Serverless AWS Lambda Development · 课时

使用 Amazon ElastiCache 和 DAX 进行缓存

了解使用 ElastiCache（Redis）和 DynamoDB Accelerator（DAX）为 Lambda 函数提供内存缓存，如何降低延迟和数据库负载。

使用 Amazon ElastiCache 和 DAX 进行缓存 是 CoddyKit 上的免费 Serverless AWS Lambda Development 课时。这是第 4 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Serverless AWS Lambda Development 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Serverless AWS Lambda Development 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

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 value

Setting 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.

常见问题解答

「使用 Amazon ElastiCache 和 DAX 进行缓存」课时是免费的吗？

是的 — 「使用 Amazon ElastiCache 和 DAX 进行缓存」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Serverless AWS Lambda Development 课程的其余内容，请升级到 CoddyKit PRO。 Serverless AWS Lambda Development 课程共包含 4 节课。

「使用 Amazon ElastiCache 和 DAX 进行缓存」这节课中我会学到什么？

了解使用 ElastiCache（Redis）和 DynamoDB Accelerator（DAX）为 Lambda 函数提供内存缓存，如何降低延迟和数据库负载。你通过在浏览器中直接运行的动手代码来练习 Serverless AWS Lambda Development，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Serverless AWS Lambda Development 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Serverless AWS Lambda Development 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 4 节课，共 4 节。

「使用 Amazon ElastiCache 和 DAX 进行缓存」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Serverless AWS Lambda Development 课中编写并运行代码吗？

能。每节 Serverless AWS Lambda Development 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

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