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Architectural Insights: Designing Efficient Multi-Layered Caching With Instagram Example

DZone

Caching is a critical technique for optimizing application performance by temporarily storing frequently accessed data, allowing for faster retrieval during subsequent requests. Multi-layered caching involves using multiple levels of cache to store and retrieve data.

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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

When serving and storing files on the web, there are a number of different things we need to take into consideration in order to balance ergonomics, performance, and effectiveness. Caching them at the other end: How long should we cache files on a user’s device? Cache This is the easy one. main.af8a22.css main.af8a22.css

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Designing Instagram

High Scalability

Design a photo-sharing platform similar to Instagram where users can upload their photos and share it with their followers. High Level Design. from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. Component Design.

Design 334
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How DoorDash Rearchitected its Cache to Improve Scalability and Performance

InfoQ

DoorDash rearchitected the heterogeneous caching system they were using across all of their microservices and created a common, multi-layered cache providing a generic mechanism and solving a number of issues coming from the adoption of a fragmented cache. By Sergio De Simone

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Performance Game Changer: Browser Back/Forward Cache

Smashing Magazine

Performance Game Changer: Browser Back/Forward Cache. Performance Game Changer: Browser Back/Forward Cache. With that caveat out of the way, let’s get to the guts of the article: What is the Back/Forward Cache and why does it matter so much? Didn’t The HTTP Cache Do All That Anyway? Barry Pollard.

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How RevenueCat Manages Caching for Handling over 1.2 Billion Daily API Requests

InfoQ

RevenueCat extensively uses caching to improve the availability and performance of its product API while ensuring consistency. The company shared its techniques to deliver the platform, which can handle over 1.2 billion daily API requests. By Rafal Gancarz

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Fast memcpy, A System Design

ACM Sigarch

We look here at a Gedankenexperiment: move 16 bytes per cycle , addressing not just the CPU movement, but also the surrounding system design. A lesser design cannot possibly move 16 bytes per cycle. This base design can map easily onto many current chips. Cache pollution is addressed in a section below.). byte loads.

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