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The Power of Caching: Boosting API Performance and Scalability

DZone

Caching is the process of storing frequently accessed data or resources in a temporary storage location, such as memory or disk, to improve retrieval speed and reduce the need for repetitive processing. Bandwidth optimization: Caching reduces the amount of data transferred over the network, minimizing bandwidth usage and improving efficiency.

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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.

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Design Of A Modern Cache—Part Deux

High Scalability

The previous article described the caching algorithms used by Caffeine , in particular the eviction and concurrency models. This allows for quickly discarding new arrivals that are unlikely to be used again, guarding the main region from cache pollution.

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Redis vs Memcached in 2024

Scalegrid

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Under the hood, Titus is powered by Kubernetes , but it provides a thick layer of enhancements over off-the-shelf Kubernetes, to make it more observable , secure , scalable , and cost-efficient. Deployment: Cache To produce business value, all our Metaflow projects are deployed to work with other production systems.

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