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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

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How To Choose A Headless CMS

Smashing Magazine

Working for a major airline not even a decade ago, I can remember trying to model content for mobile devices (yes! From a developer perspective, not only static assets need to be cached on a CDN. Many headless CMSes cache content retrieved via RESTful or GraphQL APIs. Look out for: Caching of images and content via CDN.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

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Using Parallel Query with Amazon Aurora for MySQL

Percona

Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. I’m using the “Airlines On-Time Performance” database from [link] (You can find the scripts I used here: [link] ). The second and third run used the cached data. MySQL on ec2.

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