Caching with Amazon ElastiCache and DAX
Learn how in-memory caching reduces latency and database load for Lambda functions using ElastiCache (Redis) and DynamoDB Accelerator (DAX).
Caching with Amazon ElastiCache and DAX is a free Serverless AWS Lambda Development lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless AWS Lambda Development learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Why Cache?
Reading from a database on every invocation is slow and expensive. A cache keeps hot data in memory so repeated reads are near-instant.
Two AWS Cache Options
Two managed caches pair well with Lambda:
- ElastiCache (Redis or Memcached) for general key-value caching.
- DAX, a cache built specifically for DynamoDB.
Cache-Aside Pattern
The most common pattern: check the cache first, fall back to the database on a miss, then store the result for next time.
def get_user(cache, db, uid):
cached = cache.get(uid)
if cached is not None:
return cached
value = db.load(uid)
cache.set(uid, value, ttl=300)
return valueSetting a TTL
A time to live expires stale entries automatically. Short TTLs keep data fresh; long TTLs maximize hit rate. Choose based on how often data changes.
DAX in One Line
DAX is a write-through cache for DynamoDB. You point the DynamoDB client at the DAX endpoint and reads transparently use the cache.
import amazondax
client = amazondax.AmazonDaxClient(endpoint_url='dax://my-cluster')
resp = client.get_item(TableName='users', Key={'id': {'S': uid}})Caches Live in a VPC
ElastiCache and DAX run inside a VPC. Your Lambda must be VPC-attached with the right security group to reach the cache.
Reuse Connections
Create the cache client outside the handler so it persists across warm invocations, avoiding a new connection on every call.
cache = connect_to_redis() # module scope, reused
def handler(event, context):
return cache.get(event['key'])Invalidate on Write
When data changes, update or delete the cache entry so readers do not see stale values. Write-through and write-around are two strategies.
Memcached vs Redis
Memcached is simple and multi-threaded; Redis adds data structures, persistence, and replication. Pick Redis when you need richer features.
When Not to Cache
Caching adds complexity. Skip it for rarely read data or data that must always be perfectly current, where staleness is unacceptable.
Measure the Hit Rate
Track the cache hit ratio in CloudWatch. A low ratio means the cache is not helping and your TTL or keys may need tuning.
Quick Check
Test your caching knowledge.
Recap
You learned to cut latency and DB load with ElastiCache and DAX using the cache-aside pattern, TTLs, connection reuse, invalidation, and hit-rate monitoring.
Frequently asked questions
Is the “Caching with Amazon ElastiCache and DAX” lesson free?
Yes — the full text of “Caching with Amazon ElastiCache and DAX” is free to read here on the web, and the Serverless AWS Lambda Development course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless AWS Lambda Development course, upgrade to CoddyKit PRO.
What will I learn in “Caching with Amazon ElastiCache and DAX”?
Learn how in-memory caching reduces latency and database load for Lambda functions using ElastiCache (Redis) and DynamoDB Accelerator (DAX). You practise Serverless AWS Lambda Development with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless AWS Lambda Development?
No prior experience is required. Serverless AWS Lambda Development on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Caching with Amazon ElastiCache and DAX” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless AWS Lambda Development lesson?
Yes. Every Serverless AWS Lambda Development lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Integrating with DynamoDB
- S3 for File Storage and Events
- Choosing the Right Data Store
- Caching with Amazon ElastiCache and DAX