Tutorial: AWS Certified Developer - Associate (DVA-C02)

Caching

Concepts

Client-side caching involves storing data locally on the client device, such as a web browser or a mobile app. The idea is to prevent the need for the client to repeatedly fetch the same data from the server, thereby reducing latency and server load.

For example, an S3 bucket can be configured to add cache control headers to the responses for static assets so that a web browser knows how long to cache those resources. Here’s a snippet of how to set the Cache-Control header using the AWS CLI:

aws s3 cp s3://mybucket/myfile.txt s3://mybucket/myfile.txt –metadata-directive REPLACE –cache-control max-age=86400

With this command, myfile.txt will have a Cache-Control header that instructs the browser to cache it for one day (86400 seconds).

Edge Caching

AWS enables edge caching through Amazon CloudFront, a content delivery network (CDN) service that caches copies of your content at edge locations close to your users to minimize latency.

When using CloudFront, you can set caching policies that determine how long your content is cached on the edge servers. For example, you can create a cache policy with specific parameters like TTLs (time-to-live), headers, cookies, and query strings that will influence the cache behavior.

In-Memory Data Stores

For more dynamic applications, in-memory caching can significantly enhance performance. AWS offers managed in-memory data stores such as Amazon ElastiCache, which supports two open-source in-memory engines: Redis and Memcached.

Amazon ElastiCache for Redis

ElastiCache for Redis is a popular choice for tasks like session caching, database caching, and message queuing. It offers features such as data persistence, backup and restore capabilities, and support for complex data types.

An example scenario could be caching database query results to speed up read-heavy applications. Here is an example of using the SET and GET operations in Redis (pseudo-code):

def get_user_profile(user_id):
profile = redis_client.get(f”profile_{user_id}”)
if not profile:
profile = database.query(“SELECT * FROM user_profiles WHERE id = %s”, user_id)
redis_client.setex(f”profile_{user_id}”, 3600, profile)
return profile

In this pseudocode, a function checks whether a user’s profile is present in the Redis cache. If not, it queries the database and stores the result in Redis with a TTL of one hour.

Amazon ElastiCache for Memcached

ElastiCache for Memcached is well-suited for simplifying caching architectures. It’s useful for use cases requiring a large cache across multiple nodes and can be easily scaled up or down.

Example use cases include caching the results of I/O-intensive database queries or storing session states. Here’s how you might set and get a cache item using Memcached (pseudo-code):

from pymemcache.client import base

client = base.Client((‘localhost’, 11211))

def cache_set(key, value, timeout=180):
client.set(key, value, timeout)

def cache_get(key):
return client.get(key)

Caching Strategies Comparison

Caching Type	Use Case	AWS Service	Features
Client-Side	Static assets caching for web applications	Amazon S3	– Set cache control headers – Reduce server load
Edge Caching	Content delivery with low latency globally	Amazon CloudFront	– Edge locations – Cache policies – Supports HTTPS
In-Memory (Redis)	Advanced data structure caching, data persistence	Amazon ElastiCache	– Data structures support – Read/Write scaling
In-Memory (Memcached)	Simple caching, large distributed systems	Amazon ElastiCache	– Horizontal scaling – Multi-threaded architecture

By understanding the different caching strategies and their use cases, developers preparing for the AWS Certified Developer – Associate exam can make informed decisions about which approach to take for their specific application needs.

These caching mechanisms can greatly improve performance, cost-efficiency, and user experience of AWS-hosted applications, which are key aspects that are covered in the AWS Certified Developer – Associate exam. It’s important for developers to not only understand these concepts but also know how to implement and manage them through AWS’ suite of services.

Answer the Questions in Comment Section

Caching refers to storing data in a temporary storage area to improve system performance.

True
False

Answer: True

Explanation: Caching involves storing data in a temporary storage area to improve the speed of data retrieval and overall system performance by reducing the need to repeatedly access the underlying slower storage layer.

AWS Elasticache supports which of the following caching engines? (Select TWO)

Redis
Memcached
MongoDB
MySQL

Answer: Redis, Memcached

Explanation: AWS ElastiCache supports two caching engines: Redis and Memcached, which are both popular open-source in-memory data store and caching systems.

In Amazon CloudFront, the TTL (Time to Live) defines:

The maximum amount of time that a DNS record can be cached.
The maximum amount of time an object is allowed to stay in a CloudFront Edge Location before it is checked for a new version.
The duration for which a user session is maintained.
The time it takes for an EC2 instance to start up.

Answer: The maximum amount of time an object is allowed to stay in a CloudFront Edge Location before it is checked for a new version.

Explanation: TTL in Amazon CloudFront specifies the duration for which an object is allowed to be cached in an Edge Location. After this time, CloudFront checks the origin server for a newer version of the object.

What is a benefit of implementing caching in a distributed system?

Reduces the amount of computation needed
Eliminates the need for a database
Increases the data security
Simplifies application code

Answer: Reduces the amount of computation needed

Explanation: Caching reduces the amount of computation and database reads by temporarily storing copies of content. This can help to significantly increase the efficiency of data retrieval.

Amazon API Gateway provides a caching feature to cache your endpoint’s responses.

True
False

Answer: True

Explanation: Amazon API Gateway allows you to enable caching for your APIs, which caches the endpoint responses, reducing the number of calls made to your backend services and improving the latency of requests to your API.

When implementing caching, which of the following factors does NOT need to be considered?

Cache invalidation strategy
Storage capacity of the cache
Color scheme of the user interface
Data consistency between the cache and the source

Answer: Color scheme of the user interface

Explanation: Color scheme of the user interface is not relevant to the implementation of caching as it does not affect the performance or data handling of caching mechanisms.

What AWS service is primarily used for speeding up distribution of static and dynamic web content to users?

AWS Lambda
Amazon CloudFront
Amazon S3
AWS Elastic Beanstalk

Answer: Amazon CloudFront

Explanation: Amazon CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds.

What type of caching involves storing application data in a distributed key-value data store for quick access?

Disk caching
Object caching
Database caching
Edge caching

Answer: Object caching

Explanation: Object caching refers to storing application data, often as key-value pairs, in a distributed cache like Redis or Memcached that can be quickly accessed by the application when needed.

Which of the following AWS services does not provide caching capabilities?

Amazon CloudFront
AWS Elasticache
Amazon API Gateway
Amazon EC2

Answer: Amazon EC2

Explanation: Amazon EC2 provides scalable computing capacity in the Amazon Web Services cloud and is not primarily used for caching, unlike services like Amazon CloudFront, AWS ElastiCache, and Amazon API Gateway.

Can Amazon DynamoDB be directly integrated with ElastiCache?

Answer: No

Explanation: Amazon DynamoDB cannot be directly integrated with ElastiCache. However, you can implement caching logic within your application to store frequently accessed DynamoDB data in ElastiCache.

ElastiCache for Redis provides support for both primary-replica replication and partitioning data across shards.

True
False

Answer: True

Explanation: ElastiCache for Redis supports primary-replica replication for high availability and supports partitioning data across multiple shards (nodes) for horizontal scaling and increased performance.

When updating an item in a cache, best practice advises that you also update the data store immediately to prevent stale data issues.

True
False

Answer: False

Explanation: While it’s important to keep the data store and cache in sync, immediately updating the data store is not always the best practice due to potential performance impacts. Instead, using an eventual consistency approach or a well-defined cache invalidation strategy can be more efficient.