Concepts
In AWS, caching can be implemented at different layers of your architecture:
1. Edge Caching:
Using Amazon CloudFront, you can cache content at edge locations closer to your users. This reduces the load on your origin servers and decreases latency by serving content from a location nearest to the requester.
2. Application Caching:
Application-level caching involves storing frequently accessed data in memory to speed up data retrieval. AWS Elastic Cache offers two engines for this purpose: Redis and Memcached.
3. Object Caching:
Amazon S3 provides built-in caching headers that allow objects to be cached closer to the application or user, typically within the browser or intermediate proxies.
4. Database Query Caching:
AWS offers RDS (Relational Database Service) with query caching capabilities. RDS instances can be configured to cache the results of frequently run queries.
Edge Caching with Amazon CloudFront
With CloudFront, caching is managed via cache behaviors. You can specify which requests are cached and how long they are stored in cache. CloudFront also supports invalidation to manually clear cached content.
Here’s an example CloudFront cache behavior configuration in JSON:
{
“CacheBehaviors”: [
{
“PathPattern”: “/images/*”,
“TargetOriginId”: “myS3Origin”,
“ForwardedValues”: {
“QueryString”: false,
“Cookies”: {
“Forward”: “none”
}
},
“TrustedSigners”: [],
“ViewerProtocolPolicy”: “allow-all”,
“MinTTL”: 3600,
“DefaultTTL”: 86400,
“MaxTTL”: 31536000
}
]
}
This configuration sets how long images are cached (MinTTL, DefaultTTL, and MaxTTL), and it does not forward query strings or cookies, making it appropriate for static images.
Application Caching with AWS Elastic Cache
Elastic Cache dramatically speeds up data-heavy applications by caching information in-memory. Here is how the two services differ:
| Feature | Redis | Memcached |
|---|---|---|
| Data Types | Rich data types | Simple key-value pairs |
| Clustering | Sharding and replication for scaling and HA | Supports sharding |
| Persistence | Snapshotting and AOF for persistence | Non-persistent |
| Backup and Restore | Supported | Not supported |
| Advanced Data Operations | Pub/Sub, Lua scripting, transactions | Multi-threaded performance |
To optimize performance using Elastic Cache with Redis, you can leverage read replicas to offload read traffic from the primary database server, allowing horizontal scaling.
Object Caching with Amazon S3
With Amazon S3, configuring caching involves setting the proper cache-control headers on your objects:
{
“CacheControl”: “max-age=86400, must-revalidate”
}
This header instructs clients and proxies on how long to store the cached version of the object, specified in seconds.
Database Query Caching with RDS
Database query caching is largely managed within the database engine itself. In RDS, for example, you can adjust the query cache parameters such as query_cache_size and query_cache_limit in MySQL to control the amount of memory allocated to caching and the maximum size for individual cache entries.
Considerations for Caching Strategies
While caching can offer significant benefits, it requires careful planning:
- Cache Invalidation: Decide when cache entries should be invalidated or updated, keeping in mind data freshness.
- TTL (Time to Live) Settings: Set appropriate TTL values to balance data freshness with performance benefits of caching.
- Cost Management: Understand the cost implications of caching, as both CloudFront and Elastic Cache incur charges based on resource usage.
- Security: Ensure sensitive data is handled appropriately and not exposed through caching mechanisms.
Overall, an understanding of caching strategies on AWS is valuable for the Solutions Architect – Associate exam, and in practice, it can make a substantial difference in the architecture you design. Proper implementation of caching can enhance the performance, reduce costs, and improve the scalability of your AWS-hosted applications.
Answer the Questions in Comment Section
True or False: Amazon Elasticache supports both Memcached and Redis cache engines.
- True
- False
Answer: True
Explanation: Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud, and it supports both Memcached and Redis cache engines.
Which AWS service can be used as a dedicated cache to reduce database load?
- Amazon RDS
- Amazon S3
- Amazon ElastiCache
- AWS Lambda
Answer: Amazon ElastiCache
Explanation: Amazon ElastiCache is a fully managed in-memory cache service that can be used to reduce database load by caching frequently accessed data.
True or False: AWS CloudFront can be used as a caching layer for static and dynamic content.
- True
- False
Answer: True
Explanation: AWS CloudFront is a content delivery network (CDN) service that caches static and dynamic web content at edge locations close to users to reduce latency.
In Amazon CloudFront, what is the term for the time period a file is available in the cache before CloudFront checks for a newer version?
- Time to Live (TTL)
- Expiration Period
- Cache Duration
- Refresh Interval
Answer: Time to Live (TTL)
Explanation: Time to Live (TTL) is the period that a file is available in the cache before CloudFront checks with the origin server to see if a newer version of the file is available.
True or False: Write-through caching writes data to the cache and the underlying database at the same time.
- True
- False
Answer: True
Explanation: Write-through caching is a caching strategy where data is written to both the cache and the underlying storage or database simultaneously.
Which caching strategy ensures data is written to the cache only if it is successfully written to the database first?
- Lazy Loading
- Write-Around Caching
- Write-Through Caching
- Write-Back Caching
Answer: Write-Through Caching
Explanation: Write-Through Caching ensures that data is only written to the cache after it has been successfully persisted to the underlying database.
True or False: With lazy-loading caching strategy, cache space can be saved as only the requested data is cached.
- True
- False
Answer: True
Explanation: Lazy-loading caches data on-demand as it is requested, which can save cache space since only needed data is stored in the cache.
Which AWS service allows you to automatically move infrequently accessed data to a more cost-effective storage class?
- Amazon S3 Intelligent-Tiering
- Amazon Glacier
- AWS Snowball
- Amazon EFS
Answer: Amazon S3 Intelligent-Tiering
Explanation: Amazon S3 Intelligent-Tiering automatically moves data to the most cost-effective access tier when access patterns change, without performance impact or operational overhead.
True or False: Amazon S3 can serve as an origin store for CloudFront, but it cannot be configured to cache data.
- True
- False
Answer: False
Explanation: Amazon S3 can indeed serve as an origin store for CloudFront, and CloudFront can be configured to cache data from Amazon S3 to improve delivery speed.
A read-heavy database should primarily use which type of cache strategy?
- Write-Around Caching
- Write-Back Caching
- Read-Through Caching
- Write-Through Caching
Answer: Read-Through Caching
Explanation: Read-Through Caching is a strategy where all read requests are first directed to the cache, making it an effective approach for read-heavy databases where most data is frequently accessed.
True or False: Amazon Aurora replicates data across multiple Availability Zones by default for caching purposes.
- True
- False
Answer: False
Explanation: Amazon Aurora replicates data across multiple Availability Zones for high availability and durability, not specifically for caching purposes.
To refresh specific content in an AWS CloudFront distribution before the TTL expires, what operation must you perform?
- Invalidate the content
- Update the content
- Restart the CloudFront distribution
- Increase the TTL
Answer: Invalidate the content
Explanation: To refresh content in a CloudFront distribution before the TTL expires, the content must be invalidated, which forces CloudFront to fetch a fresh copy from the origin on the next request.
Great blog post! Very informative.
Thanks for this, cleared up a lot of confusion I had about caching strategies.
Can someone explain the difference between write-through and write-back caching in an AWS context?
How does AWS ElastiCache handle cache invalidation?
The way you explained caching strategies is top-notch. Appreciate it!
I’ve been using Redis with AWS ElastiCache, and I’ve found it really effective for session management.
Is there a significant performance difference between Redis and Memcached in ElastiCache?
I didn’t quite understand the part where the author talks about lazy loading. Can anyone clarify?