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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.

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How to Clear Cache and Cookies on a Customer’s Device

CSS Wizardry

If you work in customer support for any kind of tech firm, you’re probably all too used to talking people through the intricate, tedious steps of clearing their cache and clearing their cookies. set ( ' Clear-Site-Data ' , ' cache ' ); } else { res. Well, there’s an easier way! Something maybe a little like this: const referer = req.

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Image Processing Insights

KeyCDN

KeyCDN has significantly simplified the way images are transformed and delivered with our Image Processing service. Our Image Processing service makes it easy to do that. Our Image Processing service will automatically optimize the image quality and reduce the size of the image if no query string is provided.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources. Observing AI models Running AI models at scale can be resource-intensive.

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WebP Caching has Landed!

KeyCDN

We’re happy to announce that WebP Caching has landed! The new feature integrates into the existing CDN and is available to all customers. How Does WebP Caching Work? Enable the Feature for your Zones Cache Key WebP can be enabled for all Pull Zones. It’s all about the accept header sent from the client.

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PostgreSQL Connection Pooling: Part 3 – Pgpool-II

Scalegrid

It supports high-availability, provides automated load balancing, and has the intelligence to balance load between masters and slaves so write loads are always directed at masters, while read loads are directed to slaves. The Pgpool-II parent process forks 32 child processes by default – these are available for connection.

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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

These integrations are implemented through Metaflow’s extension mechanism which is publicly available but subject to change, and hence not a part of Metaflow’s stable API yet. In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training.

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