Analyze Caching Opportunities

[knightempire]

Analyze Caching Opportunities Across the System

Description

This issue is focused on identifying where caching can be introduced throughout the system to enhance performance, reduce database load, and improve response times.

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Objective

• Analyze the entire system (pages, modules, APIs)
• Identify areas that are read-heavy, slow, or repetitive
• Determine the possibility, impact, and type of caching for each

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Tasks

• Review major pages and backend endpoints
• Identify static or slow-changing content
• Suggest appropriate caching method (in-memory, Redis, HTTP cache, etc.)
• Document risks (stale data, invalidation requirements)
• Prioritize based on performance impact

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Candidate Pages / Modules for Caching

Page / Component	Data Type	Cache Type	Notes
Product Listing	Product data	Redis / In-memory	Low frequency updates, high reads
Product Details Page	Product info	In-memory	Moderate update rate
Dashboard (Admin)	Aggregated stats	Redis	Can be refreshed periodically

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Considerations

• Pages with high traffic and low update frequency are best candidates.
• Must define cache invalidation logic for mutable data (e.g., products).
• Determine TTL (Time to Live) for each cached data point.
• Monitor cache hit/miss rates after implementation.

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Suggested Tools

• Redis – For centralized caching and TTL control
• node-cache / memory-cache – For quick in-process memory caching
• HTTP cache headers – For client-side and proxy-level caching
• CDN – For static assets or frontend-heavy content

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Notes

• This is a research and planning issue. No implementation required yet.
• Use findings from this analysis to open separate issues for implementation per module/page.

A well-planned caching strategy ensures fast, scalable, and efficient systems.