data across multiple nodes within a system. This aids in improving the speed by limiting the amount of work an individual node has to deal with.
What is the effect of overutilizing caching in AWS?
Overutilizing cache resources may lead to higher costs, potential cache thrashing due to high turnover of data, and increased memory usage which could degrade application performance.
How can caching improve database performance in AWS?
Caching can improve database performance by storing frequently accessed data closer to the application layer. As a result, subsequent requests for the data can be served from the cache, reducing the need for expensive and time-consuming database read operations.
What is the purpose of a cold cache in AWS?
A cold cache is a cache that doesn’t have the requested data when a request is made. The need to request this data from a slower, disk-based database can result in an initial performance hit, but it allows the cache to ‘warm up’—the data becomes subsequently available for faster retrieval from cache.
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