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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 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.

Cache 246
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Front-End: Cache Strategies You Should Know

DZone

Caches are very useful software components that all engineers must know. In this article, we are going to describe what is a cache and explain specific use cases focusing on the frontend and client side. In this article, we are going to describe what is a cache and explain specific use cases focusing on the frontend and client side.

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

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Speed Up Presto at Uber with Alluxio Local Cache

Uber Engineering

Uber’s interactive analytics team shares how they integrated Alluxio’s data caching into Presto, the SQL query engine powering thousands of daily active users on petabyte scale at Uber, to dramatically reduce data scan latencies through leveraging Presto on local disks.

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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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Not a Single Trace

DZone

Your team celebrates a success story where a trace identified a pesky latency issue in your application's authentication service. It turns out that the fix we made did improve performance at one point but created a situation in which key information was never cached. But the celebrations are short-lived.

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