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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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Key Advantages of DBMS for Efficient Data Management

Scalegrid

Additionally, DBMS is critical in reservation systems, where it stores and manages records like ticket bookings, schedules, seat allocation, and other pertinent transaction data for airlines, hotels, and railways. By implementing data abstraction techniques, these challenges can be addressed more effectively.

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Reducing The Web’s Carbon Footprint: Optimizing Social Media Embeds

Smashing Magazine

of global emissions (similar to the airline industry), and rising. These numbers are based on first-page load — caching seems very efficient for subsequent page loads. Measuring the carbon footprint of the web isn’t an exact science, but a report by the BBC in 2020 estimates that all internet activity accounts for around 3.7%

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Typical uses include storing session-state and ecommerce shopping carts, product descriptions, airline reservations, financial portfolios, news stories, online learning data, and many others.

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The Power of Integrated Analytics Within an IMDG

ScaleOut Software

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Typical uses include storing session-state and ecommerce shopping carts, product descriptions, airline reservations, financial portfolios, news stories, online learning data, and many others.

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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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