Lesson 3: Caching

Why Cache?

Caching is the process of storing copies of data in a temporary storage location (cache) so that future requests for that data can be served faster.

• Reduce Latency: Memory is faster than disk.
• Reduce Load: Fewer queries to the database.

Caching Strategies

Cache-Aside (Lazy Loading)

1. App checks cache.
2. If miss, App reads from DB.
3. App writes to cache.

• Pros: Only requested data is cached.
• Cons: Initial request is slow (cache miss).

Write-Through

1. App writes to cache and DB simultaneously.

• Pros: Data in cache is always fresh.
• Cons: Slower writes.

Write-Back (Write-Behind)

1. App writes to cache only.
2. Cache writes to DB asynchronously.

• Pros: Fast writes.
• Cons: Data loss risk if cache fails before syncing.

Eviction Policies

When the cache is full, what do you remove?

• LRU (Least Recently Used): Remove the item that hasn’t been used for the longest time.
• LFU (Least Frequently Used): Remove the item used least often.
• FIFO (First In, First Out): Remove the oldest item.

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🛠️ Sruja Perspective: Modeling Caches

In Sruja, caches are often modeled as separate containers or components.

import { * } from 'sruja.ai/stdlib'


Catalog = system "Product Catalog System" {
    WebApp = container "Storefront" {
        technology "Node.js"
    }

    ProductCache = container "Product Cache" {
        technology "Memcached"
        description "Caches product details using LRU eviction."
    }

    ProductDB = container "Product Database" {
        technology "MongoDB"
    }

    WebApp -> ProductCache "Read (Cache-Aside)"
    WebApp -> ProductDB "Read on Miss"
}

view index {
include *
}