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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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Caching Across Layers in Software Architecture

DZone

The purpose of this article is to help readers understand what is caching, the problems it addresses, and how caching can be applied across layers of system architecture to solve some of the challenges faced by modern software systems.

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Front-End: Cache Strategies You Should Know

DZone

Caches are very useful software components that all engineers must know. It is a transversal component that applies to all the tech areas and architecture layers such as operating systems, data platforms, backend, frontend, and other components. What Is a Cache?

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PolyScale.ai – Scaling MySQL & PostgreSQL with Global Caching

Scalegrid

Modern application architectures such as the JAMstack enforce the separation […]. However, as any development and/or DevOps team tasked with performance improvements will attest, making data-driven apps fast globally is “non-trivial”.

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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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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. The team at RevenueCat created an open-source memcache client that provides several advanced features.

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Hashnode Creates Scalable Feed Architecture on AWS with Step Functions, EventBridge and Redis

InfoQ

Hashnode created a scalable event-driven architecture (EDA) for composing feed data for thousands of users. The company used serverless services on AWS, including Lambda, Step Functions, EventBridge, and Redis Cache. The solution leverages Step Functions' distributed maps feature that enables high-concurrency processing.