Caching & Latency in AWS Serverless

Introduction

In serverless architectures, caching is essential to reduce latency and improve performance. AWS provides several services to implement caching strategies effectively. This lesson explores the fundamentals of caching, its importance in AWS serverless applications, and best practices to optimize application performance.

Key Concepts

What is Caching?

Caching is the process of storing copies of files or data in a temporary storage location (cache) to make future requests for that data faster.

Latency

Latency refers to the time it takes for a request to travel from the client to the server and back. Reducing latency improves the user experience significantly.

Types of Caching in AWS Serverless

API Gateway Caching
Lambda Function Caching
DynamoDB DAX (DynamoDB Accelerator)
CloudFront Caching

Caching Strategies

API Gateway Caching

API Gateway allows caching of responses to reduce backend load and improve response times. Enable caching on specific methods and configure the cache size and time-to-live (TTL).

Note: Ensure to set appropriate caching keys to avoid caching sensitive data.

Lambda Function Caching

Lambda functions can utilize in-memory caching (like Redis or Memcached) to store frequently accessed data. This can significantly reduce execution time, especially for repetitive tasks.

Implementation

Step 1: Enable Caching on API Gateway

To enable caching on an API Gateway method, follow these steps:

Open the API Gateway console.
Select your API and navigate to the "Resources" section.
Select the method for which you want to enable caching.
In the Method Execution pane, select "Method Request" and expand "Caching." Enable caching and set the TTL.

Step 2: Configure Cache Settings

Configure the cache settings according to the expected load and usage patterns. For example, set a higher TTL for rarely changing data and a lower TTL for frequently updated data.

Code Example: Enable Caching using AWS CLI


aws apigateway update-integration-response \
    --rest-api-id  \
    --resource-id  \
    --http-method GET \
    --status-code 200 \
    --patch-operations op=add,path=/cacheKey, value='method.request.querystring.param'

Best Practices

Use cache keys wisely to ensure that cached data is relevant.
Monitor cache hit rates to optimize performance.
Implement cache invalidation strategies to keep data fresh.
Test the impact of caching on application performance in a staging environment.

FAQ

What is the maximum cache size in API Gateway?

The maximum cache size for API Gateway is 500 MB.

How can I clear the cache in API Gateway?

You can clear the cache by invalidating the cache key or by using the console to delete cached items directly.

What is the difference between CloudFront and API Gateway caching?

CloudFront caching is at the CDN level, caching responses at edge locations, while API Gateway caching is specific to API responses and reduces load on backend services.