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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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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

In this post, I’m going to break these processes down into each of: ? Caching them at the other end: How long should we cache files on a user’s device? This shows us the sheer power and importance of compression, so ensure you have the best setup possible for your infrastructure. Cache This is the easy one.

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Cache-Control for Civilians

CSS Wizardry

To this end, having a solid caching strategy can make all the difference for your visitors. ?? How is your knowledge of caching and Cache-Control headers? That being said, more and more often in my work I see lots of opportunities being left on the table through unconsidered or even completely overlooked caching practices.

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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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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

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Kubernetes in the wild report 2023

Dynatrace

Findings provide insights into Kubernetes practitioners’ infrastructure preferences and how they use advanced Kubernetes platform technologies. Kubernetes infrastructure models differ between cloud and on-premises. Kubernetes infrastructure models differ between cloud and on-premises. Kubernetes moved to the cloud in 2022.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Central engineering teams enable this operational model by reducing the cognitive burden on innovation teams through solutions related to securing, scaling and strengthening (resilience) the infrastructure. All these micro-services are currently operated in AWS cloud infrastructure.